Events

Today Workday provided an update on its acquisition of Peakon, now called “Workday Peakon Employee Voice,” roughly six months since the deal closed. Before getting into the details of this update, we’re going to provide some context on the employee engagement and experience market. We’ll then turn to the goals of the acquisition and what we can tell so far about how well Workday Peakon Employee Voice is meeting those goals.

The Employee Engagement & Experience Market

Growing Rapidly

As we wrote earlier this year, employee engagement and experience technology has been a lifeline for leaders hampered by work from home and unable to interact directly with their employees. It enabled leaders to keep a check on employee pulse throughout the pandemic, especially as fatigue, burnout, and stress levels have all boomed. It has also helped leaders to understand changing perceptions of return to office plans and adjust at a much faster velocity than ever before. Further, leaders are increasingly using these solutions to better understand diversity, equity, inclusion, and belonging (DEIB) within their organizations.

The pandemic did not create the employee engagement and experience market – it was going full steam ahead before March 2020. However, the events of 2020 turned that steam into rocket fuel. As a result, the employee engagement and experience market was one of the fastest growing people analytics tech segments in 2020, and when we complete our study of 2021, we expect it to be THE fastest growing segment. Further, we believe that growth will continue well into the future, as senior leaders have just begun to really grasp the power of people data.

Quite Crowded and Complex

Yet, the employee engagement (eng) and experience (exp) market is quite crowded and complex, especially when you consider all of the vendors who have added employee engagement to their core offerings. For example, let’s take 4 areas we’ve seen converging for the last 3 years or so:

• Employee engagement / experience
• Performance management
• Recognition
• People data integration

When you look at the intersecting points of all these areas and vendors, you get a chart that looks like Figure 1. There are approximately 30 vendors by our count in the employee engagement or experience market, and we are certain there are more than we have on this chart (if you’re one of them, feel free to email us at [email protected], and we will get you on our list).

We are seeing so much overlap because vendors and customers realize that it is no longer realistic to keep these concepts separate. How do you understand engagement without also understanding performance feedback? And how do you give performance feedback without also giving recognition? And how do you understand any of this without solid people analytics?

As a result, we are seeing a need for significant data integration – which is leading to interesting data partnerships, such as the People Intelligence Alliance, as well as acquisitions.

And Very Acquisitive

And there have been lots of acquisitions – and on multiple levels. For example, there have been acquisitions where somewhat larger engagement / experience or performance providers bought each other, such as:

• Culture Amp (Eng/Exp) purchased Zugata (PM) in 2019
• Betterworks (PM) purchased Hyphen (Eng/Exp) in 2020
• Perceptyx (Eng/Exp) purchased Waggl (Eng/Exp) in 2021
• LTG / People Fluent (Core HR, Learning, etc.) purchased Reflektive (PM and Eng/Exp) in 2021

Many of these vendors bought their smaller counterparts so as to expand their feature set, acquire new customers, increase engineering capabilities, etc.

But we’ve also seen the much bigger HR Tech vendors buying best-of-breed engagement / experience solutions, such as:

• Microsoft purchased LinkedIn / Glint in 2018
• SAP purchased Qualtrics (2018), then sold it in 2021, but maintained a majority ownership stake
• Workday purchased Peakon in 2021

These bigger vendors’ reasons for purchasing employee engagement and experience platforms were different: it was a customer value and data play. They were looking to do three things:

• Provide a high-quality engagement / experience solution for customers
• Create or round-out their offerings in the four areas highlighted above
• Integrate data from these different talent areas more smoothly

Given those three goals, how is Workday’s acquisition of Peakon going, 6 months in?

The Integrated Product: Workday Peakon Employee Voice

As we wrote in the acquisition blog, we think this purchase made a lot of sense. In short, it filled a hole in capability for Workday, Peakon is a solid product, and there was strong cultural alignment between the two orgs. Let’s talk though, about how this acquisition is performing, given the goals mentioned immediately above.

Goal 1: High Quality Engagement Solution

The new, integrated product, Workday Peakon Employee Voice, appears to be following Peakon’s pre-acquisition trend of delivering strong customer value. Customers are using the solution to take insights on topics such as engagement, diversity, equity, inclusion, and belonging (DEIB), and health and wellness and turn them into action through conversations, personal dashboards, team collaboration, and contextual learning resources.

Customers are rewarding Workday Peakon for the offering, as indicated by:

• Commercial success of the new product has been significant, with Peakon experiencing a dramatic acceleration of its business
• Growth has come from new Peakon customers as well as existing Workday customers

In addition, according to Workday, early customer feedback has focused on the ease of use of the platform, the ability for employees to provide feedback easily to leaders, and the use of natural language processing (NLP) to classify comments more easily (especially as positive, neutral, or negative) so they can respond much faster.

Workday is selling the product within its larger suite of products as well as a separate SKU. This is important, because it means that customers outside the Workday HCM ecosystem can still buy it.

Given all the above, it appears the acquisition is very much so meeting this goal.

Goal 2: Round Out Talent Offerings

As mentioned above, a second reason many of these large HR tech providers bought the smaller engagement / performance management vendors was to round out their overall talent offerings.

Peakon clearly ticks this box when it comes to employee engagement and experience (as discussed immediately above). What’s not yet totally clear, though, is the extent to which it does the same for the performance management offering.

Workday’s current performance management offering could use some improvement, especially when it comes to serving more agile performance management approaches. Prior to acquisition, Peakon offered Grow, which was its performance management solution targeted at organizations leveraging a more agile approach. This product is still available to customers, so in this way Workday ticks this box.

However, Grow is not yet integrated into the broader HCM suite in the same way as Workday Peakon Employee Voice. This means that Grow and the existing Workday performance management solution do not talk to each other yet. As a result, there isn’t really a way for existing Workday performance management customers to seamlessly adopt the agile approach offered by Grow.

Workday indicated performance management is a high area of interest and they plan to continue building out the capabilities of Grow and to integrate them into their standard performance review capability. We don’t yet have a timeline yet on when that might happen, though.

Goal 3: Integrated Data

The opportunity to integrate Peakon and Workday data together is one of the most exciting aspects of this acquisition – and one Workday is working on now.

As many of you know, Workday offers its VIBE^TM Index (VIBE stands for Value Inclusion, Belonging, and Equity), which provides insights on a wide variety of diversity characteristics in the following areas:

• Hires
• Promotions
• Leadership
• Belonging
• Attrition

Yet, VIBE only has insights on the current state and how it compares to benchmarks – it gives little insight into how an organization got to that point.

This is where Peakon’s insights – specifically from its Include product – come in. Workday is integrating Workday Peakon Employee Voice insights into the VIBE^TM Index, so that leaders will be able to both see what is happening and why. You can imagine a world where, instead of just sharing stories on how representation has changed (as shown in Figure 2), the VIBE^TM Index could also share how key drivers of engagement or turnover have changed for a specific population, and what that might portend for the future.

This integration of Workday Peakon Employee Voice data into VIBE^TM is still in process, but should be available relatively soon. Workday is also working to integrate Workday Peakon Employee Voice data into other parts of its People Analytics solution as well as into Prism, but those are not yet available.

Given all the above, we see Workday working quickly to meet this goal, though it hasn’t been fully achieved yet.

Looking to the Future

Looking forward, there are lots of other interesting ways Workday Peakon Employee Voice capabilities could be integrated into both other aspects of Workday as well as into the overall flow of work.

Our understanding is that Workday is looking to use Workday Peakon Employee Voice strategically throughout the employee experience, by asking targeted questions at specific trigger points (e.g., return to office, return from parental / care leave, 30/60/90-day milestones). The solution is currently integrated with both Microsoft Teams and Slack via the company's Workday Everywhere initiative and we image they will come up with additional ways to put the solution into the everyday flow of work.

From everything we can tell, it appears the acquisition of Peakon is going well, and we are excited to see Workday work to get these integrations – particularly data and of the performance management products – completed. By doing this, Workday will be able to realize its customer value proposition of delivering one data model and a seamless experience more fully. We look forward to continuing to hear from customers as this happens.

Why this report, and why now?

We started paying attention to coaching technology well over 2 years ago. At first, it was out of curiosity: we were seeing vendors developing new ways to address a very old learning technique. Earlier this year, we took a look at our vendor database and realized that we had over 45 vendors claiming to provide some sort of coaching functionality.

Coaching technology has exploded. As orgs have developed a larger appetite for coaching, vendors have begun to think through what coaching actually entails and how some or all of those steps can be simplified.

Interestingly, as vendors have thought through what coaching entails, the definition of coaching has also morphed: it is no longer defined only as a 1-to-1 relationship where the coach utilizes tools and a methodology to help the coachee gain actionable insights that can help them perform better. It has expanded in ways that we didn’t imagine when we started this research.

To that end, it’s important to clarify that, in this report at least, we are making no judgments on what coaching actually means. Vendors sell what they believe the market needs; in our conversations with orgs, we also found varied definitions of coaching, as well as varied needs for coaching. So, when a vendor tells us they have coaching functionality, we take them at their word.¹

This report was written to help us, and hopefully you, get a clearer understanding of the vast range of coaching technologies. As such, it answers the following questions:

1. What are the major trends in coaching tech?
2. What does the landscape look like, and what sense can be made of it?
3. Who is playing in this space, and what are common and unique functionalities?
4. How can orgs choose? What criteria should they use to find something that will work for them?

Let’s get started.

Major trends in coaching tech

Indeed, things have changed when it comes to the coaching world. In the last section, we mentioned that the definition of coaching has morphed, and that it is no longer defined solely as a 1-to-1 relationship between 2 humans. Technology is playing a bigger role.

And, as in other industries where tech begins to play a role (e.g., transportation: taxis, Uber and Lyft, self-driving cars, teleporting), things accelerate quickly. In the case of coaching, several things helped with that acceleration, including the pandemic, a greater focus on the employee experience, fear of the Great Resignation, and the promise of the ability to scale something that used to be just for top leaders, so it’s available to more people in the org.

What, exactly has changed when it comes to coaching tech? Our data and briefings with vendors pointed to a few attributes.

More coaching tech

First, there’s just more coaching tech, both in terms of players in the space and revenue being earned. We mentioned that our own vendor database has grown to over 45 vendors saying they have coaching functionality. We are seeing that growth in stand-alone tools as well as in add-on functionality in learning and performance tools.

Additionally, when we asked vendors about their revenue growth in the past 3 years, the majority of them, or 63%, said that their revenue has grown steadily (see Figure 1).

A broader definition of coaching

More organizations are offering more coaching to more employees. Whereas coaching was once reserved for top leadership (or those with severe behavioral challenges), orgs now understand that there are benefits to coaching more broadly.

To accommodate the uptick in demand, coaching tech vendors are thinking about coaching differently. Our briefings and surveys surfaced several flavors of coaching, including:

• Coaching on demand: Employees leverage expertise of an external or internal coach to work on a specific challenge at a specific time
• Managers as coaches: Managers are trained and supported with platforms that can create accountability and discipline around coaching conversations
• Peers as coaches: Peers utilize tech to pair up and participate in guided coaching sessions designed to bring clarity to challenges they may be facing
• Reverse mentoring and coaching: Younger employees are matched with more experienced employees to share viewpoints and insights that can help them lead better
• Coaching circles: Tech helps employees with similar challenges to meet to talk through issues and receive feedback and advice from the group
• AI or machine-delivered coaching: Technology takes the place of a coach, helping employees become aware of certain behaviors and providing insights and data to help correct those behaviors

The coaching tech vendors we examined support a variety of these different coaching configurations. The tech they offer can help orgs to scale coaching, making it more cost-effective and helping leaders make a business case for increased coaching.

Coaching in more areas

Another trend we’re seeing in the coaching space is a broader range of topics offered by coaches and coaching tech. Whereas coaching used to only include performance or business coaching, new subjects are becoming more common. Figure XX illustrates the topics that coaching tech vendors are currently focusing on.

 

Not surprisingly, coaching follows some of the trends we’re seeing in the people space in general. Business and leadership coaching remain predominant, but wellbeing has crept in, as has Diversity, Equity, Inclusion, and Belonging (DEIB), both spurred by the pandemic and by the social justice movement.

Coaching on DEIB and wellbeing have both grown, spurred by the pandemic and by the social justice movement.

These new topics also speak to the fact that coaching is being provided as a benefit to individual employees. Health & fitness and financial in particular do not necessarily improve org performance; rather they are being offered to engage employees and help them eliminate stress and avoid burnout.

New things tech can do

Finally, there is more functionality. While earlier coaching tech focused on streamlining tasks associated with coaching (finding and paying coaches, facilitating conversations between coaches and coachees, and matching coaches to coachees), newer tech goes beyond those traditional functions to include aspects of AI, coaching without humans (machine delivery), integrations with work tech, nudges, and absorption of work tech data to make coaching algorithms better. We’ll talk a lot more about functionality in subsequent sections of this report.

AI, machine deliver, integrations with work tech, nudges, and more are changing the way orgs are offering “coaching” to their employees.

A model for thinking about coaching tech

Classifying coaching tech has been one of the most difficult HR tech projects we have ever taken on. Because coaching now has a much broader definition and because we are seeing a lot of new functionality, coming up with a picture that adequately describes what is going on has been a challenge.

That said, in looking at the tech and characterizing how orgs are making decisions about coaching tech, there appear to be 2 major factors driving decisions about coaching.

1. Resources: Are resources available internally to support a coaching effort?
2. Philosophy: Does the org believe that humans are necessary to deliver coaching?

