Events

Key Findings

1. Skills and competencies are two sides of the same coin. Skills and competencies both help answer 2 critical questions:
   • “What can our workforce do now?”
   • “What will our workforce need to be able to do in the future?”

Although there are differences between the 2—both material and perceived—forward-thinking orgs are finding ways to reconcile skills, competencies, and the data they both offer to solve their people challenges.

2. Leaders don’t need to choose between skills and competencies. HR functions sometimes debate about which framework—skills or competencies—to use. Instead of trying to choose 1 of the 2, however, all of HR should embrace both frameworks to ensure as much information as possible about employees’ abilities and expertise is surfaced. This approach can both afford employees opportunities they wouldn’t otherwise have and also enable the org to make better-informed talent decisions.
3. Skills and competencies can help solve business challenges. Skills and competencies can only be effectively reconciled within the context of the people-related business challenges an org is facing. The 4 people challenges that skills and competencies most often help with are:
   • Employee development
   • Career mobility
   • Diversity, equity, inclusion, and belonging (DEIB)
   • Performance management

4. Leaders should consider all the skills and competencies data available. Having more data (both broader and better) usually equates to having a more complete picture of the skills and competencies within an org—and what’s still needed to meet org goals. As companies begin to consider skills and competencies together, accounting for the data provided by both can help to more fully inform the org’s strategies and decisions.
5. Employees need clear messaging about skills and competencies. Employees and business leaders are often confused by skills and competencies. Many employees don’t care about the differences between the two: They just want to know what’s expected of them. Leaders should create clarity by using consistent terminology and messaging that highlight not only how employees should use skills and competencies systems, but also the benefits of skills and competencies for employees.

Skills & Competencies: Why We Struggle with These Terms

The ongoing skills conversation has ramped up since the beginning of 2020. COVID-19, a social justice movement, and multiple natural disasters have created a business imperative for orgs to pivot quickly and continually. These events have also spotlighted the longstanding need for orgs to support all employees, not just a select few.

Skills, which used to be a conversation about robots taking human jobs, has become one about org agility and inclusivity. Central to this conversation are 2 questions:

• What can our workforce do now?
• What will our employees need to be able to do in the future?

Leaders must help their businesses by figuring out fast, user-friendly ways to answer these questions. Orgs can’t effectively pivot in rapidly evolving environments without clearly understanding what’s currently possible and what’ll be needed in the future.

Orgs can’t effectively pivot in rapidly evolving environments without clearly understanding what’s possible now and what’ll be needed in the future.

Two of the most common frameworks used in this situation are skills and competencies. During our research on this topic, leaders reported having spent hours talking in circles about the definitions of and differences between the 2 frameworks. Most leaders agree that it often feels like a futile and unhelpful conversation, yet they still find themselves engaging in seemingly endless debates about the differences.

Why? From our research, we’ve discovered 3 reasons.

1. Different perceived purposes. Skills and competencies, as defined by HR, are seen to have different purposes, which may affect how they are used to fill business needs. For example, competencies are still important to efforts like performance management and leadership development. And skills have gained in popularity. But orgs haven’t necessarily found a way to reconcile all the perceived differences between skills and competencies.
2. Inconsistent language. The terms “skills” and “competencies” don’t have consistent definitions in the literature—and even within orgs they’re often not clearly defined. People in various parts of the org, therefore, often try to answer the same questions using an assortment of terms (or the same few terms with different meanings), which only creates miscommunication and confusion. Leaders with cross-functional perspectives should see this as an opportunity to align everyone and speak the same language.
3. Technology. Tech platforms often account for skills and competencies in different ways. In some orgs, information about skills and competencies may even reside in multiple systems. This causes confusion and sometimes incomplete data when, for example, one system uses competencies and another skills.

Orgs must reconcile how skills and competencies are defined and used across the business in a helpful and clear way.

Bottom line: Orgs must reconcile how skills and competencies are defined and used across the business in a helpful and clear way. Let’s start by first exploring these 2 terms.

How ARE they different & does it matter?

Confusion with these terms clearly exists. From our literature review, we found lots of contradictory information about what skills and competencies really are. Some sources used these 2 terms interchangeably, while others drew clear distinctions. Leaders we spoke with corroborated this confusion, reporting that most people in their orgs don’t know if the 2 terms are synonymous or different—and whether it even mattered.

The differences do matter—but only to those of us trying to make them work together in our orgs.

As it turns out, the differences do matter—but only to those of us trying to make them work together in our orgs. As we discuss later in this report, messaging to the broader org may need to be very different from what’s going on “under the hood” with skills and competencies.

That said, understanding the key characteristics of skills and competencies can help orgs both leverage each more fully and combine them in helpful ways. When we dug into the characteristics, we found that most leaders agree on the characteristics for each as shown in Figure 1.

Characteristics of skills

In general, skills tend to be more granular, descriptive, and applicable across jobs or orgs. They describe what an employee can do, but rarely do they prescribe how a task or job should be done. Skills data is often dynamic and real-time, since it’s gathered through a number of continually updated sources such as employee skills profiles, social media pages, and operational systems like email. In many cases, the employee is responsible for their own skills profile and development.

Skills tend to be more granular, descriptive, and applicable across jobs or orgs—describing what an employee can do, but rarely prescribing how a task or job should be done.

In more traditionally structured orgs, skills are used to understand (by accessing far better information than a resume can provide) which employees can fulfill open roles. More orgs are paying attention to current employees’ skills as they’ve realized the benefits of hiring internally versus acquiring skills from the outside.

Understanding the skills a workforce has allows leaders to identify individuals who can form teams to accomplish pieces of work.

While the conversation on skills has been around for some years now, the skills movement continues to gather steam as “future of work” conversations continue to happen and orgs continue to move toward project- and team-focused ways of managing work. Understanding the skills a workforce has allows leaders to identify individuals who can form teams to accomplish pieces of work.

Characteristics of competencies

Competencies tend to be broader than skills, prescriptive, and specific to (or at least in the context of) a job or org. They tend to describe the behaviors expected from employees by explaining how a job should be done, or how an employee should perform to succeed in that particular org or job.

Competencies tend to describe the behaviors expected from employees by explaining how a job should be done, or how an employee should perform to succeed in that particular org or job.

While competencies can come across as slightly archaic and cumbersome (particularly as the world becomes more skills-focused), they can provide tremendous value to orgs. Competencies are often seen as the “how” in comparison to the “what” of skills. Because of their focus on behaviors, competencies are essential in some orgs to maintain a healthy culture and, quite frankly, public image. They also provide robust and defensible structures for many performance management systems.

Competencies are often seen as the “how” in comparison to the “what” of skills.

Competencies are typically identified from the top down, involving leaders to identify and outline key expectations—aligning competency data closely with broad org needs, goals, and often culture. But it also means the data is typically static and from a point in time. As such, HR often owns competencies, and is responsible for periodically reviewing and updating them as needed.

“And” not “or”: Making the most of skills & competencies

Perhaps due to the differences in these terms, HR functions may disagree about which one—skills or competencies—to use. Instead of trying to choose 1 of the 2, however, all of HR should embrace both frameworks to ensure as much information as possible about employees’ abilities and expertise is surfaced. This impacts business in 2 ways, as this info:

• May well afford employees opportunities they wouldn’t otherwise have access to or know about
• Enables the org to make better-informed talent decisions

All of HR should embrace both frameworks to ensure as much information as possible about employees’ abilities and expertise is surfaced.

This is no simple feat. There’s no clear “right” way to implement skills and competencies together in an org. That said, our review of almost 100 articles, discussions with 50 leaders in our roundtables, and in-depth interviews with 6 orgs all led us to 3 key strategies that enable orgs to find what works best for them:

1. Using skills and competencies to solve business challenges
2. Identifying and using the data they both provide
3. Crafting a clear message about skills and competencies

In the following sections, we take a closer look at each of these strategies and how they can impact different business challenges.

Using Skills & Competencies to Solve Business Challenges

One of the resounding themes of this research is the need to take business goals into account when considering skills and competency strategies. Leaders emphasized that skills and competencies can only be effectively reconciled within the context of the business challenges the org is facing. One leader put it quite well:

“What’s the business problem you’re looking to solve? A new way to hire people? Learning objectives? Career paths? You might want skills in one situation and competencies in another.”

Christina Norris-Watts, Head of Selection Assessment & Competencies, Johnson & Johnson

We find this idea enlightening. Like most people decisions, use of skills and competencies should depend on what orgs are trying to do. In our discussions with leaders, it was refreshing to see how they view skills and competencies helping with some of their larger people challenges. From those discussions, leaders identified 4 primary business challenges for which skills and competencies could play a role:

• Employee development. How and what kinds of resources are used to build the skills and competencies of the workforce
• Career mobility. How employees move around, up, down, and out of an org, based on both their preferences and the needs of the business
• Diversity, equity, inclusion, and belonging (DEIB). How well an org provides transparent opportunities to all of its employees
• Performance management. How orgs determine an employee’s progress and pay

Interestingly, while for some business challenges either competencies or skills takes the lead, both were identified as being useful to each of these challenges. Let’s dive into them.