There are many, many other questions that define what type of coaching tech orgs are looking for, which we’ll address in the final section of this report, but the above 2 factors seem to be the primary drivers. If orgs develop clarity about those 2 things, they can narrow down their coaching tech options significantly.

When we plot those 2 factors against each other, we get the 4-square shown in Figure 3 below, which gives us a helpful way of classifying coaching tech solutions.

 

This model divides the coaching tech landscape into 4 distinct quadrants:

1. Quadrant 1: Human coaches, external resources. Coaching tech vendors in this quadrant match external (usually professional) coaches with internal coachees and provide tools and a platform to support the coaching relationship.
2. Quadrant 2: Human coaches, internal resources. Coaching tech vendors in this quadrant match internal coaches with internal coachees and provide tools to support the coaching relationship.
3. Quadrant 3: Machine coaches, internal resources. Coaching tech vendors in this quadrant leverage org-supplied data (often from other work systems) or provide tools to help coachees self-guide to receive insights, nudges, and other aids, often without the involvement of a human coach.
4. Quadrant 4: Machine coaches, external resources. Vendors in this quadrant provide machine-delivered coaching based on their own frameworks or programs and offer up insights, nudges, and other aids as needed.

Obviously, not all vendors fit neatly within one quadrant. Most fall somewhere along each of the axes in the model. Figure3 places them roughly where we think they fall on both axes.

So, for example, CoachHub provides external coaches, and focuses exclusively on delivering coaching through humans. As a result, this vendor falls squarely into the upper right-hand quadrant of the model. Cultivate, on the other hand, uses internal data to drive its algorithms and includes no humans in its coaching, so the company is placed to the far left and bottom of the model.

The next sections are organized around each of these 4 quadrants. For each quadrant, we’ll share some of its characteristics and some of the common functionality. We’ll also share some of the more interesting functionality some of the coaching tech vendors provide. Finally, we’ll look at some of the best use cases for coaching tech in each quadrant.

A caveat: while we classified and identified many, many vendors, we’re sure that we missed some. The next sections highlight what some particular vendors are doing, but are written broadly enough to give you enough information to make good choices about solutions that are not included in our assessment.

Quadrant 1: Human coaches, external resources

The first quadrant (upper right) includes coaching tech that matches external (usually professional) coaches with internal employees and provides a platform for continued interaction between coach and coachee.

 

This, undoubtedly, is the most traditional way to think about coaching—and consequently the tech that supports it. When most people think about tech to help with coaching, they think in terms of external coaches being matched with internal employees. It’s the way coaching has been done for centuries. And it’s probably the simplest and most straightforward of the 4 quadrants.

Common functionality

Coaching tech orgs in this quadrant share a lot of the same functionality. Of course, there are differences, and those differences could make a big difference in how the tech may function in a given company. But understanding what is common to vendors can help you make better purchasing decisions. We discuss some of these points of commonality below.

Platform for communication

One of the main functionalities in almost all coaching tech solutions in this quadrant is provision of a platform—that is, a place for coaching to happen. Platforms offer a place for the coach and employee to meet and a way to document agenda, goals, and topics to be worked on.

Coach matching

The majority of coaching tech solutions in this quadrant also offer a way to match coaches and employees. Solutions falling in this quadrant generally believe that the coach/employee relationship is critical to success; thus, matching is an important functionality. In the solutions we looked at, matching primarily happens in 2 ways:

• Artificial Intelligence (AI). Many coaching tech solutions tout AI matching—utilizing algorithms to find the best coaches based on the employee’s needs and the coach’s expertise. Note: While we didn’t dive too deeply into the AI algorithms of individual coaching tech solutions, we do know that AI is a very buzzy word and apt to be used in many ways. Those looking for solutions should ask some pointed questions about the algorithms and how exactly they function.
• Matching Assessments. Many solution vendors take a more tried-and-true approach to assigning coaches by asking employees exactly what they’re looking for through short assessments, and then matching coaches to them accordingly. As with AI, we encourage additional questions about matching, as well as ability to personalize the questions on which employees and coaches will be mapped.

Competency assessments

One of the beauties of coaching tech is that it can standardize coaching practices across the organization. Many of the solution vendors in this quadrant accomplish that by way of assessments. Assessments run the gamut—from asking a few questions about what you want to focus on to asking for a complete 360° assessment by the coachee, to get a sense of what their development areas are. This information is available to the coach and the coachee so that they can work together to strengthen those areas.

From the org’s perspective, standard assessments and a common development model can unify coaching initiatives and provide a consistent vocabulary, particularly if coaching is being used to get a group of employees (leaders, say) to have similar behaviors. It also provides the possibility of analyzing rolled-up coaching data for all participants.

Coaching tech vendors in this space tended to utilize their own models and data to create these competency assessments.

Data

One of the big promises of coaching tech, which is not unique to this quadrant, is the availability of valuable data that can be used to evaluate the success of the coaching and the progress of the coachee. Until coaching tech was born, most orgs were reliant on self-assessments, satisfaction surveys, or their faith that the coach was doing a bang-up job. Now, almost all coaching vendors offer some sort of metrics for this purpose (although they can be sparse in some areas).

At the very least, orgs are now able to understand coachees’ level of engagement with the coaching initiative and a general sense of how coaches are performing. For many orgs, this is enough, both because it’s likely more than they have had in the past, and because of their concerns about privacy and confidentiality in the coach / coachee relationship. Orgs choosing this kind of tech tend to be less worried about the granularity of the data than in some of the other quadrants we explored.

That said, with some coaching tech solutions, particularly those utilizing standardized models across all orgs, data about topics being worked on could be rolled up to the manager, department, and org levels to give orgs more information about the types of things that were being coached.

Coaching quality

Many of the vendors in this space are also concerned about the quality of their coaches, and have therefore put interventions in place. This usually takes the form of a consistent coach onboarding process, vetting (many mentioned ICF-certified coaches), ongoing training, and quality checks. Because coaching tech keeps tabs on satisfaction data with respect to coaches, it is easier to intervene earlier when things are not going well.

Common coaching tech functionality for Quadrant 1 includes platforms for communication, coach matching, competency assessments, data, and ensured coaching quality.

Things we saw and liked

We found it interesting that coaching tech solutions in this quadrant understand the market and some of the threats to more traditional coaching. Coaching tech solutions that leverage external coaches understand that it is an expensive solution that most orgs are going to reserve for high-potential employees (HiPos) and present and future leaders.

Even so, one of the strengths of coaching tech is its ability to offer coaching to more people in the org. Within this particular quadrant, coaching tech solutions are facing constraints to their ability to attract and retain well-qualified, external coaches; in response, many are creating functionality that helps orgs to scale or show value beyond simplifying the administrative aspects of running a coaching initiative. Some of the features we liked are outlined below.

Alignment with existing leadership initiatives

Pluma (recently acquired by Skillsoft), among others, offers the flexibility to upload an org’s leadership model and customized 360, and provide coaching to leaders with respect to that model. This could be particularly useful in situations where orgs have well-established leadership development programs and frameworks, and want to ensure that any coaching initiative is aligned with them.

Human coaching for specific topics

Many of the coaching tech vendors in this space appear to have recognized new needs in the marketplace and created particular “programs” to address those needs. In an earlier section, we identified several coaching subjects. While the majority of orgs still seek coaching to help with the classic topics of leadership and business growth, many are interested in several new coaching areas.

These new areas, including wellbeing and DEIB, can be slightly more programmatic than the more traditional areas, and can therefore be more easily standardized. This has allowed coaching tech solutions to provide consistent coaching topics and additional resources to help orgs struggling with how to address some of these topics.

For example, CoachHub saw a need for leaders with better Diversity, Equity, Inclusion, and Belonging (DEIB) skills; it created a framework that can be used to build those skills throughout the org.

Another example is Betterup’s recent foray into wellness and mental health (in fact, if you check out their website, coaching is now de-emphasized as they move into these new topics). Their coaches now include therapists and peak performance experts, with the goal of ensuring that employees receive the individual care they need to be at their best.

Just-in-time or drop-in coaching

Torch.io has worked with clients to create drop-in coaching—opportunities for employees beyond traditional HiPos and leaders to schedule time with professional coaches on an as-needed basis. This time can be used to role play an upcoming situation, discuss career moves, or talk through business challenges.

 

 

Early career coaching

One of the newer applications for coaching is serving those early in their careers. From an individual perspective, an external perspective can be valuable as younger employees consider their first big career decisions. From an org point of view, coaching is increasingly being used as an engagement tool.

One coaching tech solution focusing specifically on early career is The Lighthouse. Lighthouse is a small company that leverages grads from top MBA programs to provide one-off coaching sessions with early-career coachees.

Best used for

In our initial conversations with org leaders, we found that many are looking at several different technologies for different types of initiatives. Based on those conversations, our assessment of the best uses for technology in Quadrant 1, which uses human, external coaches, are:

Ensuring higher-quality coaches with credentials

Many of the tech vendors in this category tout the quality of their coaches; many refer to ICF (International Coaching Federation) certifications and/or years of service. These vendors place a very high value, not only on tech and scaling, but also on ensuring a quality experience.

A human touch

With the pandemic has come a push by many organizations to provide more, not fewer, points of human contact. Vendors within this quadrant also highly prize human interaction (some going so far as to claim that unless coaching involves humans, it’s not actually coaching). For orgs looking for more human touch, vendors in this quadrant may offer the best solution.

Offloading administrative tasks

Before this type of coaching tech existed, many orgs relied either on a binder full of bios of trusted coaches that they then assigned manually, or on programs run by outside consultancies or training firms. This type of coaching tech takes some of the administrative burden out of providing coaching by automating tasks such as matching coach to coachee, or ensuring continued interaction.

Quadrant 2: Human coaches, internal resources

Given that coaching is becoming an increasingly hot topic, it comes as no surprise that organizations are trying to provide the opportunity to as many people as possible. One of the obvious challenges is cost and scalability: offering coaching to everyone can put a fairly hefty dent in development budgets.

Coaching tech in Quadrant 2 addresses this issue by leveraging internal resources. In most cases, this takes the form of leveraging human coaches from among the employee population. Coaching tech solutions in this quadrant also tend to leverage internal or proprietary data, models, and content as well, rather than utilizing standard models provided by coaching tech.

In this quadrant, we also heard more about creating a “coaching culture” or teaching coaching skills more broadly, particularly to managers, rather than relying on traditional coaching relationships.

Interestingly, one of the challenges associated with creating a coaching tech landscape was the breadth of ways that vendors describe internal coaching. True, many stick to the traditional description of coaching: discussions between 2 individuals. However, we saw the most diversity in both offerings and users in this quadrant. This quadrant was also where most mentoring vendors make their appearance.²

Technology that falls within this quadrant is geared mainly toward either setting up an internal coaching program (without the use of external coaches), or creating a learning culture—usually by encouraging manager / employee development discussions. In our investigation of these vendors, we found they had 3 major flavors:

• Coaching platforms, many of the same that offered external coaching services, configured to utilize internal resources instead of external coaches
• Mentoring platforms that provide a way for continuous feedback and direction from mentors to be leveraged for coaching as well
• Dashboards in skills, mobility, and learning platforms that provide information to managers about how employees are performing so that they can better coach them

 

You may have noticed that our Coaching Tech Landscape shows several coaching tech solutions that hover between Quadrant 1 and Quadrant 2. These solutions have platforms that are configurable enough to be used to access either external coaches or internal coaches.

Common functionality

Defining common functionality in this quadrant is difficult because of the broad definitions of coaching used by the quadrant’s vendors. Aside from traditional coaching relationship (1-to-1 conversations where a formal coach asks exploratory and discovery questions of the coachee), we also observed several other types of coaching relationships, including peer coaching, manager coaching, coaching circles, drop-in coaching or just-in-time coaching, and reverse mentoring.

Several functionalities appear to be fairly standard across a number of the coaching tech solutions.

Matching internal coaches with internal coachees

For coaching tech solutions that focus on the 1-to-1 relationship between coaches and coachees, we saw the same sorts of functionality that we found in Quadrant 1. This is not surprising, since many of the players from Quadrant 1 can configure their solution to work for internal coaching pools, which can be helpful to orgs that want to move between external and internal coaches.

Coaching tech solutions in this quadrant generally match internal coaches and coachees in 2 ways: AI and matching assessments. We saw little difference in matching functionality as it was applied to either internal or external coaches; the only difference appears to be the coaching pool.

Platform for ongoing engagement

As in Quadrant 1, most vendors focusing on the 1-to-1 relationship between coaches and coachees also provide a platform for continued communication and discussion.

More integration, more nudges

Because of the internal focus and their broader definition of coaching, vendors playing in this quadrant are more likely to integrate with existing systems. Many identify integrations with work technologies (mainly Slack and Teams) to help coachees stay on track and check in regularly.

There are also vendors in this quadrant that provide more than just coaching tech (i.e., they’re a learning or performance tech that also does some coaching), and so more integrations to additional resources, assessments, learning platforms, and the like are also more common.

Access to additional resources

Many of the vendors in this quadrant provide access to additional resources or micro-learnings in order to enhance the coachee experience. This is not surprising, given that many of these are learning platforms with a coaching component; we do however, like the idea of extending the learning beyond the in-person engagement.

Several vendors also have onboard coaching resources as well, to provide training or help to amateur or manager coaches

Common functionality for many of the coaching tech vendors in Quadrant 2 includes matching internal coaches with internal coachees, platform for ongoing engagement, more integration, more nudges, and access to additional, usually internal, resources.

Things we saw and liked

Coaching built into other initiatives / Asynchronous coaching

Both Novoed and Intrepid offer coaching as a part of their cohort learning platforms. Both coaching tech solutions include video exercises with offline feedback, scheduling, and group coaching in their platforms.

Novoed provides a Coach’s Dashboard so that coaches can understand where each of the coachees in the cohort are and identify needs.

Figure 7: Novoed’s Coach dashboard | Source: Novoed, 2021

Depending on the program and need, Intrepid enables coaches to provide feedback throughout and are available to schedule 1-to-1 engagements with employees who want a little extra help or advice.

Figure 8: Intrepid's Rubric page | Source: Intrepid, 2021

Asynchronous coaching is used quite a bit in sales or other industries where the practice and delivery of certain skills is important. This technology allows employees to record themselves performing a task (a sales pitch, for example) and then receive video feedback based on a predetermined rubric.

Rehearsal offers an asynchronous coaching tool as its main functionality. It allows orgs to set exercises (sales is a big use case), then allow people to practice as many times as they would like with video, submit the video, and receive feedback from a coach who refers to a rubric. If orgs want, they can also allow other coachees to view, judge, and even upvote video practices.

Bongo (which, incidentally, doesn’t sell to end customers but is instead incorporated into other coaching tech solutions), also enables asynchronous coaching through video and rubrics.

Manager-as-coach dashboards

There are also a number of products that focus on providing information to managers so that they can better support their employees.

Degreed’s Skills Coach, for example, provides a manager dashboard that summarizes a team’s skills, as well as providing data on each individual, so that managers can plan the coaching for both the team as a whole and individuals.

 

Axonify and Qstream, both of which focus on front line workers, are considered learning tech but offer dashboards to give managers a sense of what employees are focusing on and where they may need individual coaching.

And Bridge, recently separated from parent company  Instructure, is considered both a learning and performance tool. It was also built with manager-as-coach in mind. It offers data visible to managers to help them provide better feedback and guidance about development and performance, and a platform for ongoing discussions. Bridge also offers a timeline of activity and a space for weekly check-ins to enable managers to act as coaches.

 

We are big fans of providing managers as much information as possible when they’re coaching employees. These dashboards provide employee development and skills data to managers, which can help them tailor feedback and guidance for further development or better performance.

Focus on DEIB

Many vendors spoke of the ability of orgs to use their tools to further DEIB efforts; many had stories about utilizing their platforms to further coaching and mentoring efforts among specific populations. Chronus was one vendor that stood out here—they pay specific attention to their matching algorithm to encourage more inclusive matching; they also provide a dashboard geared toward increasing diversity in mentoring relationships and are beginning to offer insights associated with industry DEIB benchmarks to help orgs make better decisions.

Peer coaching functionality

With the broader definition of coaching comes additional functionality. Imperative’s coaching tool, for example, provides a platform and guided discussions to help managers coach each other peer-to-peer. The platform and structure ensure that managers adhere to coaching principles (open-ended questions, for example) and that there is a place and prompts to continue conversations. Pairing managers together helps them reflect on how they perform and what they can do better.

Figure 11: Imperative’s manager peer-to-peer coaching tool | Source: Imperative, 2021

Best used for

Orgs utilizing coaching tech vendors in this quadrant generally have 1 of 3 goals for their engagement.

Scaling coaching to more people

Orgs that use the coaching tech solutions in this quadrant are interested in providing a human coaching experience to their employees, but want to leverage internal coaches in order to do that. The solutions in this space are enhancing the skills of existing resources and providing guardrails or guidance so there is more structure and consistency across the coaching experience.

Creating a coaching culture

This type of technology is also being used to help orgs build a coaching culture. In the wake of the pandemic, many orgs have realized (again) that their managers are not as strong as they could be. Many of these solutions have been implemented to give managers support and guidance around career coaching and difficult conversations.

Upskilling and supporting managers

The pandemic and related moves to hybrid and remote work settings have caused orgs to reevaluate the quality of interactions between employees and their managers. In many cases, managers are falling short. Fortunately, orgs are also recognizing that the shortfall isn’t due to lack of trying or desire, but rather a lack of skills and support. Many coaching tech solutions in this space are geared toward answering this need.

Quadrant 3: Machine coaches, internal resources

The bottom half of the coaching tech landscape focuses on solutions that mainly rely on technology or machines to deliver coaching. These tech solutions use information to drive prompts and help coachees think through how they’re doing and what they can do to improve.

The promise of AI or machine coaches is generally 3-fold:

• It offers a fairly inexpensive and unlimited way to scale coaching to more employees
• It solves one of the major challenges of coaching – consistent check in and feedback – that is difficult if relying only on the humans.
• It offers a means of standardizing data – currently one very big hole in the world of coaching tech

In this quadrant, we start to see a departure from what is considered traditional coaching. Not only do we see more automated coaching systems that don’t rely on the humans (or augment what the humans are doing), but we also see more integration and interaction with performance and learning tech.

In fact, as we look across our HR tech research over the past 5 years we’re seeing much more overlap between performance, learning, and engagement platforms. Many offer consistent follow up, spreading learning over time, identifying ways to personalize experiences, and nudges for regular conversations with managers. These functionalities do overlap with what coaching has come to mean, so they likely have a legitimate claim to the therm “coaching tech”.

This does mean, however, that leaders need to be extra vigilant and ask lots of questions about the nature of the “coaching” offered. We mention this in the section dedicated to Quadrant 3, but this is also an important point for Quadrant 4. Do your homework. Ask lots of follow up questions (see the final section of this paper). We’re in new territory here.

We also think the use of machines that feed off internal data and provide valuable insights to employees will continue to grow as data gets better and it becomes more acceptable to use coaching data as employee development data.

 

Coaching tech solutions in this quadrant rely heavily on internal data and resources. They often absorb information from other work tech to generate insights that are delivered directly to employees. They also often point to internal resources (via a learning platform, for example) that can augment feedback or insights.

Delivering this information directly to employees—sans manager or human coach—can sometimes take the sting out of feedback and provide data in a way that can be more easily absorbed by the individual.

As with Quadrant 2, we ran across several learning tech solutions that are also targeting coaching clients. As several of them do have coaching functionalities, we have included those that tell us they’re coaching tech, even if their main functionality is L&D tech.

Common functionality

Common functionality in this quadrant was a little harder to identify. From the survey filled out by coaching tech solutions, however, 3 common areas surfaced.

Digital or AI coach – nudges

Common to this group of technologies was that all of them have a digital component and do not require a human. Some vendors call this functionality a “coach on the shoulder” that provides information when it is most likely to be absorbed and used.

Most tech solutions provide this information through nudges—small insights or reminders to coachees, based on their desired behavior changes.

Integration with work tech

Most of the vendors in this group integrate in some way with work technology. This is used for both pushing and nudging, and to gather data on performance to help the tool get smarter, which makes for better insights. Common integrations are Slack, Teams, email clients (Google, Outlook, etc.).

Data and Information pushed down

Tech solutions in this quadrant tend to push information down to the individual rather than delivering it through a manager or coach. We saw a lot of dashboards and insights summaries as a part of these solutions, making the individual—the person most motivated and able to act—responsible and empowered to do so.

The majority of coaching vendors in this quadrant say their solution:

• Provides data and information to coachees to help them understand their own progress
• Rolls up data to manager, function, organization levels, etc. to help the org better understand challenges and areas of focus

Because it is integrated with existing work and HR tech, data associated with these types of coaching tools tends to be better and slightly more granular. We observed that these tools have a greater ability to roll up results and provide individuals with progress data than solutions in either Quadrant 1 or Quadrant 2.

Common functionality in Quadrant 3 includes digital or AI coaches and nudges, more integration with work tech, and data being pushed down and provided to employees (rather than their managers).

Things we saw and liked

As we mentioned earlier, the bottom half of the coaching landscape is pretty new. As AI, machine learning, data, and comfort with sharing data about coaching gets better, we expect a lot of growth. Some of the differentiators that showed up in this quadrant include the following.

Team coaching

In most learning tech we have seen in the past few years, nudging has been used mainly as a way to help employees follow up on learning initiatives. Within this quadrant, nudging is being used in a much more sophisticated manner.

Humu, for example, uses nudges to help teams improve. After understanding the goals of the team and how they’re working toward them, Humu utilizes a series of actionable nudges that promote continuous improvement. Nudges are personalized to the individual team member, but take into account the team and goals, so that teams can help each other execute.

Because nudges happen regularly, teams have opportunities to reflect and respond, allowing the tool to gather and integrate more data to better target nudges.

Digital coaching to optimize live coaching sessions

We also ran across tools that utilized machine delivery and AI to simplify the human coaching element. Sparkus, for example, has an onboarding and self-coaching component that requires those interested in having a coach to think through what they want to accomplish and what help they need in advance. This prework has a couple of benefits.

First, it helps orgs understand the level of commitment of coachees; since they are not assigned a coach until they finish the self-coaching component, orgs can quickly understand who is serious about the experience and who isn’t. Second, it helps to minimize the amount of live coaching needed. One challenge many orgs have is understanding when a coaching engagement is finished.

The self-coaching component helps the coachee and the org to bookend the human coaching engagement, optimizing the number of sessions with a live coach. This helps organizations scale because they are able to offer a finite number of coaching sessions to more individuals.

 

AR/VR

While there aren’t many, we also ran across a couple of vendors that leverage augmented / virtual reality to help with coaching. Mursion, likely the most well-known tool in this space, provides an immersive coaching experience. Coachees complete a simulation where they need to handle a difficult conversation (our demo experience was about creating a safe place for employees with very different opinions to discuss whether a woman should be promoted).

 

Mursion utilizes a combination of technology and real players (actors) on the back end to give an accurate simulation. While the experience from the user side is slightly animated, coachees have the opportunity to read body language, respond to tone, and evaluate all players in the scenario. It also provides a deeper experience than coachees can get with a static, linear role play, and accounts for some of the current shortfalls associated with tech simulations and AI.

Coaches on the shoulder

Cultivate is a great example of a tool that absorbs data from other systems—in this case, email—and provides feedback to managers about how they are communicating with their team members. It uses a combination of data and insights to make managers aware of behaviors and suggest ways to change them. For example, a manager may get a prompt telling her that she is sending less than 5% of emails to her team after work hours—which is good—but that prompt may also identify the individuals to whom she is sending after-hours emails.

Cultivate also offers ideas that can be tried immediately; in this case, onboard learning snippets can give the manager information on improving communication habits, adjusting priorities, or simply delaying sending messages until business hours.

 

Because the tool is integrated with a particular manager’s communication tech, the insights as well as the feedback are personalized. Because the coaching is integrated into the flow of work, managers are more likely to be able to use that feedback immediately.

Emplay is another coach-on-the-shoulder type tool. While its current strength is in sales, it is also branching into manager training. Emplay has the philosophy that successful coaching is a combination of sharing the right information and instilling discipline.

 

Emplay provides coaching in 4 areas: First, it can surface experts within the organization based on the experts’ assignment and data recommendations. It can also use conversational tech to ask questions that prompt coachees to reflect and find answers to their own questions. Third, Emplay surfaces behavior patterns in salespeople that can provide insights that can help them close deals faster; finally, Emplay can absorb long-form content and then utilize it to respond to queries via Teams and Slack. Emplay also creates dashboards and provides access to both manager and coachee for more insightful discussions.

Best used for

Because the tech falling in this quadrant is not traditional, utilizing this type of tech requires a non-traditional mindset. While coaching of this type will likely never fully replace human-delivered coaching, it does provide some unique opportunities that have yet to be solved by human coaches. We see 3 major use cases.

In-the-moment awareness for creating new behaviors

One of the promises of machine-delivered coaching tech is the ability to insert coaching opportunities into the work itself. Many of the tools in this quadrant operate on of the assumption that making people aware of their behaviors is the first step in helping them to modify their own behaviors.

Support of other initiatives

Because of its ability to provide in-the-moment data and insights, this type of technology may be very well suited to reinforce other types of learning, performance, or change initiatives. For example, once information about behavior has been shared explicitly (manager shortcomings, for example), a tool from this quadrant may be very helpful in drawing attention to unconscious behaviors in the work flow.

This type of coaching tech may also be helpful in providing common language and expectations for initiatives such as DEIB and extending the useful life of initiatives; regular reminders or opportunities to practice can reinforce principles learned earlier and build skills for using that new knowledge in the context of work.

Scalability

Finally, as with every other quadrant, one of the primary purposes of these tools is to scale. Machine-delivered coaching, while not as personal as human-delivered coaching, is infinitely scalable and fairly inexpensive. Organizations looking to provide something may be able to start here.

That said, machine-based coaching, particularly in this quadrant, does not provide the human touch and may not elicit the positive reactions or engagement of employees whose org invests in a real live coach.

Quadrant 4: Machine coaches, external resources

As with the vendors in Quadrant 3, those in Quadrant 4 rely heavily on machines for delivery of coaching. However, they also utilize external resources—meaning coaching insights are based on external data, models, usually proprietary, and additional content that can be used by coachees for extra growth.

 

Orgs taking advantage of coaching tech solutions in this quadrant are generally looking for a solution that scales very easily and has some programmatic aspect. As this type of coaching tech generally uses proprietary models and resources, it can be seen as more of a turnkey solution than coaching tech in some of the other quadrants.