Like most people decisions, use of skills and competencies should depend on what orgs are trying to do.

Employee development

We listed employee development as the first business challenge that skills and competencies can help address because it’s likely the most obvious. A 2019 McKinsey study emphasized that the future of L&D depends on the ability to identify and develop the employee skills and competencies which will support the execution of the company’s business strategy.¹

L&D can no longer succeed using the “shotgun” approaches of yesterday—strategies that provide all employees with the same training, regardless of whether or not they need it. Instead, orgs should know, in very targeted ways, what their employees can do and what they need to be able to do—then fill in the gaps.

In very targeted ways, orgs should know what their employees can do and what they need to be able to do—then fill in the gaps.

Understanding skills and competencies can help L&D functions fill those gaps by enabling many types of development opportunities, not just providing content. As development becomes more widely defined, for example, orgs are helping employees find assignments that enable them to grow.

“Let’s say a project requires 10 skills. An employee has 8 of them and wants to develop the other 2. That’s a perfect match because we know the employee can do the project without failing, but will also get some development out of the experience.”

Caroline Theaker, Senior Manager for Learning Strategy, Lloyds Banking Group

In Figure 2, we offer examples of how skills and competencies are each being applied to development issues in orgs today.

Using both skills and competencies improves employee development by helping an employee move toward their career goals (illuminated by skills) and helping an employee improve against performance expectations for their current role (associated with competencies).

Career mobility

The goal of career mobility is to move employees around the org in ways that benefit both the employee and the business. To do this effectively, leaders should know what an employee can do, what they want to do, and where the org has a need.

Skills and competencies can contribute to career mobility efforts by identifying what the employee can do, what they want to do, and where there’s a need.

Thinking in terms of the skills and competencies employees have can contribute to career mobility efforts by identifying what the employee can do (the employee’s skills and competencies) and where there’s a need (the org’s skills and competencies gaps).

Most orgs view skills as being more granular and transferable, so knowing what skills employees have can be valuable for making informed decisions about roles anywhere in the org for which employees may be best-suited.

For example, during the early days of the pandemic, one org had to jettison many of its retail stores. At the same time, it realized an increased need in its customer support function. Because the company understood the skills required to succeed and the skills its retail employees already had, the company reskilled its existing retail employees for a stint in customer service—allowing the org to respond quickly to the crisis. One leader views this as a major benefit of having more granular skills data.

“Skills data is usually transferable across jobs or even industries. That allows companies to be more nimble, agile, and quicker to react to the VUCA² world.”

Learning Lead, global food corporation

Interestingly, while most of the literature and discussion about mobility has focused mainly on skills, competency data can also play a key role in career mobility. Most orgs, thankfully, don’t make decisions regarding how people move about the company based solely on the skills they may have. Particularly in cases of leadership positions, competencies play a big role in mobility decisions, as they define the “how” in how work gets done.

Competencies can also play a role in team formation as well as in the fit and potential performance of employees in new positions.

In our roundtables and interviews, several ideas surfaced about how skills and competencies may be used to address robust career mobility challenges (see Figure 3).

We talked with an enterprise that’s successfully leveraging skills for both employee development and career mobility through a recently launched talent marketplace. Its Talent and Diversity team experimented with the skills data in the system—and specifically, what companywide insights could be extracted from the data.

Diversity, equity, inclusion & belonging

The events of 2020 have compelled orgs to pay much more attention to issues of diversity, equity, inclusion, and belonging (DEIB). Leaders continue to look for ways to level the playing field, give employees the widest possible access to opportunities through mobility and development, and ensure that all employees feel they belong and are supported.

Skills and competencies can help leaders level the playing field, give employees the widest possible access to opportunities through mobility and development, and ensure that all employees feel they belong and are supported.

While it may not seem immediately obvious, using skills and competencies can be useful in DEIB efforts. Skills and competencies data can be used, for example, to identify biases that may exist in a company, inequities in salary and performance management structures, and outdated talent processes, among others.

For example, InterVarsity Christian Fellowship (IVCF) is a highly decentralized org. Its leaders noticed that employees were being evaluated differently across its varying locations, despite having the same roles and responsibilities. As a result, IVCF is introducing a competency framework to reduce this evaluation bias and ensure all employees are rated fairly.

From our research, we offer specific ways in which skills and competencies can play a role in DEIB (see Figure 4).

Performance management

Performance management (performance) was originally put into place to help orgs differentiate pay.³ While that original purpose hasn’t necessarily changed, it’s been supplemented. Orgs now see the performance process as continuous—as a way to mentor and coach, to facilitate ongoing feedback conversations, and to develop employees.

Skills and competencies support innovations in performance management—helping make it a continuous effort to mentor and coach, facilitate ongoing feedback conversations, and develop employees.

With this new mindset around performance come innovations—many of which involve competencies and skills. For example, some newer approaches (such as paying for skills) can help make the criteria used in performance decisions more transparent and objective. Skills, by describing what an employee can do, help with this objectivity.

Competencies, on the other hand, have long provided robust and defensible criteria for managers in many orgs to reference in their performance, promotion, and compensation decisions.

Figure 5 identifies ways in which skills and competencies can support performance.

Summing up

These 4 business challenges—employee development, career mobility, DEIB, and performance management—became persistent underlying themes in our conversations with leaders about skills and competencies. Leaders should continually ask how skills and competencies can both be used—in ways that make sense for the org and employees alike—to solve business challenges.

Orgs should use skills and competencies—not skills or competencies—to address business challenges.

From our research and participating leaders, the resounding agreement is that orgs should use skills and competencies—not skills or competencies—to address these challenges.

Use All of the Data

Within the skills conversation, a core theme is how to use skills data to solve business challenges, including the ones we previously listed, among others. Having more data (both broader and better) usually equates to having a more complete picture of the skills and knowledge an org has—and what’s still needed—to meet org goals.

As companies begin to consider skills and competencies, accounting for the data provided by both can help to inform the org’s strategies and decisions.

While there’s been near-frenzied discussions about skills data, orgs often overlook the information that competencies can provide. As companies begin to consider skills and competencies (basically, as 2 sides of the same coin), accounting for the data provided by both can help to inform the org’s strategies and decisions.

When, in the course of our research, we identified that skills and competencies can and should exist peacefully within the same org, we naturally assumed that the data from both would also peacefully meld together. That turned out not to be true in all cases, as illustrated by 2 stories from our roundtables:

• One org identified and partnered with a platform that allowed the consolidation of data from many sources. Having many sources of skills and competency data in one place, paired with AI and machine learning, allowed the company to both understand the skills and competencies it had—and infer abilities based on that information.
• Another org realized it could not, at least in the short term, effectively merge all its skills and competency data into one system due to technical limitations on its existing systems. So the company worked with different data sets to accomplish different things. For example: Skills data was mined by asking individuals to self-identify skills, and was used primarily to support individual employee development and career mobility. Competency data was gleaned from performance management systems and used primarily to support analysis at the functional level. While the data wasn’t combined together, identifying and understanding the data from the 2 sources still allowed the org to accomplish its goals.

Regardless of whether orgs consolidate all information into 1 system or use separate systems to service different aspects of skills / competency building, leaders in our study indicated they’re using several types of data. So, let’s talk about the sources of that data.

Data sources

Most orgs starting their skills journey often make the mistake of thinking of skills data in terms of what can be extracted from a skills platform (or a platform with skills functionality). While such platforms are a good place to start, orgs that focus solely on the data in 1 system tend to have a one-note view of their workforce’s abilities. Why? Most often, 1 system doesn’t account for more qualitative data or data provided in conjunction with competencies.

Orgs that focus solely on the data in one system tend to have a one-note view of their workforce’s abilities because one system doesn’t account for more qualitative data or data provided in conjunction with competencies.

Our research identified several sources that orgs currently plumb for skills and competencies data. Figure 7 shows these sources and their reliance on humans to gather the data. We explore this reliance on humans—from “active data sources” like talent profiles, which employees must complete specifically as part of a skills / competencies effort, to “passive data sources” like email and chat, through which employees generate skills / competencies data in the course of their normal work.

Aside from providing several sources that offer skills and competency data, Figure 7 also indicates whether the data can be collected and stored using technology, or whether it relies on humans. Several sources exist in the middle of the spectrum that, depending on the org’s tech savviness and willingness to invest, can use either tech or more manual methods.

Passive data

Increasingly, orgs use sources which yield data that doesn’t require a separate initiative: This data is created in the course of the org doing its business and the employees doing their jobs. We call this “passive data.”

While we think of HRIS / HCM systems as providing passive data, increasingly learning systems, productivity systems, and social media profiles and communication tools are being used as such data sources.