Common functionalities

The common functionalities in this quadrant are not surprising: machine delivery, and the provision and consumption of data for the purposes of creating insights. We detail some of them below.

Digital or AI coach

Most of the technologies in this section pride themselves on providing insights to coachees with little or no involvement of a human. Digital or AI coaches work with existing data in organizations to provide those insights in ways and at times that can be most impactful to coachees. They may come via Slack, Teams, email, or other systems that are already used for work.

This quadrant distinguishes itself from the other quadrants by the fact that almost all of the tech in this quadrant uses humans to augment the tech, not the other way around.

Roll up data

As we mentioned above, one of the benefits of utilizing the same models and having access to more automated data is that it is easier to roll data up. A characteristic of many of these vendors was the ability to roll up data to the manager, function, and organization level, to help the org better understand the challenges and areas of focus.

Integration with HR systems

Vendors in this quadrant also integrate more readily with the HR systems that are already being used in an org. Because they are often using standardized models and data to drive insights, it may be easier for these coaching tech vendors to also standardize their integrations. In some cases, they may also be key to the functioning of their solution. We think this may be in its infancy as well – and there are privacy and ethics concerns that must be addressed – but linking coaching in with other HR systems, such as performance management, can help orgs tie coaching to broader goals.

Things we saw and liked

As with the other quadrants, there were several ideas or functionality provided by vendors that we found interesting.

Focus on wellbeing

meQuillibrium was one of the few vendors we spoke to whose solution provides coaching on well-being. meQuillibrium’s tool starts with an assessment based on their internal research. From there, coachees receive a personalized resilience program based on their assessment of how they deal with stress.

meQuillibrium provides data, feedback, nudges, activities, and content to help coachees understand what they need and then take care of themselves.

 

Listening – AI speech coaching

Orai is one example of a AI speech coach that listens to the coachee as they speak and then provides feedback on pace, tone, and filler words. It has prompts for the coachee to practice extemporaneous speaking, a prepared speech, or a presentation. While it’s not perfect, we had fun trying this out. We found that it gave some great feedback on filler words and speed (2 of our biggest challenges).

Orai is a good example of where we see this quadrant going: humans were nowhere in sight; the tech leveraged natural language processing (NLP) and AI to provide actionable feedback and insights, and there were daily prompts over a period of time for continued improvement.

 

Programmatic coaching augmented by group coaching

Pilot is a perfect example of a tech that utilizes humans to augment the machine coaching. Pilot focuses on managers and has utilized research and years of experience to identify the biggest challenges to managers. Its program walks managers through information, nudges, and activities to help them practice using new knowledge and skills online. It then augments this learning with planned group coaching events, where all coachees in a cohort join a call to receive extra instruction and get their questions answered.

Best used for

Coaching tech in this quadrant is probably the most experimental; several of the tools acted more like guided learning for the time being, but we see a lot of potential in this space. As AI and natural language processing (NLP) get better, we see the current coaching tech—and the possibilities for new coaching tech—getting better.

Orgs experimenting with some of these tools likely do so for 1 of 3 reasons.

Scalability

Because few, if any, humans are involved, tools in this space are usually infinitely scalable. It generally costs just a few dollars to add another user to this type of tool, compared to the hundreds or thousands of dollars it would take to add a user to a tech that uses human coaches.

Orgs looking for something that will meet immediate needs, or even act as a stopgap, may have success using some of the tools we’ve discussed.

Standardization

Orgs looking for standard off-the-shelf models for leadership, wellness, or other subject-matter coaching may find what they need in coaching tech within this quadrant.

Additionally, because vendors in this quadrant leverage the same model and the same resources across all users, data can be standardized and leveraged. With standardized data, these vendors will likely have an easier time improving the tool, its nudges, and its AI than those vendors that rely on human input.

Experimentation

Coaching tech in this quadrant is generally low risk. Because of that low risk, orgs that want to experiment with coaching, or more particularly machine coaching, might want to start here. Since the majority of tech here use their own models and there is not much on- or off-boarding cost, orgs may want to give a few technologies a try as they firm up their philosophy on coaching in general.

Choosing the right coaching tech for your organization

As with all of our tech reports, we try very hard not to make decisions for orgs or guide orgs toward particular solutions. We don’t give top 10 lists or indicate that one tech is better than another because, in all honesty, it entirely depends. Context matters. Culture matters. Goals of the initiative matter. What works for one org may not work at all for another. You can’t cheat off your neighbor.

In this final section, we provide some help to those looking for the right coaching tech for their orgs. We are hopeful that the 4-square model introduced earlier can help narrow down the choices at a high level. However, as we explored the tech, we found ourselves asking deeper questions to completely understand the solution, what it could offer orgs, and in what context it would be most appropriate. Even with the 4-square chart, orgs will need to be thoughtful about their own unique needs and their choice of a vendor to meet them.

The following sections outline 3 fairly general steps to take when looking for coaching tech.

1.     Define your purpose

The very first step in deciding which tech is going to work best for your org is to consider the goals of the coaching initiative. Different goals may require different tech.

For example, consider the following vignettes:

1. You are trying to simplify the process of finding and assigning coaches. Right now, your org has to continuously vet coaches and then add them to a binder (yes, one of those things that holds papers), and then contract with each one separately. Coaching tech will help you to simplify the system you already have in place and ensure a level of quality you don’t have right now.
2. Coaching in your org is seen as a coveted developmental experience. Since COVID, there have been fewer opportunities to provide rich, “special” employee development to HiPos and future leaders. You’re looking for a coaching tech that can help you scale. Your goal is to ensure that coaching is still seen as a premier experience, but with a lower cost point and wider availability.
3. Your org has recently been acquired and you find yourself working with the org development team from the acquiring company to build common ground and standardize management practices. You need to offer some sort of education / change management support / coaching to all employees who are manager level and above. You want to provide a low-cost, yet somewhat personalized experience that can provide insights to those managers and help them develop a shared vocabulary and understanding of management practice.
4. You’re trying to create a coaching culture. Rather than looking at coaching as something that only certain individuals get, you want to create a culture where peers can coach peers and managers can coach employees. You know that consistency and discipline are the keys to making this happen, so you’re looking for a tech that can help provide the necessary structure.

Tech appropriate for one of these scenarios may very likely not be appropriate for one of the others. The goal matters. Coaching tech, just like any other learning tech, has to fit the situation and the ultimate desired outcome.

It’s important for leaders to understand the purpose for their coaching initiative – it can greatly affect the type of coaching tech solution they should choose.

Orgs may also find themselves in situations where they have more than one purpose at any given time. Unfortunately, we found no single coaching tech that can meet all of the different coaching needs an org may have. Orgs may need to choose 2 or 3 to serve the needs of different coaching initiatives.

2.     Choose a quadrant

We hope that the major themes with coaching tech that we’ve described so far will help you narrow down the search for your particular initiative. To determine which quadrant you may want to consider exploring further, ask yourself a few questions:

• Human vs. machine?
• Internal vs. external resources?
• Scalability?
• Control?

Figure 20 provides the bones of the Coaching Tech Landscape. The double-ended arrows represent the 4 questions posed above and can guide you toward the quadrant you should be considering, depending on where you fall on each line, and we provide more detail about each question below.

Human vs. machine?

Do you understand your org’s tolerance (or acceptance) of tech? In some organizations, coaching is seen as ONLY a human activity, while in others, scaling with tech is viable and jives well with the culture. Understanding where your org lies on that spectrum can help to determine which quadrant you should be looking at. Vendors in the upper part of the Coaching Tech Landscape model rely more on human coaches, while those in lower part rely on machine-delivery coaches.

Internal vs. external resources?

Do you have the resources to launch the coaching initiative internally, or will you need external resources? When you consider resources, think not only about humans, but about models, data or benchmarks, and content as well. Vendors on the left-hand side of the Coaching Tech Landscape tend to use internal resources, while those on the right rely on external ones.

Scalability?

How broad is the reach of the coaching initiative? Will it affect only a small cohort of employees, or is your goal to make coaching widely available? Machine-delivery coaching tools are much more scalable than human coaches.

Control?

Does your coaching initiative require that all coachees are coached using the same model or adhere to the same leadership traits? Do you want to determine what data and content is used, or are you looking for a vendor that will provide data and benchmarks, coaches, and models? Vendors on the left-hand side of the Coaching Tech Landscape tend to offer more control to the org.

3.     Vet, vet, vet

News flash: Vendors can’t or don’t always do what they say they can do. Many of the orgs we have talked to about their use of coaching tech have been disenchanted by the difference between what they thought (or were told) the tech could do and how it actually worked in the context of their orgs.

While there is absolutely no guarantee ever, and while there is much to do inside the organization as well to make sure the tech integrates well with other systems and processes, we’re very big proponents of vetting vendors to get the one(s) that make success the easiest. We spend a good one-third of our professional lives talking to vendors, and almost all of them will tell you that we ask an obnoxious number of questions. So should you.

The best advice we have for you? Ask lots and lots and lots of questions.

The following table identifies several questions that you may want to ask coaching tech vendors. While the list is clearly not exhaustive, we provide a set of questions that apply to any vendor, and then include several questions more specific to each quadrant. This list is by no means exhaustive. Understanding your goals for coaching tech will help you to identify others.

In addition to quadrant-specific questions, those looking for coaching tech should also be concerned about the health of the companies they’re vetting. As a part of our Learning Tech Ecosystem research, leaders identified 5 things they look at when determining viability of vendors.

1. Similar challenges. Vendors can refer potential customers to clients who have solved similar challenges using the vendor’s technology.
2. Confidence of investors. While not always completely accurate, several leaders told us that they used the market to help them vet vendors. Understanding where startups were in the funding process gave them hints about the long-term viability of those vendors.
3. Robust & innovative roadmap. Vendors should be able to speak confidently to their roadmap, and learning leaders should ask for it. Understanding the roadmap helps learning leaders to understand if the technology is moving in parallel with their organizational needs and enables them to assess the vendor’s innovation and ability to respond to the market.
4. Longevity in the market. Leaders we spoke to were wary of very young vendors, worrying about their long-term viability. That said, some of the more forward-thinking leaders were also wary of vendors who have been in the market too long—worrying about their ability to react and be innovative.
5. Evidence of partnering. Many leaders also mentioned using vendors as an extension of their team and a way to push forward and adopt new ideas. They look for evidence of partnering and problem-solving, not just providing software or content. As organizations continue to adopt an ecosystem point of view, it is getting more important to not just vet the tech, but also vet the vendors. Learning leaders should look for those who go beyond just providing services and can proactively help to solve problems.³

Wrapping it up

Exploring coaching tech and identifying a model to help leaders make sense of the space has been a pretty wild ride. We started out with some assumptions, all of which were blown to hell by the 3rd briefing. That said, however, we’re excited about this space.

Why? As with other areas on HR tech, the coaching tech space seems to be reinventing itself – which is remarkable given that the coaching tech space isn’t very old to begin with. We like that many of these vendors are experimenting – not just with what tech can automate from old models, but what new tech can do that has never been done before. They are, in essence, rethinking the very idea of what coaching is and how it can affect the largest numbe of people in the org.

In fact, as we have interviewed leaders for our sister report on coaching initiatives, we can safely say that coaching is one area where the tech vendors are ahead of orgs in how they’re thinking and innovating. We imagine that coaching tech vendors will continue to push orgs to think differently about coaching and we’re looking forward to seeing how that plays out.

Download Research

It really comes as no surprise that LinkedIn Learning is jumping on the LXP bandwagon. As organizations have begun the trek from “you’ll learn what I darn-well tell you to learn” to “Look! It’s Netflix for learning!” to, finally, “Let’s help you build skills – it’s good for you and it’s good for the company”, it makes logical sense that LinkedIn would eventually go here. Read their announcement.

Here’s what we know:

It’s free (for some, and for now).

LinkedIn Learning is offering LinkedIn Learning Hub for free to existing LinkedIn Learning Pro product customers for 1 year. We’re assuming this is a way to quickly build market share and allow those orgs that are thinking about dipping their toes in the LXP market to experiment.

This is particularly savvy as organizations are thinking more broadly about learning – no matter how good LinkedIn Learning content is, it’s likely not enough on its own for any organization. LinkedIn Learning Hub gives LinkedIn Learning the chance to offer more value to existing customers by creating a new product in a hot category.

This move may cost LinkedIn a bit of money upfront in customer service and integration unless they have an incredibly easy interface to connect both content, data, and employee information and expect it to be turnkey. But it also provides them with further opportunities to connect with and build relationships with existing customers.

What we’d like to know:

• What will be the cost after the first year?
• What services will LinkedIn Learning add to accommodate their new LXP customers? Even the simplest LXP is significantly more complicated than a content portal.
• Will they leverage customers using the product to further develop the product to better compete with existing platforms?

It’s for learning.

LinkedIn is offering LinkedIn Learning Hub as an addition in LinkedIn Learning. That fact, and the name, “Learning Hub”, lead us to believe that LinkedIn is thinking about this product as firmly planted in the learning space. As such, it can easily find a line item on the L&D budget and also has the opportunity to be a fairly big disrupter to the LXP market.

While this is seems like a logical move, it could also be shortsighted given that other big LXP players (like Degreed or Edcast) are endeavoring to increase their footprint outside of L&D as they realize that “skills” isn’t just a learning problem; it’s a strategic problem that affects almost every people aspect of an organization.