While we mostly think of HRIS / HCM systems as providing this type of data, increasingly learning systems (like LXPs), productivity systems (like Asana and Jira), and social media profiles and communication tools are being used as data sources for skills and competencies.

It’s relatively easy to extract and consolidate information from these systems: Vendors are getting much better at enabling them to talk to each other to provide real-time data. Having quantitative and qualitative data in 1 place typically allows orgs to do deeper analysis, including inferring skills or channeling data to other systems to help personalize learning or mobility for employees.

Active data sources

While not nearly as sexy, for decades, orgs have used other, more manual sources of data as well. This includes sources such as 360 evaluations, word-of-mouth referrals, surveys, and skills inventories. These, like their passive counterparts, offer all kinds of interesting data—but rely on humans to do the heavy lifting. This type of data almost always involves an initiative separate from work to gather it.

Active data sources offer all kinds of interesting data—but rely on humans to do the heavy lifting.

More and more, orgs are utilizing tech to minimize the human lift: For example, surveys are now online, which means they’re digitized, and easier to mix with other skills and competency data. Still, the lift is real. We look forward to seeing more solutions for passive data in the future, as some of the tech (e.g., natural language processing, listening, etc.) gets better.

One of the most commonly used methods of gathering skills and competencies data is to have employees fill out a talent profile. But getting lots of employees to fill out their profiles is no trivial matter. Collecting data in this manner works if employees are motivated to actually fill in their information—otherwise the system remains unused and unhelpful.

Some orgs launch a skills or competencies system with a massive push for all employees to complete their profiles. Others launch with little fanfare, like Cornell University in the following real-world story.

In Cornell’s case, employees immediately saw the value of the skills platform for their own development and engaged accordingly. The skills platform presented employees with a list of recommended skills to add to their profiles, from which they could choose the ones they found most applicable. The platform then made recommendations about networking and development opportunities that might help employees close the skills gaps they’d identified in their profile.

Other orgs have found that prepopulating the skills profile, and then asking employees to review and edit their profiles—rather than fill out a blank slate or choose from a list of recommendations—is easier for employees and gives better response rates. In all cases, leaders emphasized that it’s critical for employees to see how they’ll benefit personally from completing their profiles.

The challenges

Skills and competency data don’t necessarily have to be used together—and often technology prevents them from being used together. Some of the challenges leaders mentioned when dealing with skills and competencies data include:

• Inconsistent formats. Data formats from different technologies (dates in the U.S. vs dates in Europe, for example) make it difficult to align data.
• Many, many sources. Skills and competency data live in many places, making it difficult to consolidate and analyze all of it.
• Silos. We’ve talked with some orgs whose structures are so siloed that they can’t (or won’t) easily share information across boundaries, or they utilize incompatible systems that prevent an easy exchange of information.
• Residing in people’s heads only. Much of the information about activity that happens outside the walls of the org, including skills developed at home, on volunteer or services assignments, or in past roles, isn’t accounted for in any system.
• Paper. Some information about skills and competencies lives on paper in file cabinets in deep, dark parts of the org—and are hard to both find and use in that form.

Leaders emphasized the importance of thoughtfully setting up data collection systems to prevent issues associated with clunky, irrelevant, or unusable data.

Luckily, tech is increasingly able to help with these challenges. The middle of the data collection spectrum contains sources like job descriptions, performance evaluations, and job histories (see Figure 7). Many orgs rely on spreadsheets and manual entry to track skills and competencies based on these sources—leading to issues with data sharing, version control, and data siloing. But tech exists that can parse these documents to extract skills and competencies: This tech is getting better and more deeply integrated into many skills and competencies platforms.

Craft Clear Messaging

The final area we want to address in using both skills and competencies is crafting a clear message. As we mentioned at the beginning, the differences between skills and competencies may matter to those of us on the HR backend—but they often confuse leaders and employees on the frontend. In fact, one leader told us:

“What does your average consumer want? Whether it’s a people leader, an employee, or a prospective candidate, they just want to know what’s expected. They’re asking, ‘What do you need from me?’ Just give them the answer to that question in really plain language.”

VP Talent & Diversity, multinational media conglomerate

Unfortunately, in many orgs, the answer to the question, “What do you need from me?” is about as clear as mud. This lack of clarity creates fuzziness about expectations and messes with unity of purpose. As both skills and competencies are supposed to create clarity and provide a unified sense of purpose and direction, unclear messaging foils our efforts.

Unfortunately, in many orgs, the answer to the question, “What do you need from me?” is about as clear as mud—creating fuzziness about expectations and messing with unity of purpose.

To create clarity, leaders focused on 2 things:

• Consistent terminology. As we’ve discussed, the terms “skills” and “competencies” are inconsistently used in the literature and within orgs. Leaders can create clarity for employees by intentionally choosing, defining, and using consistent terminology to discuss questions of “What can employees do, and what do they need to be able to do?”
• Clear communication of expectations and benefits. Employees want to know how they should interact with skills and competencies systems—and, critically, how they’ll benefit from those interactions.

Regardless of the specific messaging content or terms chosen, leaders emphasized the importance of being clear and consistent: Make a decision and stick to the chosen message.

Leaders emphasized the importance of being clear and consistent—make a decision and stick to the chosen message.

Leaders also noted that clear communication about skills and competencies can create the buzz needed to help others in the org get onboard with a skills and competencies effort.

Choosing terminology to boost clarity

While we in HR know the purposes of skills and competencies, the distinctions between the 2 are of little consequence to most employees and managers. In most orgs, employees just want to know what they need to do. In these orgs, choosing terminology that makes it easy to talk about expectations becomes paramount, regardless of whether the terms “skills” or “competencies” are actually used—see the first and second examples in Figure 9 below.

In other orgs—for example, in an org in which competencies have been used for some time and skills are just being introduced—clearly distinguishing the terms generates more success. The third example inFigure 9 represents such an org.

The messaging strategy your org uses should be chosen with your workforce in mind.

In the examples listed in Figure 9, orgs reported that their chosen strategy reduced employee confusion—and increased employee acceptance of their skills and competencies systems. The strategy your org uses should be chosen with your workforce in mind.

Messaging expectations & benefits to employees

As we mentioned earlier, inaccurate or untimely data can sometimes do more harm than good. Given that much of the timely and accurate data is provided by employees themselves, orgs should also think about their messaging with respect to getting employees to input their data. To do this, leaders in our study strongly recommend that orgs get serious about consistently and clearly communicating 2 things:

• What is expected of employees. Employees want to know what systems are available for helping them track and develop skills and competencies, and how they should engage with those systems. The question they’re asking is: “What do you need me to do?”
• Benefits to employees. Equally important, employees need to know why and how they’ll benefit from engaging with these systems. The question they’re asking is: “What’s in it for me?”

Leaders emphasized the importance of communicating how employees should interact with systems that help track skills and competencies—and, critically, the benefits to employees of those interactions. Employees need to understand these systems—both how to use them and how those systems can potentially affect their lives.

Leaders emphasized the importance of communicating how employees should interact with systems that help track skills and competencies—and, critically, the benefits to employees.

Inputting data is the part of the process where leaders particularly emphasized clarity of expectations. What information should employees input? Why? Where? How? How often? Answering these questions clearly and consistently can go a long way toward getting the information that’s needed in the systems.

Answering the “Why?” question at both the org and employee levels turned out to be particularly important. Many times, employees fail to update their data in employee profiles, keep track of skills developed, or record recent projects completed—because they don’t understand the benefits of keeping those systems updated.

Employees need to understand that this data is being used by the org to make real decisions that can impact them.

Employees need to understand that this data is being used by the org to make real decisions that can impact them. These systems help the org create a more complete picture of their employees, what experiences they have, and what they can do. On a macro scale, this data is used to understand what skills should be developed and to make opportunities more transparent for everyone. On a micro scale, this data is used to make decisions about future roles and projects, opportunities for development, and even performance.

Often we see orgs invest a lot of money to implement systems that focus on skills and competencies—but fail to adequately or effectively market them. Orgs should make employees aware of these systems, set expectations for their use, and very clearly help them understand the benefits of using them.

How to best communicate the message

We started this research with the assumption that all orgs should stop trying to distinguish between skills and competencies. It’s a confusing and unhelpful effort, we thought, and orgs should create a unified message using language like, “What employees can do.”

The most important factor is clear and consistent terminology and messaging that highlights the benefits of skills and competencies for employees.

We discovered, however, that the picture is more nuanced: The most important factor is clear and consistent terminology and messaging that highlights the benefits of skills and competencies for employees. Specific messaging strategies differ based on org culture and employee familiarity with skills and competencies.

Wrap-Up

When we started this research, we, like many leaders out there, didn’t understand the differences between skills and competencies. We thought they were the same—or could be blended into one and the same thing. After careful research, we see a need for both skills and competencies, and the data they each provide. Each has a unique place in an org’s ecosystem.

We see a need for both skills and competencies, and the data they each provide—each has a unique place in an org’s ecosystem.