Other players are increasingly emphasizing that learning happens everywhere, and not just as a result of consuming content, to build skills. Other ways of developing skills, most notably through experiences, are being developed and tested. (Incidentally, if you’re interested in the skills discussion, check out our podcast, Workplace Stories: The Skills Obsession.)

What we’d like to know:

• How does the product accommodate (and connect with) other technologies that are increasingly involved in developing/tracking/reporting skills and experiences?

It touts its data.

Not surprisingly, LinkedIn Learning Hub is touting data and insights from their Skills Graph, “the world’s most comprehensive skills taxonomy, with 36K+ skills, 24M+ job postings, and the largest professional network of 740M+ members.” LinkedIn has got some fantastic data – one of the very big advantages it has over others playing in this space.

However, how LinkedIn indicates it’ll used use that data is underwhelming. According to their introductory post by their Sr. Director of Product, James Raybould, all that lovely data will be used to “empower customers with richer skills data insights, personalized content, and community-based learning.”

These things are important – but at this point, we don’t see the ability to provide incrementally better recommendations for content as a game changer in the LXP space.

What we’d like to know:

• What do the richer skills data insights look like, and what can LinkedIn Learning Hub do with those insights beyond these basics in the near future?
• How will those insights be leveraged for some of LinkedIn’s other offerings? (e.g., we see how skills information could be really valuable to LinkedIn proper and their support of recruiting).

So far its data appears to be for the adults.

Data and insights about skills are touted as available to L&D functions through the admin portal so they can “identify skills gaps, pin key skills and track trends over time, benchmark themselves against similar companies, get insights on skills interest and learning activity, and track skill trends across content sources.”

One of the really powerful advantages we think LinkedIn has is their history of providing data to the employees themselves – those most empowered and most motivated to do something with it. We’d love to understand what kind of skills data LinkedIn Learning Hub will provide individual employees and how it can enable employees in their careers. With the strong focus many organizations have on employee experience these days, this seems like a no brainer and a pretty big selling point.

What we’d like to know:

• What information will be pushed down to individuals?
• How is this tool designed to help guide employees to new opportunities for growth and career?

It (like everyone else) has a skills taxonomy.

One of the biggest arguments about skills is what to call them and how they relate to each other. Many organizations lack a common language about skills, and one of the biggest frustrations is the lack of consistently between departments, businesses, and even technology. We don't know how to talk about skills. To solve this problem, many organizations either create skills taxonomies or adopt ones and tailor them to their needs so – at least internally – everyone is using the same language.

The LinkedIn Learning Hub's skills taxonomy may help some organizations create the consistency they crave. It also provides a way to more accurately benchmark against industry and/or regional norms for skills and skills development. Many providers of skills frameworks are moving towards ontologies (structures that show concepts and their relationships relationships and adapt to new information) rather than taxonomies (structured, formalized, hierarchical organizations). Although we haven't seen it, we're assuming LinkedIn may lean more toward ontology than pure taxonomy – important to their ability to do more cool stuff later.

What we’d like to know:

• How does the taxonomy stay current and valid given rapid changes most orgs are facing,
• How can it align with taxonomies that have already been adopted by organizations?

It appears to duplicate some of Viva’s offerings.

Less than 3 months ago, Microsoft, LinkedIn Learning’s parent company unveiled its new Employee Experience Platform, Viva. This tool “brings employee engagement, learning, wellbeing, and knowledge discovery directly into the flow of people’s work.” See our take on Viva here.

As a part of that offering, there is a native player for LinkedIn Learning content. Other things it does?

• Identify content that may work for individuals.
• Provide insights to individuals, managers, and leaders
• Connect information and experts across the organization

Clearly, there is overlap. It is unclear how these 2 systems play with each other, if at all. Given the overlap, it appears that there could be some cannibalization. Further, Viva will integrate with other LXPs – rendering LinkedIn Learning Hub even more redundant.

What we’d like to know:

• How does LinkedIn Learning Hub interface with Microsoft’s Viva?
• If orgs have implemented one, is the other necessary?
• Are there plans to create a massive experience platform that uses all data that Microsoft and LinkedIn have? Cuz that would be cool.

To sum up:

LinkedIn Learning Hub is an interesting move by LinkedIn Learning – one that allows it to increase its offering to existing content customers – likely necessary because while content has value, it is increasingly becoming only a small piece of the overall L&D picture. It’s also not a move completely without precedent. Skillsoft purchased SumTotal for the same reason years ago.

Offering it to existing Pro customers for free may increase market share quickly, allowing those experimenting with LXPs for the first time to see if it’s for them, and get them used to a product that will likely increase in functionality and polish in future. It may be a very good move for small and midsize organizations or larger organizations with constrained L&D budgets.

Two final observations: 1) LinkedIn Learning Hub is pretty basic. Nothing about this LXP is extraordinary – yet. That could change. 2) While Viva made one heck of a bang when it hit the market, LinkedIn Learning Hub entered with more of a whisper. Some of our friends at other LXP providers say there isn't yet much disruption to deals in their pipelines. LinkedIn Learning Hub may not yet have the heft of existing options.

We’re very interested in your opinion – what are your thoughts?

 

We read a lot at RedThread—both to directly inform our research and because we’re reading junkies. We also listen to a lot of podcasts. (In fact, in this piece, we use “reading” as shorthand for “consuming content,” regardless of whether we’re consuming a podcast, book, audiobook, or article.)

Part of our mission at RedThread is to accelerate the flow of ideas through the marketplace—and one way we do that is by sharing what we’re doing / thinking as soon as we’re doing it. In that spirit, we want to share what our team members are reading these days.

We’ve divided the list into 4 sections:

• Reading that directly informs our research
• Reading that keeps us up to date in the field
• Reading that broadens our horizons
• Reading that we plan to do

Throughout this post, all titles and images are hyperlinked to the source. Let’s dive in!

Reading That (Directly) Informs Our Research

These books, articles, and podcasts help drive our thinking on the specific topics we’re writing about currently—topics like purpose; diversity, equity, inclusion, and belonging (DEIB); people analytics; learning; and skills. Here are our top things to read in this category.

The Enlightened Capitalists

In this book, author James O’Toole gives a fantastic historical perspective on how businesses have approached purpose. We’ve been doing a lot of research on the topic of purpose—individual, team, and organizational—and found this book remarkably enlightening (pun intended). It helped us understand how our collective concept of purpose has changed over time and why purpose is such an important component of a business’s success, now more than ever before.

 

Reimagining Capitalism in a World on Fire

Also supporting our purpose research, this book’s author Rebecca Henderson describes how capitalism is on the verge of destroying the planet and destabilizing society. Capitalism is destabilizing the climate, driving human deaths and mass species extinctions. Wealth is increasingly unevenly distributed and many institutions that have historically provided stability—families, faith traditions, governments—are “crumbling or even vilified.”¹ What can org leaders can do to change the path we’re on? A lot—and this book offers a practical roadmap for how businesses can build a kind of capitalism that works for everyone.

 

Caste: The Origins of Our Discontents

A number of people recommended this book to us, including Deborah Quazzo, Managing Partner at GSV Ventures and one of the guests on our “Is Purpose Working?” podcast season. Isabel Wilkerson writes about the existence of a invisible caste system in America and how that system influences us all. She shows how a rigid hierarchy is embedded in our society and institutions, feeding racist policies and beliefs in ways we often do not see. The book supports the research we’re doing on DEIB.

 

How to Be an Antiracist

This powerful book reshapes the reader’s notions of what it means to be racist. Starting from the idea that there are very few people in the world who think, “Yes! I’m racist!”, author Ibram X. Kendi helps readers understand that racism is fundamentally a problem of systems, policies, and institutions that foster inequity and invite individuals to (sometimes unconsciously) hold beliefs and commit actions that also foster inequity. The book paints a compelling picture of how we can all be antiracist by actively and continuously pushing ourselves, our communities, and our institutions to promote equity. This book supports our research on DEIB.

 

Reading That Keeps Us Up to Date in the Field

We love these sources—none of which, you’ll notice, are books—because they reflect some of the most leading-edge thinking on the topics we care about. If you like RedThread’s research, then you’ll probably find these resources helpful, too.

Articles by Matthew Daniel

Matthew is a longtime learning leader who writes about skills, talent, and learning. One of our favorite quotes:

Ultimately, we in L&D may be robbing our organizations of some of the greatest potential in talent, because they sit in the frontline and they're non-exempt employees—and so they just don't get access to content, or the systems, or the programs, or the mentoring, or the class.²

Matthew is a very forward-leaning thinker in the talent and learning space. He’s a regular contributor to CLO Magazine and posts valuable content regularly to LinkedIn.

Learning Tech Talks

This podcast, hosted by Christopher Lind, gives one of the most comprehensive (and entertaining!) perspectives around on learning tech—vendors, challenges, opportunities, ecosystems, and more. Each episode features a learning tech vendor talking about the problems they’re trying to solve. We like it because it’s not salesy, it’s always informative, and Christopher has an amazing ability to synthesize what’s going on in the space.

 

David Green’s Monthly Roundup of People Analytics Articles

Every month, David Green posts on LinkedIn a summary of the top articles published that month on people analytics and related topics. Each post contains a dozen or more articles, each summarized in at least a paragraph, often with helpful charts and graphics. This single monthly post is a great way for us to keep up to date on what other people are saying in the field.

 

HRTech Weekly Podcast

Stacey Harris and John Sumser at the HR Examiner host a weekly podcast, “HRTech Weekly One Step Closer.” They cover topics ranging from HR tech trends to analysis of tech vendors, recent mergers and acquisitions, and the implications of senior leaders’ movements between orgs. This weekly show is another fantastic way we stay current on others’ thoughts in the field.

 

McKinsey & Company Research on the Future of Work

McKinsey has been publishing a lot on skills, reskilling, upskilling, and the future of work. The company’s findings are well-researched and highly informative. These articles help keep us current on others’ work on the topics of skills and learning—for example:

Learning itself is a skill. Unlocking the mindsets and skills to develop it can boost personal and professional lives and deliver a competitive edge.³

McKinsey Quarterly, August 2020

Reading That Broadens Our Horizons

Curiosity may have killed the cat…but it sure makes us better researchers! We read a lot of stuff that’s not directly related to our research projects or even our areas of focus. These books, podcasts, and Facebook groups (yep) help us stay on our intellectual toes and keep us growing, learning, and thinking.

More: A History of the World Economy from the Iron Age to the Information Age

Author Philip Coggan writes the weekly Bartleby column for The Economist. Here, he’s provided a sweeping history of trade, industry, and growth in the global economy from ancient Rome to the 21^st century. We enjoy his style of putting complex information about management and the world of work in an easy to comprehend and interesting format that’s very appealing.

 

 

Prediction Machines

We’ve been talking about how AI will disrupt our lives and work for some time now—but how, exactly, will that happen? Authors Ajay Agarwal, Joshua Gans, and Avi Goldfarb explore the economic implications of the price of AI, which is declining in a way that’s similar to how the price of computing declined in the 1980s and 1990s. The book was recommended to us to truly understand AI disruption.

 

 

Profiles in Courage

In 1954, then-Senator John F. Kennedy decided to write a book profiling 8 of his predecessors: Senators from history including John Quincy Adams and Daniel Webster. The book won a Pulitzer Prize in 1957 and became a classic on courage in the face of difficulty and pressure. It’s an exceptional view into leadership in different times—with real implications for today.

 

 

The Rise: Creativity, the Gift of Failure, and the Search for Mastery

This book is an amazing exploration of failure—what it is, what it isn’t, and how failures are part of the journey to successes. Author Dr. Sarah Lewis, an associate professor at Harvard, has a background in art and culture—and uses these lenses in her lyrical, insightful, and practical exploration of the true nature of failure. (Hint: It’s not what we tend to think.)

 

Raising Kids with a Growth Mindset

This resource isn’t a single article or book—it’s a private (though very large) Facebook group of parents learning to live and parent with a growth mindset. Although most of the discussions focus on how to help children, the lessons and insights that group members share are often equally—if not more so—relevant to adults. We’ve found it to be some of the most helpful self-awareness and growth content available anywhere.

Reading That We Plan to Do

You probably won’t be surprised that we have long lists of things we want to read, but haven’t yet. Here are the top few.

The Making of Asian America

Given current events, we think it’s tremendously important to better understand the history of Asian-Americans in our country. Asian immigrants and their descendants have played a major role in U.S. history, but much of this influence has been overlooked or forgotten. This book by Erika Lee, a professor, author, and historian at the University of Minnesota, was recommended to us as a comprehensive, engaging, and fascinating way to learn something we should already know: how Asian-Americans have shaped the history of the United States.

 

The Remote Work Revolution: Succeeding from Anywhere

Looking ahead to post-pandemic life, we’ve recognized that work—like life—will never look the same. In this new environment, employees want to know how to stay connected while maintaining work-life balance; managers want to know how to lead remote teams; and orgs want to know how to enable great work to be done. We’ve heard that this book by Tsedal Neely answers many of these questions. It’s a practical guide for leaders, managers, and teams as they figure out what works best for them and their organizations.

 

You Are Your Best Thing: Vulnerability, Shame Resilience, and the Black Experience

We are looking forward to reading this product of a collaboration between Tarana Burke and Brene Brown—something that combines Brown’s work on vulnerability with Burke’s work on shame resilience. They bring in Black authors, artists, activists, and more to share their stories—resulting in a “stark, potent collection of essays on Black shame and healing” within a space where we can “recognize and process the trauma of white supremacy…be vulnerable and affirm the fullness of Black love and Black life.”⁴

Brave New Work: Book & Podcast

This resource started as a book and has continued on as a podcast about the way we work. Author Aaron Dignan explores the “operating systems” of organizations—the things that comprise organizational culture—and how we can improve the ways we work.

 

 

The Making of a Manager: What to Do When Everyone Looks to You

There’s increasing research that, to improve performance, employee engagement, and other key metrics, orgs should focus on helping their managers become better managers and leaders. This book by Julie Zhuo is a practical guide designed to do just that. Each chapter focuses on a specific aspect of management—for example, holding effective meetings (and canceling unnecessary ones)—and offers specific advice to new managers learning the ropes.

 

 

More Reading

For more sources related to our current research agenda, check out these lit reviews:

• Learning Content in the 2020s: What the Literature Says
• Choosing Learning Tech: What the Literature Says
• The Changing Perspective on Mobility
• Competencies vs. Skills: What’s the Difference?
• Skilling: 5 Themes in the Conversation
• The Purpose-Driven Org: What the Literature Says

What Are You Reading?

You might have noticed from this article that we love reading. We want to hear from you: What are you reading these days? What questions are you trying to answer for yourself?

Share your favorites with us at [email protected]!

DEIB Tech: Its Time Has Come

Global pandemic. Protests. Elections. Riots. (And whatever else happens between when we publish this article and you read it.) Needless to say, the last year has been rough. It laid bare our differences in stark relief. Shown how events impact diverse people differently. Perhaps it caused you some measure of disgust, despair, or even depression. At a minimum, it likely contributed to exhaustion.

But, at the same time, the last year has also revealed our underlying humanity. The extent to which we care about other people. The depth at which we hold our beliefs about our country. The potential we have when we work together (hello, COVID-19 vaccine!).

Given all this, there has never been a greater need for a focus on diversity, equity, inclusion, and belonging (DEIB) – both in our society and in our organizations. We have a need to understand each other and to work together, more than ever before.

Organizations throughout the world have recognized this, from top leaders to DEIB leaders to managers and employees. It’s for this reason companies are talking about DEIB more in their earnings reports than ever before and why the number of DEIB job openings has skyrocketed. The thing is this: organizations cannot just talk about DEIB and hire people to lead it. That is a good start, but it’s not enough. Organizations need to change their systems, practices, and behaviors. The change cannot just rely on individuals – it has to be baked into how the organization operates.

This is where DEIB technology can help, as it has the potential to build in practices, behaviors, insights, and recommendations that address bias. It can also provide insights about what is actually happening with people (versus relying on anecdote-based understanding) at the moment of critical decision-making about talent.

Tripping down memory lane

When we first began studying the D&I tech market in 2018, the #MeToo movement had thrust diversity and inclusion in the workspace under a spotlight. Stories and accounts of workplace discrimination, harassment, and unethical behaviors toward women in the workplace led numerous businesses to pledge to change their policies and take action.¹ As a result, organizations began to feel a greater need for systemwide solutions.

In 2018, we launched our first research study on this topic, and we published a comprehensive report, Diversity & Inclusion Technology: The Rise of a Transformative Market, in February 2019. The study included a list of all the D&I vendors we identified and was accompanied by a detailed vendor landscape tool (with 2 updates since). As we shared in our initial report, tech can play a transformative role.

Fast forward to today

We (still) find ourselves in the midst of health, social, and economic crises. 2020 was not an easy year for anyone, but it especially impacted diverse people in many significant ways, including:

• Women left the workforce in record numbers
• Lower-income earners saw their jobs evaporate
• The murders of George Floyd, Breonna Taylor, and others disproportionately impacted the Black community

Many companies have responded by making pledges or promises in support of the #BLM movement.² A large number of them have focused on increasing diversity levels within the companies, both at the employee and leadership levels (for examples of such corporate pledges, see Diversity, Equity, Inclusion & Belonging: Creating a Holistic Approach for 2021).

As the pressure to follow through on these promises increases, leaders must develop strategies to achieve them––and we believe that DEIB tech represents one of the critical components of the process (see Figure 2 further down). Sophisticated tech––such as artificial intelligence (AI), deep machine learning, natural language processing (NLP), and organizational network analysis (ONA)––can help leaders manage DEIB better and more easily and are increasingly becoming more accepted as essential tools for people practices.³

Through this report, we aim to achieve 4 things:

1. Help leaders understand the role of DEIB tech
2. Provide insights on the state of the DEIB tech market
3. Highlight the talent areas focused by vendors
4. Guide leaders who may be looking to make tech investments

Key Findings

The study covers three major areas and how they have changed since 2019: the DEIB tech market, talent areas vendors focus on, and what buyers should consider before investing. We also address what we see coming next. Some of the key findings from the study include the following:

1. Three major shifts punctuate the current DEIB tech market
   • In previous years, leaders were especially focused on gender; in 2020-21, the emphasis has evolved to include a focus on race and ethnicity.
   • Social justice movements and conversations around discriminatory workplace practices and behaviors have led to greater attention to inclusion than ever before.
   • The role of AI in mitigating bias to enhance DEIB has come front and center, and more approaches have been introduced to address this issue.
2. The DEIB tech market is hotter than ever
   • The global market size is estimated to be $313 million and growing, up from $100 million in 2019.
   • The number of HR tech vendors offering features or functionalities that cater to DEIB as part of their solutions has increased by 136% since 2019.
   • The total number of DEIB tech vendors increased by 87%, with a total of 196 vendors in the market for 2021, compared with 105 in 2019.
3. People analytics for DEIB has arrived
   • Lack of analytics and insights on DEIB is the primary challenge the majority of vendors help their customers solve, hence the growing number of solutions. providing DEIB analytics in 2021 compared to 2019 (28% vs 26%, respectively).
4. Small-sized organizations and knowledge industries remain the main customers of DEIB tech
   • The largest customer category is small-sized organizations (those with less than 1000 employees), who represent almost 30% of all DEIB vendor customers.
   • However, these small organizations represent a smaller percentage of DEIB vendor customers in 2021 than in 2019, and there was an increase in the percentage of customer organizations in the 10,000-50,000 range.
   • The industries most likely to be DEIB tech customers are concentrated in knowledge industries, namely technology, financial, banking, and insurance.

Check Out the Full Study and Tool

The full study (available to members) has lots more information than what we’ve detailed here, including many more details on the market, customer quotes and feedback, and checklists for leaders interested in DEIB tech.

In addition, we encourage you to check out the brand new, fully redesigned DEIB Tech tool, which is available both to members and non-members. You can look at the 196 vendors in each of the four talent areas and their relevant sub-categories. RedThread members can click through and see details on individual vendors.

 

 

RedThread members can see the areas of talent vendors focus on, the top industries served, vendor capabilities, strengths, challenges addressed, and customer feedback (see Figure 3). We provide the maximum amount of information we can, based on what vendors shared with us or what we were able to find publicly available. This tool is designed to be evergreen, so it will be updated continuously as we conduct briefings throughout the year.

 

A Thank You

This study involves a significant time investment from everyone who participated in its development. We want to thank all of the vendors and customers who gave their time, energy, and expertise to make this such a robust study and tool.

If you have any questions about this research or about becoming a RedThread member, please contact us at [email protected].

 

 

Last Friday, we suggested that February would provide us with another strong next segment of HR tech market watching (did you take that popcorn out of the microwave like we advised?!). And wow, do we have a good one on our hands!

Today Microsoft announced Viva, a single employee experience platform “designed to empower people and teams to be their best.”

This announcement fundamentally reshapes the employee experience and people analytics tech market.

 

Those of you who know us well know that we don’t throw that type of language around lightly — and thus had to write a long blog to share our thoughts (#Sorry #NotSorry).

We’re going to explain what this new product is, why it’s such a big deal to the employee experience and people analytics tech market, and the implications for Glint (the engagement solution Microsoft bought 2.5 years ago).

What is Microsoft Viva?

For those of you who have been following along, you know we've predicted Microsoft would enter the employee experience market for years, especially following its acquisition of GitHub, LinkedIn, Lynda.com (now LinkedIn Learning), and Glint. That day has finally come.

Built on top of Microsoft 365 and Teams, Viva offers four modules (see Figure 1), which combine existing Microsoft offerings into a single solution:

• Connections – Creates a “digital campus” where all policy, benefits, communities, and other centralized resources are available. (Available this summer.)
• Insights – Combines Microsoft Workplace Analytics, My Analytics, and Glint to provide employees with insights on how they work, and gives managers and leaders information about their teams, burnout risk, after-hours work, etc. (Available now.)
• Topics – Leverages Project Cortex to identify knowledge and experts across the organization, generating topic cards, topic pages, and knowledge centers (including people – not just information) for others to access – a “Wikipedia of people and information” for the org. (Available now.)
• Learning – Integrates LinkedIn Learning (formerly Lynda.com), Microsoft Learn, and other external sources (including LMSs or LXPs such as Cornerstone and Skillsoft) into a single location within Microsoft. (Available this summer.)

For the newbies here, let’s clarify a few things: What is employee experience and how does tech support it?

Let’s take a step back here and provide a definition, as folks like to throw around the term “employee experience” like a magic eight ball (shake it and a different definition comes out each time!).

We define employee experience as:

Employees’ collective perceptions of their ongoing interactions with the organization¹.

 

Within that definition, there are some nuances, which we illustrate in Figure 2. The main point is this: employee experience encompasses the entire experience – not just tech.

However, tech vendors – who have been largely responsible for popularizing the term – have only generally focused on a subset of employee experience:

• Improving and measuring employees’ tech experiences
• Measuring employees’ collective perceptions, primarily (though not solely) through surveys

Until a few years ago, vendors tended to stay in one of those two boxes. However, we’re seeing more overlap than we used to, such as employee experience vendors moving more into employee engagement (e.g., Qualtrics or Medallia) or HCM vendors offering employee surveying solutions (such as what we talked about last week with the Workday / Peakon acquisition).

Despite all the great things about employee experience vendors, many of them face 3 important challenges:

• Surveys are limited in scope. Surveys can only report on the specific items in the survey, only measure employees’ perceptions (vs. what actually happened), and can only be done with limited frequency (#surveyfatigue).
• Experience data are incomplete. Even in vendors that extend beyond survey data, they are often still limited in terms of the data available: the data necessary to truly understand how employees work exists outside these vendors’ solutions.
• Integration and analytics capabilities are limited. Many (though not all) of these solutions are not built to integrate varied data types at scale or to conduct deep analytics, limiting their ability to explain employee experience outside of the data they capture or integrate.

As a result of these challenges, many employee experience vendors partner with multi-source analysis platforms (e.g., Visier, Crunchr, OneModel, SplashBI, HCMI Solve and others in our people analytics tech tool), which specialize in data integration and deep analysis. Those tools’ core capabilities are integrating varied data sources and deriving meaningful insights from a lot of data. A prime example of this is the announced partnership between Visier and Medallia.

In sum, employee experience vendors, to date, have only covered part of employee experience – leaving open space for someone who can (at least claim to) do it all.

Why is Viva – and Viva Insights in particular – such a big deal?

Microsoft Viva has the potential to do three really important things:

• Cover nearly all digital aspects of employee experience, unlike any other vendor on the market
• Integrate expansive amounts of passive, continuous behavioral employee data with perception data (only for Glint / Microsoft / Workplace Analytics customers)
• Seamlessly provide deep analytics and insights of these larger data sets via Glint and Microsoft Workplace Analytics

These three capabilities are why we think this announcement fundamentally reshapes BOTH the employee experience and the broader people analytics tech market.

 

Let’s start with the first two points about the breadth of employee experience and data types. Through its combination of offerings, Viva will have access to continuous, passive, behavioral data in the areas that most of the other employee experience and people analytics vendors do not:

• Work Relationships: LinkedIn (who you know, inside and outside your company), Office 365 (also who you know, but combining that with email, calendars, Teams, Yammer, SharePoint interactions, etc.)
• Work Environment: Office 365 — including SharePoint — products (where work is getting done), but also Connections (the central hub) and Topics (the “Wikipedia of the org”)
• Org practices: Office 365 (how work is getting done and with whom), Topics (where and with whom information resides), LinkedIn Learning (what people are learning), and Glint’s performance development capabilities (360s, anytime feedback, development goals, and manager nudges)

Viva Insights will also be able to address the other areas existing experience vendors cover, such as improvement and analysis of highly repeatable experiences and employee engagement / experience surveys (Glint).

Finally, Viva Insights will provide an integrated, deep analytics platform with the combination of Glint, Workplace Analytics, and My Analytics (for employees). There will be no need for customers to marry two different vendors and hope they can sort out data integration challenges. Viva Insights should do all of this, seamlessly, and then integrate it into Teams and Office 365. It is important to note that all of the above is only possible if companies are customers of the relevant products (e.g., Glint and Workplace Analytics), but there are no additional integration costs.

With this offering, Viva has the potential to fill the gaps left in the employee experience market, and thus fundamentally change it.

What does this mean for Glint?

First, it is critical to note that Glint will continue to operate as a standalone offering, in addition to being integrated into Viva. The integration of Glint into Viva – and the inherent integration of Glint with Workplace Analytics that comes with it – means that Glint’s aperture of employee experience is much bigger, and moves beyond employee engagement (perception) data to include passive, continuous behavioral data. Glint, through these integrations, will be the only vendor that will be able to do this at such scale.

The primary benefit of this is leaders will be able to connect how people feel to how people work.