That said, we see a great need for orgs to do 3 things:

• Consider the strengths of skills and competencies, and use those strengths to solve business challenges.
• Consider the data skills and competencies offer. Use them appropriately, and find ways for technology and systems to use them together more.
• Craft simple, clear, consistent messaging that tells employees what’s expected of them and how they’ll benefit from skills and competencies.

We hope this discussion illuminates for you some of the ways orgs are defining and using skills and competencies—sometimes together, sometimes in parallel—to address their most pressing people challenges.

As always, we welcome dialogue! Please feel free to reach out to RedThread Research and tell us your experiences. Reach us at [email protected] and visit our website at redthreadresearch.com.

Appendix 1: Methodology

As the skills conversation transformed from a one-note debate about robots taking human jobs to a multifaceted exploration of “What can our workforce do now, and what do they need to be able to do in the future,” we noticed HR leaders grappling with skills and competencies, and were compelled to take a deeper look at how the 2 can work together toward org goals.

We launched our study in fall 2020. This report gathers and synthesizes findings from our research efforts, which included a lit review of 93 articles from business, trade, and popular literature sources; 2 roundtables with a total of 53 participants; and 6 in-depth interviews with learning leaders on their experience with skills and competencies.

For those looking for specific information from those efforts, you’re in luck: We have a policy of sharing as much information as possible throughout the research process. Please see these articles on our website:

• Skilling: 5 Themes in the Conversation
• Competencies vs. Skills: What’s the Difference?
• Skills & Competencies: Differences, Utility, & Messaging
• Skills & Competencies: Finding & Using Skills Data

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. Showed 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's 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 (see Figure 1¹) and why the number of DEIB job openings has skyrocketed (see Figure 2²).

The thing is this: Organizations can't just talk about DEIB and hire people to lead it. That's 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.

DEIB tech is no longer a brand new market—but still many have not heard of it. With that in mind, let’s do a quick review of where this market came from and why it's now ready to meet this moment.

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.³ 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 (105) 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.

Today, we’ve expanded the topic’s breadth to now span diversity, equity, inclusion, and belonging—increasing our coverage to 196 vendors (and counting!). And while we cover the market trends and changes extensively in this report, the complete list of all the vendors and the details around their capabilities are included in our online tool.

We believed in 2019 that tech may be the missing link which—along with a combination of strategies, goals, practices, policies, and behaviors—could bring about systemic changes for DEIB.

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

The rise of the Black Lives Matter (#BLM) movement in the U.S. and around the world has forced people to pay greater attention to issues surrounding racial diversity, equity, inclusion, and belonging. As a result, businesses are increasingly expected to take a stand on social justice issues, remain true to their values, and treat their workforce in an equitable manner.⁴

Many companies have responded by making pledges or promises in support of the #BLM movement.⁵  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 3 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.⁶

Orgs that are serious about implementing systemic change and seeking to achieve a lasting impact should look to DEIB tech for capabilities that enable them.

Specifically, DEIB tech can help:

• Improve the org’s understanding of and complexities surrounding DEIB
• Promote objective decision-making
• Flag and mitigate bias
• Ensure equal access to opportunities for all within the org
• Create transparency and accountability
• Scale DEIB efforts throughout the org

We believe that leaders must have a clear understanding of the DEIB tech available (internally and externally), and how it can help them achieve their business’s goals.

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 on by vendors
4. Guide leaders who may be looking to make tech investments

Key Findings

1. 3 major shifts punctuate the current DEIB tech market. To start, in 2017-2018, when the #MeToo movement was at its height, leaders were especially focused on gender; in 2020-21, the emphasis has evolved to include a focus on race and ethnicity. Next, and as a result of the first shift, the social justice movements and conversations around discriminatory workplace policies and behaviors have led to greater attention to inclusion than ever before. Finally, the role and impact of AI on mitigating bias to enhance DEIB has come front and center, and is being more readily addressed.
2. The broader HR tech world is responding to these market shifts. 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. We believe this reflects a growing need among organizations for HR tech solutions that incorporate a DEIB lens into all areas of talent.
3. The DEIB tech market is hotter than ever. The total number of vendors in the market increased by 87% as we identified a total of 196 vendors in the market for 2021, as compared with the 105 that we included in our research in 2019. The overall market size is $313 million, having grown at a CAGR of 59% since our last study in 2019.
4. People analytics for DEIB has arrived. Lack of analytics and insights on DEIB is the primary challenge that the majority of vendors are helping their customers solve for. Data and analytics are becoming more important for DEIB as organizations measure and track their efforts.⁷ As a result, a number of solutions providing DEIB analytics capabilities is growing (28% in 2021 vs 26% in 2019).
5. Smaller organizations and knowledge industries remain the main customers of DEIB tech. The largest customer category is small organizations (those with fewer than 1,000 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 employee range. As companies recover from the events of 2020, we expect to see orgs of all sizes increase their use of DEIB tech.

DEIB Tech: So Critical Now

Before we dive into the latest about DEIB tech, we need to establish a foundation here for some of the terms and concepts we use. We also offer a brief explanation of why DEIB tech is important to your organization.

Let’s take a step back and define our overall terms. Readers of our previous report will notice that we’ve evolved our terminology from “diversity and inclusion” (D&I) to “diversity, equity, inclusion, and belonging” (DEIB). The events of 2020 resulted in a focus on conversations around the workplace experiences of diverse and underrepresented people.

Specifically, they shed light on the uneven playing field that many individuals are faced with, as well as how it impacts their sense of belonging and being part of an organization. Due to this, we’ve seen a rise among both orgs and vendors that consider equity and belonging as part of their holistic understanding of this issue, and are including them as part of their programs and offerings.

What is DEIB?

Figure 3 features our definitions for the DEIB abbreviation—diversity, equity, inclusion, and belonging.

Now that we’ve defined the terms, it’s time to understand why DEIB is so important.

The great divide: Why is DEIB important NOW?

The events of 2020 have resulted in a sense of urgency and accelerated conversations about DEIB. And we’re seeing an unprecedented and greater willingness among leaders to engage and push for change. So, while cultural injustices have happened throughout our global history, why does there seem to be a greater push to change things now?

A key factor: Underrepresented people have been impacted disproportionately by the health and economic crises brought about by COVID-19—inequalities that have shined a discriminating spotlight on the many differences that continue to exist in our social structures.

For example: Job losses hit Black workers in far greater numbers than for Whites. Both Black men and women saw their unemployment rates go up to more than 16%, while White men saw theirs rise to a comparatively lower number of 12.8%, in April 2020.⁸ This gap didn’t improve once businesses reopened and companies began rehiring later in the year. While by August the unemployment rate for White workers was down to 7%, for Black workers it was much higher at 13% and the gap even larger.⁹

Additionally, as a result of the events of summer 2020, #BLM movement, and the following protests, many employees found themselves navigating difficult conversations around these issues at the workplace. Leaders, on their end, found themselves facing greater expectations to provide “safe spaces” for employees to do that, and have more open and honest discussions with them.¹⁰

Companies are under increasing pressure today to act on issues around discrimination and systemic racism. Leaders must seize this opportunity to make good on their claims and enable meaningful change to happen. And designing an overall approach to DEIB is a really good place to start.

Leveraging DEIB tech as part of an overall approach

Given the heightening expectations of DEIB that orgs are facing, leaders need to design a holistic approach to DEIB which includes all people practices and impacts all stakeholders. As we learned in our recent research,¹¹ when designing their new DEIB approach, orgs must do 6 key things:

1. Clarify their purpose or reason for doing it
2. Establish goals
3. Develop a strategy to meet those goals
4. Identify critical levers and activities that impact those goals
5. Leverage technology
6. Use data, analytics, and metrics to embed accountability and transparency

Technology forms a core part of a holistic DEIB approach. The next section explores what DEIB tech can offer. For more details on the other components of a holistic DEIB approach, please refer to our report, Diversity, Equity, Inclusion & Belonging: Creating A Holistic Approach For 2021.

What is DEIB tech?

When we talk about DEIB tech, we’re referring to …

… Enterprise software that provides insights, or alters processes or practices, at the individual or organizational level, in support of an organization’s efforts to become more diverse, equitable, and inclusive, and to enable belonging.

For the purpose of our ongoing research, we focus on tech that impacts decisions related to people. While there are other types of technology, such as those focusing on accessibility for people with a range of abilities and disabilities, these aren’t covered in our report as they don’t impact people decisions directly.

When we think about DEIB tech, we identify 3 types of vendors:

• DEIB focus vendors. The primary business for these vendors is helping orgs address their DEIB challenges. An example: a vendor whose product focuses only on reducing unconscious bias during hiring.
• DEIB feature vendors. These offer features or functionalities that cater specifically to DEIB needs, but their primary business focus includes more than DEIB. An example: a recruiting software vendor whose product can make all resume names / identifying info “blind” to minimize unconscious bias.
• DEIB friendly vendors. While these vendors neither address DEIB as their primary focus nor market themselves specifically as doing so, their included features or functionalities could positively impact such efforts in organizations. An example: a recruiting software vendor using AI to recommend appropriate candidates to hiring managers.