 

The specific types of questions they will be able to answer are things like:

• What work patterns and habits correlate with specific employee perceptions?
• How do those sentiments influence how people work and collaborate?

Practically speaking, that means leaders can tell if manager 1:1s, large team meetings, or growth in after-hours work is impacting employee engagement as well as other perceptions.

Given the recent (and critical) focus on mental health and wellbeing, this connection of data sources – and literally being able to see what people are doing and how it is affecting them – could be a game changer for many customers, and thus for Glint, as well. Customers will be able to access this analysis either within Workplace Analytics (Figure 3) or Glint (Figure 4).

 

Glint is very likely to get a super-charge to their business as a result of this announcement.

There are numerous reasons for this:

• Glint gets more looks. Existing Microsoft and Workplace Analytics customers looking for an employee engagement solution will be more likely to look at Glint due to the integration.
• More actionable data. The integration with Viva and Workplace Analytics will give Glint customers the ability to access data that tells leaders which behaviors (as measured by all these passive data sources) are resulting in different outcomes, and as such those data will be highly actionable.
• Data where people will use it. The integration of Glint data into so many other Microsoft products means customers won’t have to step out of the apps they use to access the data. It will be presented in the course of the normal workday, enhancing the likelihood of action and thus impact.

Also, looking forward, there are many future product offerings Glint could develop as a result of gaining access to this richer data set (e.g., organizational network analysis (ONA), targeted manager offerings based on more relevant, real-time data).

It all sounds so good. What could go wrong?

The sections above outline what could be. We all know that the reality can be harder.

First, much of the success of this product requires the different parts of Microsoft to collaborate with each other effectively. We all know that large companies don’t always do that. Further, much of this product involves successfully stitching together existing products and, again, that is often easier said than done, due to tech debt, tech limitations, and in some cases, egos.

Second, one of the big selling points here is that all the data actually integrates and everyone has access to what they need. Even though Microsoft is one company, it is highly unlikely that much of this data is on a similar architecture (especially when you factor in the number of acquisitions being pieced together here – oy vey!). I imagine that a lot of this data alignment work has been done, but we all know the devil is in the details when it comes to data integration. Further, a company has to be customers of all these various solutions in order to reap the benefits of data integration.

Finally – and this is the elephant in the room – there are issues of data privacy and ethics. All these data together – especially data coming from work productivity apps – presents some really thorny issues. We’ve been told that the following data privacy steps have been taken:

"Leaders and managers using Viva Insights in Glint—currently in pilot—can see only aggregated, de-identified results based on the confidentiality thresholds built into Glint. The Glint dashboard will never display Viva Insights information about an individual's work patterns."

While these are all real and meaningful steps to take, there will likely remain other questions, such as:

• Will employees be told that these types of data will be collected and what will be done with them?
• Will employees have the ability to opt out?
• What are the ethical implications and unintended consequences of looking at all these data together? (Perhaps the most important question of them all.)

What does this mean for the broader employee experience, people analytics, and HR tech market?

There are a lot of broader market implications of this announcement, but we have space for just a few:

• Passive / continuous data is now a must for employee experience vendors. Employee experience and engagement vendors that don’t have a way to access continuous data need to figure it out and FAST.
• Multi-source analysis platforms may be the next area of acquisitions. Given the pressure this puts on seamlessly combining lots of data with platforms that can analyze it, we may see some of the multi-source analysis platforms be purchased by bigger HCM or employee experience providers.
• Big money is here for real in the employee experience market. In case you needed more convincing after last week’s heady news of the $27 billion valuation of Qualtrics and the Workday acquisition of Peakon, this deal should reinforce one thing: BIG money is now here in employee experience and HR tech. And it is going to crash plenty of other parties.

As we all know, the proof will be in the pudding when it comes to how well this new offering serves customers. However, it has all the pieces to be truly transformational for our industry, and we expect it to drive some quick responses from competitors. The next segment of HR Tech watching should be another good one.

Until next time, stay well and safe — and please, don't forget the popcorn!

As many of you can see from the headlines, yesterday’s Qualtrics IPO was incredibly successful, with the stock closing 51% above its initial price, and the end of day stock price on Thursday valuing the company at $27.3 billion.

What we wanted to think about, though, is: What does this really mean for Qualtrics, SAP, and the broader employee engagement / experience market?

Let’s start with Qualtrics.

For those of you who have been following the story, you know that SAP bought Qualtrics for $8 billion before its intended IPO in 2018. They held the company for roughly 2 years, and then, as of yesterday, raised approximately $27 billion from the public markets. While that is a phenomenal return on investment for SAP (more on them later), Qualtrics also got a lot out of this little detour on its journey to IPO.

First, Qualtrics achieved a scale it would have struggled to reach on its own. SAP took Qualtrics leaders under their wings, expanded Qualtrics’ international offerings and capabilities, brought Qualtrics into verticals (e.g., supply chain) they were not in previously, and generally taught them the ropes of being a public company. This mentorship – if we can call it that – of Qualtrics leaders means the company is likely more prepared to execute at scale than at least some of its competitors.

Second, the last 2 years have given Qualtrics an opportunity to broaden its strategy and focus on being much more of a platform player across the entire process of designing and executing customer or employee experience, as shown by Figure 1. We imagine that the SAP experience has encouraged Qualtrics to dream bigger when it comes to knitting together their platform with a combination of partners who can deliver the services aspect of their work.

Finally, SAP’s obvious focus on human capital (among other factors) may have influenced Qualtrics to focus more on their people experience business (which they call EmployeeXM) moving forward. While Qualtrics has been saying they were making this shift to focus more on EmployeeXM for some time, the reality of the shift was most recently exemplified by the move of Jay Choi, formerly leader of EmployeeXM, to Chief Product Officer over all Qualtrics products (CX, EX, PX, and BX).

Critically, the last two items underscore why it was increasingly important for Qualtrics to become more independent. If the company was going to make a broader platform play and focus more on employee experience, it needed to build beyond the SAP ecosystem and expand to a broader set of potential partners (including SAP competitors such as Workday, Oracle, and some of the HRIS systems targeted at SMBs).

Net-net: the road through SAP to IPO gave Qualtrics scale, a broader experience management strategy, and a greater focus on employee experience — plus a ton of cash.

But the big winner in all this is SAP.

First, there’s the crazy amount of money SAP just made from this IPO. We couldn’t find a public source for their exact profit, but given that they bought the company for $8 billion and it just got valued at north of $27 billion, we think SAP did more than just *alright*.

But here’s where SAP was really smart.

SAP gets to pocket those billions AND it retains financial control over Qualtrics. “Wait…WHAAAT?!?” you might be thinking (especially after having read above about the importance of Qualtrics’ independence).

Yeah, right at the top of their S-1 (the financial document a company has to file to go public), is the statement that Qualtrics was offered with two levels of stock: Class A and Class B.

“SAP will own all 423,170,610 shares of Class B common stock…Each share of Class A common stock is entitled to one vote and each share of Class B common stock is entitled to ten votes…This means that, for the foreseeable future, investors in this offering and holders of our Class A common stock will not have a meaningful voice in our corporate affairs and that the control of our company will be concentrated with SAP.”

Buried on page 47, the S1 states:

“As a result, SAP will have the ability to control all matters affecting us, including:

• the composition of our board of directors and, through our board of directors, any determination with respect to our business plans and policies;
• any determinations with respect to mergers, acquisitions and other business combinations;
• our acquisition or disposition of assets;
• our financing activities;
• […a whole bunch of other things, omitted for brevity…] and,
• the strategy, direction, and objectives of our business.”

So, SAP made a ton of money and it still – in legal terms, even if not in day-to-day operations – maintains control over Qualtrics.

Is this (not so tiny) distinction going to matter? We give it a cautious “maybe.”

As we wrote about before, we’d been hearing that Qualtrics already had an incredible amount of autonomy for an acquired company before this spin-out. Further, we’ve also been told that the primary reason for this spin-out is a need for greater independence.

However, things can change fast. The spin-out was at least partially due to leadership transitions, initially precipitated by former SAP CEO Bill McDermott leaving (now CEO at ServiceNow) and reinforced by the sudden departure of SAP’s American co-CEO, Jennifer Morgan. While founder Ryan Smith plans to remain as executive chairman and Zig Serafin as CEO, they can’t stay forever. Should SAP leadership change or become dissatisfied with Qualtrics’ leadership, they could certainly make significant changes.

Change is not the plan for now, but plans change.

In short, SAP made a ton of money and still has the keys to the castle, though they say they aren’t involved in the running of the kingdom.

Perhaps the biggest story is how much money just got put into the EX tech market.

Perhaps the biggest news here, though, is that through this IPO, BILLIONS of dollars just got put into the hands of SAP and Qualtrics – and they will use them. Sure, there will be product innovations and maybe customer service improvements. But what is most likely to happen?

You guessed it: acquisitions.

(Read here for more on our thoughts on why acquisitions are going to be the name of the game for the people analytics tech market in 2021.)

Let’s just focus on Qualtrics (SAP is too wily a beast to make these types of predictions). If we look at where we place them on our people analytics tech 2×2 (see Figure 2), you can see there’s still quite a bit of room for them to move to the right on our “continuous analysis” axis. In short, this means we think there’s still a lot of opportunity for Qualtrics when it comes to using digital exhaust and unstructured data to understand employee experience. Qualtrics have themselves called out (in Figure 1) their intent to focus heavily on continuous listening (#surveyfatigue).

Given this, I’d expect Qualtrics to potentially push into the always-on employee listening space or passive organizational network analysis (ONA) — which could be paired nicely with active survey-driven ONA (again, see Figure 2).

Another area they might go into is the multi-source analysis space. These vendors pull in data from a very wide set of sources and provide detailed and complex analysis capabilities, primarily for people analytics practitioners and HR business partners, but also HR leaders, business leaders, C-suite execs, and employees. Given Qualtrics’ desire to be a data hub – and to understand the entire employee experience – we could see this as another reasonable direction.

Finally, the employee experience starts with talent acquisition. Labor market analysis capabilities would fit nicely into Qualtrics’ overall focus on end-to-end employee experience. Both of these latter two areas would jive really well with Qualtrics’ social science-heavy roots.

Despite all our conjectures above, it is worth noting that Qualtrics’ strategy is very much an ecosystem play. Therefore, Qualtrics may choose to invest instead in collaborating with a system of partners in these areas – or at least do that before acquiring or building the tech themselves. But invest they will – this money has to go somewhere to continue to fuel their growth.

What now?

Well, as observers of all this stuff, this is when we break out the popcorn and watch the show. Because we’re certain it WILL be a show in 2021. What do we expect to see?

• This IPO will allow Qualtrics to be MUCH more competitive in the employee experience / engagement market, as they invest this money into their product and services
• The employee engagement / experience tech ecosystem is likely to change, either via acquisitions or through intentional partnerships
• We’re going to see even more institutional / external investors in the HR tech space, given how well Qualtrics performed – which will fuel more growth in the broader HR tech vendor market – starting the cycle anew

For now, let’s all have a good weekend… and take that popcorn out of the microwave as we look to February to provide the next segment.

Just yesterday, we presented at the People Analytics & Future of Work Global Conference, and told the audience: “In 2021, we are going to see a lot more market consolidation.” And here we are, with example number one: Workday’s announcement today of its acquisition of Peakon (a Danish employee engagement provider).

Though smart, this is an unsurprising (and not market transforming) move on Workday’s part. Why?

Let’s start by examining why we expect market consolidation.

First, there have been huge investments in HR tech over the last decade – one estimate is that investors put nearly $5 billion into the industry last year alone – and that’s resulted in a highly fragmented market of specialized players across our entire HR tech industry.

This is nowhere more prevalent than with employee engagement and experience – the single largest (36%) and fastest growing category in our people analytics tech study. And that isn’t going to change:  due to COVID-19, social justice movements, remote work, etc., employee engagement and experience was by FAR the most in-demand people analytics area last year, with 63% of people analytics practitioners telling us they focused in this area in 2020 (a number we expect to see rise in 2021). Highly fragmented, lots of external investors, and quick growing = market ripe for consolidation.

Second, across the last year, we’ve recognized that we need more and higher quality data on our people. That requires that the data be easier to integrate. That can be done through an ecosystem that plays nicely with each other (similar to what Visier, Medallia, EMSI and others are doing with their “People Intelligence Alliance”) or by acquisition.

Right now, employee engagement / voice solutions are amongst the easiest to buy and implement (despite what some might tell you), as evidenced by the fact that a lot of these vendors went to a freemium model during the earlier parts of the COVID crisis and allowed potential customers to just turn the tech on themselves. However, what isn’t easy is the data integration piece: connecting engagement / experience / voice data to other data that can tell you something more meaningful.

So why did Workday acquire an employee engagement provider?

The most obvious reason is that Workday needed an employee engagement solution. As you can see in our people analytics tech 2×2, Workday has solutions in most of the other areas we cover, but it didn’t have an explicit employee engagement solution. (As an aside, to my knowledge they also don’t have an organizational network analysis solution – so you ONA providers might want to see if there’s any more Workday M&A budget available for 2021!)

But why wouldn’t Workday just build out their existing capability, instead of buying a company? A few reasons:

• High-quality engagement solutions are deceptively hard to build;
• There are a lot of really good independent engagement vendors open to being acquired (even after this acquisition!); and,
• This allows Workday to meet customers’ needs now, not in a few quarters’ time.