Essentially, DEIB tech should impact people decisions in a manner that helps orgs meet their DEIB goals. It should help transform fundamental and structural qualities of the systems that are in place in order to bring about lasting change. The key point here is that it must help drive systemic change in the organizations.

DEIB tech must impact people decisions by transforming fundamental and structural qualities of the systems in place in order to drive systemic change in the organization.

Some of the ways DEIB tech can do this is by:

• Uncovering existing policies, practices, and programs that may be biased, discriminatory (in reality, if not in design), or in conflict with the company strategy, and which need to be changed
• Identifying existing gaps between goals and the actions taken to meet them
• Measuring and tracking progress toward those goals
• Analyzing data and information for greater insights, and identifying areas of interest
• Making recommendations on next steps
• Scaling these efforts and the impact of these activities for the benefit of the entire organization

Now that we’ve covered the fundamentals around what DEIB tech is and why it’s important for orgs, let’s dive into this market.

State Of The DEIB TECH Market

Since we published our first report on the DEIB market, we’ve published 2 additional updates (here and here) that feature several new vendors as well as our overview on the market itself. In addition, regular conversations with vendors and users of these technologies allow us to keep a pulse on the DEIB tech market changes over time.

Four ongoing trends caught our attention and results from our recent vendor survey confirmed these findings. Overall, the DEIB tech market is:

1. Experiencing 3 big shifts in its approach to DEIB
2. Hot and growing with more vendors offering DEIB capabilities than ever before
3. Largely comprised of customers from small orgs and knowledge sector industries
4. Getting serious about analytics

Let’s examine these market trends in more detail.

3 big shifts

Our research and conversations reveal that the events of 2020 significantly impacted how organizations are thinking and approaching DEIB. Specifically, we find the following 3 big shifts that play a role in this market’s evolution:

1. Focus shift from gender to race
2. Stronger spotlight on inclusion
3. Impact and role of AI at the forefront

Focus shift from gender to race

The #MeToo movement in 2017-2018 brought conversations about sexual harassment and gender discrimination in the workplace under a spotlight. Similarly, the twin crises of COVID-19 and the social justice movements in 2020 highlighted discussions about workplace discrimination—with the focus now shifted from gender to race. The events of 2020 have had a disproportionately greater impact on diverse and underrepresented people. And, as conversations around DEIB have increased and demanded attention, there’s more emphasis around the issue of ending systemic racism.

Our interviews with DEIB leaders revealed a greater openness among orgs to have honest conversations about race than ever before: To a large extent, this is due to the expectations that people have. Eighty percent of the U.S. population want brands to help solve society’s problems, while 71% trust their employer to do what’s right on systemic racism and racial injustice.¹²

DEIB tech providers also noticed this shift. Our findings revealed that vendors:

• Added specific questions regarding race in their surveys and analytics
• Offer resources that cover issues about racial injustice
• Provide capabilities that allow users to measure and compare employee experiences through a race lens

A stronger spotlight on inclusion

As we mention in our report Diversity, Equity, Inclusion & Belonging: Creating A Holistic Approach For 2021, our research showed that the pandemic and #BLM movement led to an expansion of DEIB efforts by orgs. In particular, remote work, the disproportional effect of COVID-19 on certain populations, and uneven caregiving responsibilities all threatened to disrupt ongoing efforts to keep employees engaged and connected. Many organizations evolved their efforts to meet those challenges: Some revisited their policies and practices around employee lifecycles and updated them to meet these changing needs.

One such example comes from Ph.Creative, a brand agency that updated its strategy to better focus on inclusion.

Solution providers, too, have noticed this growing focus and are responding to it. For example, we’ve seen a significant rise in the number of vendors focused on employee engagement and development (43% in 2021 vs 31% in 2019). These activities, including employee experience, learning, career management, and wellbeing, drive and impact inclusion. Several vendors we spoke with shared that they’re offering products to help customers:

• Check the overall employee pulse and wellbeing
• Ensure continued engagement even in remote environments
• Enable flexibility to meet the differing needs of their workforce

Economic uncertainty caused by the pandemic also impacted this market. Budget cuts and low spending meant that talent acquisition (TA), and as a result diversity hiring, didn’t receive as much focus as it has in recent years. Organizations became more focused on retaining their existing workforce by ensuring they remain safe, engaged, and connected.

Finally, the racial injustice movements and conversations brought to the forefront that Black employees don’t feel a sense of inclusion or belonging at the workplace.¹³ People in general are more aware of a racial divide now as a result of the events of 2020: This has been instrumental in orgs realizing that they need to do more to ensure their diverse employees feel included.

Impact & role of AI at the forefront of DEIB

As the impact  and role of AI on DEIB has increasingly made news over the past few years,¹⁴ users as well as solution providers have been working to better understand the problems and address the resultant issues.

AI: The impact

While AI can identify and ferret out instances of existing bias in current systems and policies, it can also perpetuate it, for example, in job descriptions, hiring or promotion practices, or workplace communications. A main reason why: The data used to train algorithms is biased to begin with and, without correction, the algorithms simply replicate those biases. This can be due to such algorithms having been trained on a data sample that’s based on an over- or underrepresented population—thereby rewarding or penalizing other groups.

While AI can identify and ferret out instances of existing bias in current systems and policies, it can also perpetuate it.

Another big reason: The training data contains human biases and inequities reflective of those who created it. As a result, technology developers are increasingly adapting approaches that ensure the training data used for machine learning algorithms is free from human bias through stress testing and experimentation.¹⁵

AI: The role

While the impact of using biased algorithms has become clear, the role AI can play to mitigate existing biases has also received greater attention. The key point for users: The technology is used for the right problem and not seen as a cure-all.

For example, an AI interviewing software would be of little help to an org looking to increase its diverse candidate hiring if very few diverse candidates have been applying for roles to begin with. In this instance, the organization should consider why diverse candidates aren’t applying. It might be a sourcing problem. It might be a job description problem. It might be an employer brand problem. (There are tech solutions for all those problems.) Whatever the problem is, the AI interviewing software won’t help. The algorithm must be directed at the right problem.

In sum: 3 big shifts

These 3 shifts together can propose what may come as the DEIB tech market matures. They also offer hope that the words and pledges made by orgs in 2021 will be followed by respective actions as the understanding and focus around these 3 issues grow.

DEIB market growth

The market grew in 2 important ways in the last few years: both the number of vendors and market size as measured by revenue increased.

DEIB growth: Vendors

The overall number of vendors in the market (as identified by us) increased from 105 in 2019 to 196 in 2021. That’s an increase of 87%.

At first glance, you might think this increase may be due to the addition of new vendors. In fact, our research revealed, however, that many established vendors, not previously offering any DEIB functionality, have added new features / functionalities that customers can now use specifically for DEIB purposes. When we compared the total number of DEIB feature vendors in 2021 vs 2019, we saw an increase of 136%.

Our research revealed that 40% of vendors fall under our DEIB feature category in 2021, as compared with 30% in 2019. DEIB friendly vendors comprise a smaller percentage of the market than they did in 2019, while the percentage of DEIB focus vendors remained mostly unchanged at 32% (see Figure 7).

As shown in Figure 7, we believe these changes are a reflection of 2 interrelated developments.

• In the last few years, a large number of DEIB friendly vendors added or developed features that cater more specifically to DEIB needs—thus, they’re now counted as DEIB feature vendors.
• New vendors are finding more value in offering solutions with a DEIB lens embedded in their talent areas of focus, rather than only addressing specific DEIB challenges (i.e., an ONA or learning solution that’s able to provide insights on employee networks or learning, respectively, which can be broken down and analyzed by gender and race).

DEIB growth: Market

While many industries suffered setbacks with investments and contracts on hold during the pandemic, the DEIB tech market grew considerably. We had initially estimated the overall market size to be $100 million in 2018. However, our research this year turned up even more vendors that existed in 2018, so we have revised our 2018 overall market size to $124 million (see Figure 8). 

We estimate the overall market size to be $313 million, with a 2-year CAGR of 59% (and a 4-year CAGR of 82%) for the overall market. This growth is commendable, given 2020 was a year when almost all orgs looked to limit their spending and avoid unnecessary new investments.

We estimate the overall market size for DEIB technology market to be $313 million, with a 2-year CAGR of 59%.

Much of this growth was driven by the renewed calls for commitments to DEIB, once the #BLM movement gained momentum in the latter half of 2020. Given that we expect internal and external stakeholders to increasingly demand that orgs “walk the talk” in 2021, we expect demand (and thus market growth) to remain strong in the near future.

Customers of DEIB tech

When we looked at the customers of DEIB tech, two main findings caught our attention.

1. In general, small businesses comprise a greater percentage of DEIB tech than large orgs
2. Customers from technology, financial, and healthcare / life science industries have increased

Customer size

A real opportunity exists for the largest organizations to leverage DEIB tech. When we calculate the mean for customer sizes, we find that almost 30% of DEIB tech customers are small orgs with less than 1,000 employees. This is a lower number than in 2019 (see Figure 9) and likely represents a maturing of the market, since we see vendors increasingly selling to larger enterprises, notably organizations in the 10,000-50,000 employee range. That said, for the largest organizations—those with more than 50,000 employees—we haven't seen any notable movement in the percentage of them becoming DEIB customers.

This relatively low level of subscription to these technologies represents a real opportunity for the largest organizations because, as our research indicates, they're the ones which can use the help most, for 2 reasons:

1. Trust in large orgs is low. This is especially telling when compared with small businesses. A September 2020 Edelman study found that 43% of Americans trust large corporations to do the right thing in responding to issues of systemic racism and racial justice, as compared with 62% trusting small businesses. Corporations, in general, are believed to care less for their employees and share too little of their success with them.¹⁶ In addition, several recent instances of employers monitoring or tracking employee activity without their knowledge have appeared in the media.¹⁷ Employee fears of privacy invasion became more serious once the majority of the workforce shifted to remote work during the pandemic.¹⁸
2. High expectations exist for large orgs to do the right thing and take meaningful actions on DEIB. Seventy-seven percent of Americans state that it’s deeply important for companies to respond to racial injustice to earn or keep their trust.¹⁹ And while words matter, actions that lead to change matter even more. This was made clear when several leaders of large corporations received criticisms and backlash from consumers and media for their public stances in support of the #BLM movement: People saw them as stating empty words and pointed out the leaders’ failures to address discrimination within their own companies.

As the largest organizations look to put real money in 2021 behind the statements they made during #BLM, we expect to see them turn to tech more to help them address the systemic challenges they have with DEIB.

Industries

When we look at DEIB customers by industry, as expected, we see that technology and financial services / banking / insurance comprise an even larger portion of DEIB tech customers than they did in 2019 (see Figure 11). Also, customers from healthcare, pharmaceuticals, life science, and chemical industries increased by almost 3%. Although this may not seem like much, our conversations with vendors revealed a growing interest from these 4 industries.

Again, we believe the COVID-19 crisis played a role as it highlighted the need for organizations to support underrepresented and diverse groups, which comprise a significant percentage of healthcare workers.²⁰

Customers from the knowledge sector, including technology, financial, banking, and insurance industries, grew by almost 10% for each of them. This isn't too surprising as the technology industry tends to be more open to using tech to solve challenges. Also, given that the technology industry has been under the spotlight for its lack of progress when it comes to diversity in the recent years,^21,22 this is a welcome sign. Although DEIB tech is not a silver bullet, combined with a comprehensive strategy and practical goals, it can help enable continuous positive change.

Analytics takes centerstage

“ turn data into information, and information
into insight.”²³

This phrase is certainly gaining traction in the DEIB tech market. Over the past 2 years, we’ve noticed a growing emphasis on using analytics and insights to understand DEIB—and our survey findings confirm this. Fifty-two percent of vendors listed it as the primary challenge their solutions are helping customers solve in 2021, as compared with 33% in 2019 (see Figure 12).

52% of vendors listed analytics as the primary challenge their solutions are helping customers solve in 2021 (as compared with 33% in 2019).

As we mentioned in our recent report, Diversity, Equity, Inclusion & Belonging: Creating A Holistic Approach For 2021, identifying, analyzing, and democratizing DEIB data is becoming a critical focus among forward-thinking organizations. Leaders are now trying to:

• Understand the experiences of diverse populations
• Identify and understand networks among different groups
• Analyze these data for deeper insights
• Build greater accountability

In response, DEIB tech vendors are also building on their capabilities to help orgs enact and scale these efforts. Twenty-eight percent of vendors cater to analytics as a talent management area in 2021, as compared with 26% in 2019.

This brings us to our next section on the different areas of talent management that vendors target.

Talent Areas Vendors Focused On

The talent areas served by DEIB tech vendors have shifted considerably during the last 2 years (see Figure 13). As you may notice, the distribution is more evenly spread across the 4 talent categories today than it was previously. The biggest difference: The percentage of solutions that focus on talent acquisition, which declined to 29% in 2021 from 43% in 2019.

We believe this shift is due to at least 2 reasons:

• A significant number of (both new and old) vendors focused just on employees have introduced features that enable them to serve DEIB needs—thus, now making them a DEIB “feature” vendor, whereas, before, they may not have been in the market at all.
• The economic uncertainty brought on by COVID-19 has resulted in much lower levels of hiring, potentially decreasing the number of vendors focusing on DEIB in talent acquisition.

Let’s look at each of these talent areas in more detail.

Talent acquisition

About 30% of the 196 vendors identified in our research focus on talent acquisition (TA). Of those, 25 participated in our survey, with 60% of them offering solutions that help customers with candidate sourcing and selection (see Figure 14).

Readers of our previous report will note that we broadened our TA category this year to include new subcategories for onboarding, employment branding, and labor market analysis. This is because we noticed a rise in new capabilities and products among several vendors. Each of these subcategories have within them several areas that solutions focus on. For example, vendors under candidate selection offer capabilities that help customers create blind assessments, match diverse candidates to job descriptions, and / or help reduce bias during the selection processes. Similarly, a solution helping customers with sourcing candidates can do so by accessing diverse pools or changing job descriptions to reduce bias.

While we haven’t listed all of the different types of capabilities that vendors offer under each TA subcategory, readers can access a complete list of all TA vendors and find which capabilities they offer through our DEIB tech tool.

One of the ways DEIB technology can help customers improve their candidate selection process is by helping them match candidates to job descriptions, as we illustrate with the following story.

Development / advancement

The number of solutions that target development / advancement as a talent category significantly increased from 19% in 2019 to 26% in 2021. We believe this growth is due to the changing needs of the orgs. As we mentioned earlier, due to the shift to remote work and a slowdown in hiring new talent, orgs have shifted their focus to developing their existing workforce.

The largest subcategories within this area are leadership development (LD) and learning (L&D). Of the survey participant vendors that target development / advancement, 50% of them focus on these 2 subcategories (see Figure 16). New subcategories in this area for our 2021 study include recognition, talent mobility, and compensation / total rewards.

A significant finding this year is the number solutions that focus on LD. Readers of our previous report may recall this: Even though a big diversity challenge was representation at different levels of leadership, we identified only 16% of tech solutions that targeted this particular subcategory. In 2021, that number rose to 26%.

One of the ways DEIB tech vendors help organizations enable LD is by providing insights on leaders’ behaviors. The ability to provide insights on leadership behaviors and communication patterns became especially crucial once the pandemic hit and employees began working remotely. An example from McKesson, a healthcare company, provides an example of how important such insights can be.

Solutions can help customers in many ways under the different subcategories in this talent area, including:

• Orgs looking for vendors that help with L&D will find such capabilities as delivering training within existing employee workflows, offering virtual reality training, and helping design civil conversations.
• Vendors focused on mentorship and career management offer capabilities, such as enabling diverse talent to search for mentors, providing networking opportunities, or personalized career pathing.

For a full list of vendors that focus on development / advancement and the capabilities they offer, please visit our DEIB tech tool.

Engagement / retention

Seventeen percent of all DEIB tech vendors focus on engagement / retention. Of the survey participants that target this talent area, 75% are currently focused on 3 subcategories: employee experience, employee engagement, and employee voice. By employee voice, we mean how an employee communicates or speaks to the organization. (See Figure 17.)

New subcategories in this year’s study include employee wellbeing and employee engagement. We added employee engagement so that we could differentiate between solutions that help customers understand the unique experiences of employees and perceptions versus those that help customers with initiatives to improve employees’ engagement levels with their work.

Some of the newest additions in this category include:

• Capabilities that focus on employee voice, by allowing anonymous reporting and confidential conversations around sexual harassment.
• Vendors focused on employee experience to help customers understand diverse groups’ work experiences and to ask questions to better understand employee inclusion.

For a full list of vendors that focus on engagement / retention and the capabilities they offer, please visit our DEIB tech tool.

Analytics

As we mentioned earlier, analytics is a growing focus among DEIB tech providers. Of the survey participants which selected analytics as a talent area of focus, 57% offer capabilities for analysis and monitoring of DEIB activities by conducting representation / KPI analyses, enabling pay equity analyses, assessing network inclusion, analyzing TA processes, and providing DEIB dashboards (see Figure 18).

Our survey also revealed that the number of solutions helping customers calculate the business case for D&I initiatives rose significantly to 30% in 2021 from 17% in 2019. This is most likely due to a growing need for DEIB leaders to quantify the impact of DEIB on business, and show the value of their initiatives and investments by tying them clearly to business outcomes.

The number of solutions that conduct ERG management and analysis also increased slightly to 13% in 2021 from 10% in 2019.