Further, the acquisition enables Workday to reinforce their single data model approach, as opposed to doing the ecosystem play – which we all know isn’t their main jam (though Prism allows data integration from external sources). By purchasing an engagement provider, they can ensure a single source of data truth when it comes to engagement data, which will make all the rest of their data offerings stronger.

There are lots of employee engagement vendors. Why Peakon?

Many of you may not know who Peakon is – I didn’t until about 18 months ago – but there’s a lot to like about them. First, Peakon is a high-quality platform, with engaged customers and devoted employees (similar to Workday).

Second, in addition to the engagement capabilities, Peakon brings two other offerings that will bolster the Workday toolbox: Grow (a performance solution) and Include (a diversity, equity, inclusion & belonging (DEIB) solution).

Let’s start with Grow. As we’ve written many times (such as here and here), we see performance and engagement becoming ever-more intertwined. Peakon’s solution is a primary example of how performance development and engagement can be bundled together effectively. This offering will surely bolster Workday’s performance solution, which is lacking in some of these capabilities.

Include will also strengthen Workday. This solution allows leaders to integrate DEIB analysis with the engagement offering. In some ways, these capabilities mirror Workday’s recently announced VIBE Index, which is a good thing, as there is overlap in vision. However, Peakon supplements Workday’s existing offerings in important ways:

• In-product features to safely report misconduct;
• Flagging of sensitive (including violence, criminal behavior, safety and wellbeing, etc.) comments for anonymous follow-up by HR; and,
• In-product links to micro-training on building more inclusive teams.

Finally, Peakon checks other important boxes:

• Financial: They completed a roughly $36 million Series B just under two years ago, which means they had significant funding, but not nearly as much as some of their competitors – and so were relatively affordable at the $700 million price tag. Given Peakon’s pricing, customer numbers, and growth rate, I imagine that the ROI on this investment will be very strong for Workday.
• Technical: Peakon is roughly 6 years old (depending on when you start counting) and thus has a modern tech stack and likely less tech debt.
• Cultural: There’s strong cultural and values alignment.

So, to sum it up, this is a good – but entirely predictable – buy for Workday. It doesn’t signal significant shifts in the market. It doesn’t fundamentally change things for the other engagement providers.

This deal is sound. It is smart. Well done, Workday and Peakon. We look forward to seeing how this works in practice.

 

DEIB Tech: Its Time Has Come

Global pandemic. Protests. Elections. Riots. (And whatever else happens between when we publish this article and you read it.) Needless to say, the last year has been rough. It laid bare our differences in stark relief. Shown how events impact diverse people differently. Perhaps it caused you some measure of disgust, despair, or even depression. At a minimum, it likely contributed to exhaustion.

But, at the same time, the last year has also revealed our underlying humanity. The extent to which we care about other people. The depth at which we hold our beliefs about our country. The potential we have when we work together (hello, COVID-19 vaccine!).

Given all this, there has never been a greater need for a focus on diversity, equity, inclusion, and belonging (DEIB) – both in our society and in our organizations. We have a need to understand each other and to work together, more than ever before.

Organizations throughout the world have recognized this, from top leaders to DEIB leaders to managers and employees. It’s for this reason companies are talking about DEIB more in their earnings reports than ever before and why the number of DEIB job openings has skyrocketed. The thing is this: organizations cannot just talk about DEIB and hire people to lead it. That is a good start, but it’s not enough. Organizations need to change their systems, practices, and behaviors. The change cannot just rely on individuals – it has to be baked into how the organization operates.

This is where DEIB technology can help, as it has the potential to build in practices, behaviors, insights, and recommendations that address bias. It can also provide insights about what is actually happening with people (versus relying on anecdote-based understanding) at the moment of critical decision-making about talent.

Tripping down memory lane

When we first began studying the D&I tech market in 2018, the #MeToo movement had thrust diversity and inclusion in the workspace under a spotlight. Stories and accounts of workplace discrimination, harassment, and unethical behaviors toward women in the workplace led numerous businesses to pledge to change their policies and take action.¹ As a result, organizations began to feel a greater need for systemwide solutions.

In 2018, we launched our first research study on this topic, and we published a comprehensive report, Diversity & Inclusion Technology: The Rise of a Transformative Market, in February 2019. The study included a list of all the D&I vendors we identified and was accompanied by a detailed vendor landscape tool (with 2 updates since). As we shared in our initial report, tech can play a transformative role.

Fast forward to today

We (still) find ourselves in the midst of health, social, and economic crises. 2020 was not an easy year for anyone, but it especially impacted diverse people in many significant ways, including:

• Women left the workforce in record numbers
• Lower-income earners saw their jobs evaporate
• The murders of George Floyd, Breonna Taylor, and others disproportionately impacted the Black community

Many companies have responded by making pledges or promises in support of the #BLM movement.² A large number of them have focused on increasing diversity levels within the companies, both at the employee and leadership levels (for examples of such corporate pledges, see Diversity, Equity, Inclusion & Belonging: Creating a Holistic Approach for 2021).

As the pressure to follow through on these promises increases, leaders must develop strategies to achieve them––and we believe that DEIB tech represents one of the critical components of the process (see Figure 2 further down). Sophisticated tech––such as artificial intelligence (AI), deep machine learning, natural language processing (NLP), and organizational network analysis (ONA)––can help leaders manage DEIB better and more easily and are increasingly becoming more accepted as essential tools for people practices.³

Through this report, we aim to achieve 4 things:

1. Help leaders understand the role of DEIB tech
2. Provide insights on the state of the DEIB tech market
3. Highlight the talent areas focused by vendors
4. Guide leaders who may be looking to make tech investments

Key Findings

The study covers three major areas and how they have changed since 2019: the DEIB tech market, talent areas vendors focus on, and what buyers should consider before investing. We also address what we see coming next. Some of the key findings from the study include the following:

1. Three major shifts punctuate the current DEIB tech market
   • In previous years, leaders were especially focused on gender; in 2020-21, the emphasis has evolved to include a focus on race and ethnicity.
   • Social justice movements and conversations around discriminatory workplace practices and behaviors have led to greater attention to inclusion than ever before.
   • The role of AI in mitigating bias to enhance DEIB has come front and center, and more approaches have been introduced to address this issue.
2. The DEIB tech market is hotter than ever
   • The global market size is estimated to be $313 million and growing, up from $100 million in 2019.
   • The number of HR tech vendors offering features or functionalities that cater to DEIB as part of their solutions has increased by 136% since 2019.
   • The total number of DEIB tech vendors increased by 87%, with a total of 196 vendors in the market for 2021, compared with 105 in 2019.
3. People analytics for DEIB has arrived
   • Lack of analytics and insights on DEIB is the primary challenge the majority of vendors help their customers solve, hence the growing number of solutions. providing DEIB analytics in 2021 compared to 2019 (28% vs 26%, respectively).
4. Small-sized organizations and knowledge industries remain the main customers of DEIB tech
   • The largest customer category is small-sized organizations (those with less than 1000 employees), who represent almost 30% of all DEIB vendor customers.
   • However, these small organizations represent a smaller percentage of DEIB vendor customers in 2021 than in 2019, and there was an increase in the percentage of customer organizations in the 10,000-50,000 range.
   • The industries most likely to be DEIB tech customers are concentrated in knowledge industries, namely technology, financial, banking, and insurance.

Check Out the Full Study and Tool

The full study (available to members) has lots more information than what we’ve detailed here, including many more details on the market, customer quotes and feedback, and checklists for leaders interested in DEIB tech.

In addition, we encourage you to check out the brand new, fully redesigned DEIB Tech tool, which is available both to members and non-members. You can look at the 196 vendors in each of the four talent areas and their relevant sub-categories. RedThread members can click through and see details on individual vendors.

 

 

RedThread members can see the areas of talent vendors focus on, the top industries served, vendor capabilities, strengths, challenges addressed, and customer feedback (see Figure 3). We provide the maximum amount of information we can, based on what vendors shared with us or what we were able to find publicly available. This tool is designed to be evergreen, so it will be updated continuously as we conduct briefings throughout the year.

 

A Thank You

This study involves a significant time investment from everyone who participated in its development. We want to thank all of the vendors and customers who gave their time, energy, and expertise to make this such a robust study and tool.

If you have any questions about this research or about becoming a RedThread member, please contact us at [email protected].

 

 

SAP announced that it plans to take Qualtrics public at some nebulous date in the near future. This is after SAP spent $8 billion in cash to acquire the company in late 2018, just days before Qualtrics was due to IPO.

Why sell (some of) Qualtrics?

This is rare. Buying and selling companies on short-ish timeframes is usually the domain of private equity firms. But even those firms are typically operating on 3-5 year time horizons, after making significant changes to the company. SAP is selling Qualtrics after 18 months – and the only meaningful change we can see is a significant increase in Qualtrics’ revenue.

Three plausible reasons we can think of for the IPO are:

• Financial
• Change in leadership
• Post-acquisition blues

Today, a lot of ink has been spilled about the potential financial upside of selling Qualtrics – this article and podcast from Tech Crunch are especially good. Essentially, Tech Crunch is saying that, with Qualtrics’ run rate of ~$800 million in annual revenue, SAP could reasonably expect a 17.3 times revenue valuation of Qualtrics – putting it at about $13.8 billion on an IPO.

Therefore, even with the eye-popping cash investment of $8 billion, SAP could stand to make a lot of cash just for having bought and held Qualtrics for 18 months (kind of like if you bought a house in 2009 and sold it last year, but on an even shorter timeframe). SAP will remain the majority stakeholder in Qualtrics (at what percentage, we do not know), so it won’t be getting all that cash – but the potential IPO still represents a significant cashflow infusion to its business.

This is all great and good, but we have to ask – Why does SAP want to sell Qualtrics now?

Financial

The first reason could be that SAP wants the cash. In today’s earnings call, the company mentioned a significant focus on cashflow in the midst of the pandemic (who is not looking at cashflow?!?). Selling part of Qualtrics generates a significant cash bunker for SAP.

It may also be that SAP thinks that we’re in for a significant long-term economic downturn, but that cloud-based businesses are still highly valued, so this is a good time to sell if they are ever going to. They may also, as they said, want to invest in other "strategic initiatives" (like S4/Hana), so are looking to free up some money.

No matter the reason, SAP can get a lot of cash – and everyone likes cash when the economy is tight.

Change in leadership

Another reason could be a lack of leadership alignment. When SAP bought Qualtrics, it was very much a meeting of the minds between Ryan Smith, Qualtrics’ founder, and Bill McDermott, SAP’s CEO. Since McDermott left SAP last October for ServiceNow, there’s been volatility at the top: SAP moved into a co-CEO model with Christian Klein and Jennifer Morgan, with Morgan moving on this past April.

It’s possible that the vision shared by Smith and McDermott for Qualtrics was fundamentally different than what has come to pass in the Klein era. Smith clearly still has a strong vision for Qualtrics, as reinforced by the fact that he’ll become the largest individual owner of the company (though, as stated above, SAP will be the largest institutional owner).

Post-acquisition blues

Finally, it may be that the realities of post-acquisition integration were just a harder road than anyone wanted to hoe. We all know that most acquisitions fail, and ones with significant cultural differences, even more so. SAP is a large, traditional organization. Qualtrics is a cloud-based start-up, with a very different culture. Those types of differences can lead to difficulties in everything, from alignment around customer integration to how they manage the partnership landscape to software and services integration.

While I don’t know the details of what has happened, as analysts we can say that the integration of Qualtrics into core SAP SuccessFactors’ offerings has been slower than we would have expected, given SAP’s overriding focus on creating a “human experience platform.”

Bottom line

Throughout the last 18 months, Qualtrics has remained remarkably independent – a point Smith reinforced in the earnings call today. It may make more sense to cut Qualtrics loose now instead of forcing a post-acquisition integration that may not have been working as some in top leadership seats hope.

What now?

SAP reinforced that it’ll remain the majority owner of Qualtrics, and that it intends to continue investing in the “human experience platform,” marrying operational data with experience data (which it neatly calls X+O data). SAP also stated that it’ll remain Qualtrics’ primary R&D partner, which will benefit both organizations. Qualtrics may especially benefit, as there are some innovative start-ups in SAP’s start-up ecosystem. Therefore, we still expect to see a tight and beneficial relationship there, and hope that SAP is able to leverage some of the innovation Qualtrics can offer.

Near term for Qualtrics

The IPO of Qualtrics will allow it to operate more independently, which may allow it to get back into important partnerships with either Oracle or Workday (depending on how close the relationship remains with SAP). It should also allow it to revert to its start-up cultural roots, in terms of how it attracts and retains talent, and how it operates on a day-to-day basis.

Qualtrics’ partnership with SAP’s sales teams likely fueled some of its strong growth over the past 18 months, so the company may face some headwinds as it transitions back to its own salesforce. That said, Qualtrics developed a strong set of COVID-19 resources for customers and has cited those offerings as part of its success in the last few months. Qualtrics is likely to continue building on those successes as, unfortunately, the need for COVID-19 support is unlikely to go away soon.

Further, as we have noted in blogs across the last year, employee experience is a hot market. It’s now even hotter than before, with so many CEOs and senior leaders recently seeing the importance of understanding employee sentiment in light of the pandemic. Qualtrics is a market leader in this space. Even though it won’t have SAP directly behind it anymore, based on today’s earnings call, it seems that Qualtrics will retain some significant cash from this IPO to fuel its future growth. Therefore, we expect to see it continue to do very well in the future.

Net-net: This seems like a good, though unusual, deal for all.