The number of solutions helping customers calculate the business case for D&I initiatives rose 13%, from 17% in 2019 to 30% in 2021.

For a full list of vendors that focus on analytics and the capabilities they offer, please visit our DEIB tech tool.

Moving forward, we expect that DEIB tech vendors will continue to improve their capabilities while also growing and developing new ones—to meet the unique and changing needs of the market. Buyers and potential investors need to be aware of these capabilities and use the success stories from other forward-thinking organizations to understand how to leverage these technologies for their own purposes. Additionally, other equally important considerations exist for you to keep in mind before investing in DEIB tech.

In our next section, we cover some of the crucial considerations that potential buyers should be aware of.

What Buyers Should Consider Before Investing

While it’s important to understand the market and the different talent areas of focus, leaders interested in DEIB tech must keep a few critical considerations in mind before making any investments:

• Be aware of the benefits and the risks of using DEIB tech
• Be clear about your own needs
• Audit existing in-house tech that can potentially be leveraged for DEIB purposes

Understand the benefits & risks of using DEIB tech

Organizations must be aware of both the benefits and risks associated with DEIB tech before purchasing it (see Figure 20).

Identify your organization’s needs

Once the benefits and risks are understood, DEIB leaders must reflect on their organization’s needs. As a DEIB leader, you can do this by:

• Understanding your organization’s DEIB journey
• Identifying if the vendor can meet your needs for support
• Determining whether any additional services besides the tech may be required

Your organization’s need for a particular type of tech will depend to some extent on:

• Where you are in your DEIB journey
• What your level of understanding of DEIB issues is
• What your specific goals are

Different leaders and organizations are at various stages in their journey to understand and embrace DEIB. When it comes to selecting DEIB tech, orgs first need to be clear on what they want to accomplish, where they currently stand, and what remains to be done.

“The tool allows everyone to begin their DEIB’s learning journey from where they are—curated content is delivered in weekly snippets that don't feel overwhelming.”

A small technology company for a DEIB focus vendor

Another critical factor to take into account is the amount of support your organization might need from the vendor. One way to gauge if the vendor can meet your needs is by looking at the vendor’s size and whether it has the in-house expertise needed.

Currently, most vendors are relatively small, with almost 70% employing fewer than 50 people (see Figure 21). These small vendors might be better suited for organizations with less complex needs (e.g., smaller, limited number of locations / geographies). For orgs with global operations looking to roll out initiatives on a wider scale, larger vendors might be better able to meet your needs. That said, vendor size is clearly not a direct determinant of capability, so it's critical to fully understand the vendor’s offerings.

“ Still very small team—needs more manpower—is not a global solution.”

A midsize financial company for a DEIB focus vendor

Your organization may also require additional expertise or services beyond tech, such as consulting services, or access to resources or communities. From our survey, 42% of vendors offer additional services beyond their tech (see Figure 22). Orgs just starting on their DEIB journey can leverage such solutions to better understand the complexities of the issues around DEIB or to seek additional customer support if needed.

Of the 42% of vendors which provide additional services, about one-third offer services for the assessment and diagnosis of your current state and D&I maturity (see Figure 23). These solutions can be leveraged by orgs looking to expand or reenergize their DEIB efforts, and are in need of insights on where they currently stand.

Almost 30% of those which provide additional services, offer training and resources around D&I learning, which can be of particular use to those looking to solve challenges like unconscious bias. About 40% of vendors help customers manage companywide efforts around DEIB or can help you develop a strategy—ideal for orgs that are just beginning on their DEIB journey and need some extra support (See Figure 23).

“ is a great way to assess where a company stands in their D&I understanding, commitment and strategy, and provides the feature to track and measure D&I activities to develop a roadmap to achieve the desired outcomes to support the organization's goals and objectives.”

A small professional services company for a DEIB focus vendor

In the following checklist, we offer some key questions to help you better understand your organization’s needs. Use these questions as a checklist when beginning your DEIB tech selection to determine where you currently stand regarding your DEIB needs and to kick start your discussions on technology selection.

Auditing in-house tech

As we mentioned earlier, many vendors have added DEIB features to their products in the last 2 years. Given this development, your organization may already have some capability in this area. Thus, your org may already have a “feature” or “friendly” technology that can be leveraged for DEIB purposes.

Your organization may already have a “feature” or “friendly” technology in-house that can be leveraged for DEIB purposes.

For example, some of the new vendors in our study are people analytics tech solutions that have developed DEIB features—allowing users to analyze different cohorts, genders, or groups of employees to understand their levels of engagement, development, and overall experience. Orgs with existing people analytics solutions may find such capabilities embedded in the technology.

Another example of existing tech that has developed DEIB features is HRIS / HCM tech solutions, such as Workday, SAP, and ADP:

• In 2020, Workday launched its Value Inclusion, Belonging, and Equity (VIBE) Central, a dashboard that brings together a company's diversity and inclusion data, best practices content, and reporting. The company also launched the VIBE Index, a metric that allows users to gauge their performance.²⁷
• SAP (via SuccessFactors) offers users the capability to monitor recruitment and management position data for women and underrepresented people, attrition and retention rates, and supplier diversity statistics.
• ADP offers a pay equity tool within its HCM suites.

The following checklist includes a few key questions to consider when auditing existing in-house technology. Compare your results with the list of available tech in the market to help you narrow your choices.

What’s Next

Given the findings from our study, we offer a few trends that we expect to see in the coming 12-18 months.

1. Continued integration of DEIB tech into all areas of talent
We expect to see more HR tech vendors add DEIB features / functionalities to their solutions and, thus, address a wider range of talent areas. And, while we did see a shift away from a heavy focus on TA and toward more solutions addressing more areas, we expect to see this trend continue and grow. Moving forward, more orgs will be looking to address all talent management activities, such as recognition, performance management, and talent mobility, through a DEIB lens.

2. More focus on inclusion and belonging
Recent research reveals that 52% of people choose culture as the primary reason to work at a company.²⁸ The recent addition of D&I ratings and demographic information for companies on Glassdoor also reflects the growing importance that job seekers place on these issues when considering new roles. We expect to see more orgs leverage DEIB tech to measure and improve their inclusion and belonging.

3. Greater expectations to drive DEIB actions
As orgs feel the pressure to take a stand, and act against systemic racism and gender discrimination, they’ll no longer be satisfied with technologies that only go so far as providing data on the current state of DEIB and identifying gaps. DEIB tech must be able to:

• Make recommendations, and highlight and prioritize specific actions for leaders
• Connect these actions to business outcomes
• Offer scenarios for how it may impact the org if those actions aren’t implemented

4. More accountability and transparency at all levels
Related to the point on actionability, we also expect to see tech drive greater accountability and ownership for DEIB at both the individual and organizational levels. Democratization of insights on actions around DEIB can encourage individual employees and leaders to take greater responsibility and ownership to monitor and change their behaviors accordingly. Tech can help employees and leaders understand how their daily actions may affect DEIB outcomes and make appropriate recommendations.

Conclusion

The events of 2020 have shifted the emphasis for organizations to act on DEIB from “need to do in the near future” to “need to do it right now.” The call for orgs to act on these issues and the urgency to show results have never been greater. The tech market is responding to these changes, as is evident from the growing DEIB market and capabilities: It’s time for organizations to step up and do their part, too.

DEIB tech can play a crucial role in helping org move the needle, provided it's leveraged thoughtfully. Today's buyer has more tech choices than ever before, which also comes with greater associated risks. However, leaders must remember that DEIB tech is only one part of the entire process—and, without proper alignment with the overall purpose, a comprehensive strategy, and a degree of accountability and transparency, technology in itself won't be able to bring about any lasting or meaningful change.

Appendix 1: Methodology

We launched our study in summer 2020, with a vendor survey that ran from June-August 2020. A total of 45 vendors completed our survey: One vendor offers 2 DEIB-focused solutions and another vendor offers 3 solutions—thereby, bringing the total number of solutions in our study to 48.

Once we collected the data, we reached out to vendors for reviews, clarifications, and to collect any missing data. We combined this with publicly available data on vendors that we found through our own research, bringing the total number of identified vendors to 196. We conducted our analysis in November 2020 and the report was written during December 2020-January 2021.

For this report, we added a customer poll, so that we could better understand the challenges and areas that DEIB tech is being used for, and user satisfaction levels with the vendors. We also created a robust evergreen DEIB tech tool, which serves as the repository of vendor-specific information. This new tool includes updated data and info on every vendor that participated in the research, including their capabilities and customer NPS scores.

Vendor Demographics

The majority of vendors (80%) that participated in our study have their headquarters in North America. Of the remaining, 16% are based in Europe, and 4% in Asia-Pacific or Australia (see Figure 24).

In 2021, the majority of investments in DEIB tech came from 5 industries—technology, financial / banking / insurance, healthcare, professional services, and pharmaceutical / chemical / life sciences (see Figure 25).

 

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].

 

 

When we published our 2019 People Analytics Tech (PAT) study at the very end of last year, we thought we had a strong sense of what was coming in the next year. Like everyone else, we were wrong.

COVID-19 and the social justice movements of 2020 dramatically changed all of our lives. As a result, business leaders wanted to understand what was happening with their people on a much deeper level. People analytics teams and their technology had an unexpected opportunity to shine.

Some teams and technologies seized that opportunity. Those who fared the best had already invested in regular employee listening strategies, democratized data analytics products for the broader organization, and created a flexible and integrated tech stack.

Other teams had to perform heroic acts to get leaders the information they needed. As the crisis of the moment turned into the reality of the year, they began to explore new approaches to deliver people insights at scale.

All of this brings us to now, when many people analytics leaders are looking to 2021, beginning to contemplate new investments, but have less time than ever to think about it.

That’s where our new research on people analytics tech comes in. Our goal is to help people analytics leaders – whether you are in the more prepared group or the heroic acts camp – prepare for next year. Specifically, we focus on 3 questions:

• How did the people analytics tech vendor market change in 2020?
• What are the newest capabilities you need to know about?
• What should you be thinking about when making (or expanding) a people analytics tech investment?

Study overview

This study has the same overall goal as our 2019 study: To make the people analytics technology market more understandable for people analytics practitioners (PAPs) as well as vendors.

Our overall methodology is similar to last year (see Figure 1). We administered a robust vendor survey (June–August) and conducted 60-90-minute vendor briefings (July–November). We made a few additions this year, too:

• We added a customer poll, so we could better understand people analytics leaders’ perspectives on their vendors’ offerings—this included a customer Net Promoter Score® (NPS)
• We asked each vendor for an opportunity to see their sandbox environment, so we could get a better sense of their product

Figure 1: Methodology for 2020 PAT study | Source: RedThread Research, 2020.

We also created a robust evergreen tool, which serves as the repository of vendor-specific information (a lot more information on this below!). This new tool includes an updated RedThread assessment on every vendor, customer NPS and other customer insights (when there were enough responses), screenshots, and case studies. That allows this report just to focus on the overall market.

Key findings

The study is broken into three areas: market changes, vendor capabilities, and considerations for making (or expanding) PAT investments. That said, the overall top five findings are below:

1. The people analytics tech market responded to customers’ 2020 needs. The events of 2020 required companies to foster connectedness and keep their employees engaged, secure, and safe. The majority of solutions in our study reported employee engagement, experience, and diversity, equity, inclusion, and belonging (DEIB) as their primary areas of focus this year.
2. Practitioners have more choices of technology than ever. We identified 121 people analytics technologies (PAT) on the market today. The market overall is growing quickly, with a 35% growth rate between 2019 and 2020, and a 55% CAGR for the last four years. We estimate the overall market value at $2 billion.
3. People analytics practitioners and HR teams are the key users today. This year, 96% of vendors said people analytics practitioners (PAPs) are their primary audience, compared to 77% last year. HR business partners (HRBPs) were the next critical audience, cited as primary by 70% of vendors. Most solutions offer targeted insights and resources to help these two audiences use their solution effectively. However, the majority of vendors anticipate that HRBPs and people managers will be using their solutions more frequently in the next 3 years.
4. Many solutions are not as easy to use or user-friendly as vendors believe them to be. For customers, ease of use and simplicity is a big differentiator. Given the high number of vendors who claim this is a differentiator – and the number of customers who claim they are still seeking it – we don’t think that most vendors actually differentiate on this capability.
5. New capabilities include advanced NLP, deep machine learning, and the use of new, unstructured data. Some of the most interesting new capabilities include context-configurable natural language processing (NLP), use of deep machine learning to analyze unstructured data (e.g., voice, images, video), and the collection of that unstructured data.

The People Analytics Tech Market Solution Matrix

In this research, we attempt to provide a foundational understanding of the market and where the different vendors fit within it. To do this, like last year, we mapped all of the vendors in the study on our People Analytics Tech Market Solution Matrix (see Figure 9). We also call it our 2×2 matrix. But please remember, unlike some other analysts’ 2x2s, up and to the right is NOT better. The different boxes all have their own strengths.

To understand the market, we compare two aspects of vendors’ capabilities: usage frequency and data sources. This approach allows us to clarify if, on the X-axis, the analysis is primarily used for strategic organizational decisions (frequent analysis) or informing individuals about themselves / their teams (continuous analysis). It also helps us see, on the Y-axis, the number of data sources integrated, which can give us a sense of the integration complexity. You can see here for more details on the different axes and how we categorize vendors.

When we compare last year’s and this year’s studies, we notice a few things:

• Compressing toward the X-axis. More vendors than before are both creating and integrating data––meaning we have more vendors in the center of the matrix
• Moving to the right on the X-axis. More vendors are making data continuously available and increasingly accessible to more user types (e.g., business leaders / C-suite, people managers, and employees)––meaning more vendors moved to the right side of our matrix this year
• Fragmenting of vendor categories. Last year, we were able to reasonably and clearly group vendor categories (e.g., employee engagement / experience or workforce planning platforms) by their location on the matrix; this year, given some of the shifts mentioned above, we find them somewhat more fragmented––meaning there’s more differentiation between the vendors within a given category

Figure 2: People Analytics Tech Market Solution Matrix | Source: RedThread Research, 2020.

Check out the full study and tool

The full study has lots more information than what we’ve detailed here, including customer quotes, overall customer NPS scores, and checklists for both vendors and people analytics practitioners to get started.

As you may know, we recently launched our paid membership, and the full study is available only to study participants and paid members. You can also access the study on the websites of PAFOW and Insight222, as they were generous enough to sponsor this research.

In addition, we encourage you to check out the brand new, fully redesigned People Analytics Tech tool, which is available both to members and non-members (the tool will also be available on the websites of PAFOW and Insight222). You can filter on a wide range of factors, such as analysis type, capabilities, customer NPS©, customer size served, primary talent area of focus, top 3 industries served, and primary users (see Figure 3).

 

Figure 3: PAT Tool, Example of Filtering Capabilities | Source: RedThread Research, 2020.

Once you click on a vendor, you will be taken to an overview tab, which provides our RedThread assessment, vendor details, and customer feedback (see Figure X). Members can also access additional insights, screenshots, and case studies.

Figure 4: PAT Tool, Example of Overview Page | Source: RedThread Research, 2020.

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 is a labor of love, in that it reflects 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].

People Analytics Tech: The Vendors, RedThread Research / Stacia Garr and Priyanka Mehrotra, 2019. https://redthreadresearch.com/pat-thevendors/ and People Analytics Tech: The Market, RedThread Research / Stacia Garr and Priyanka Mehrotra, 2019. https://redthreadresearch.com/pat-themarket/

 

In 2020, due to the COVID-19 pandemic and the social justice movements, people analytics had an unexpected opportunity to shine. Technology played a more important role than before as people analytics team looked for ways to scale and provide deeper insights to leaders on their workforce, the majority of whom were working remotely. Our goal is to help people analytics leaders succeed in that endeavor and prepare for 2021.

Through this research, we wanted to understand:

• How did the people analytics tech vendor market change in 2020?
• What are the newest capabilities leaders need to know about?
• What should leaders be thinking about when making (or expanding) a people analytics tech investment?

This study is a culmination of nearly a year of qualitative and quantitative research, that included an online poll, a vendor survey, a customer poll, and over 40 vendor briefings and demos. This flipbook highlights the changes and trends from this year, the different capabilities offered by the vendors, and the questions potential technology buyers should consider before making or expanding their tech investments. We also suggest readers check our interactive, evergreen people analytics tech tool, for current vendor information.

2020 was not easy for anyone, but it had an especially significant impact on diverse people. As leaders look to 2021, they have an opportunity to revisit their diversity, equity, inclusion, and belonging (DEIB) strategy. Through this research, we wanted to understand: 

• How have the events of 2020 have affected organizations’ approaches to DEIB? 
• What steps or actions must leaders take moving ahead? 

In this study, we review the specific areas leaders should focus on when revisiting or developing their DEIB strategy. We also review 3 major trends we believe will impact DEIB next year and which leaders should take into account when crafting their strategy.

Our study is based on a review of more than 50 articles, and interviews with 10 DEIB leaders and 20 HR leaders over the course of September – November 2020. This flipbook explores the fundamental shifts we have noticed this year, guides leaders on how to develop a holistic approach to DEIB and offers insights into some trends for 2021. 

Introduction

The conversation about skills has exploded in the past year from an almost hypothetical discussion about how to plan for digital transformation to a very real one in which hard decisions have had to be made about what skills were needed to keep businesses intact.

As organizations pivot to different ways of working, it will be even more important that they have a good understanding of the skills and knowledge employees have now, and the skills the organization will need in the future.

As part of our ongoing research on skills, we are focusing our first study on a question we have heard a lot:

What is the difference between skills and competencies, and why does it matter?

What we saw in the literature

To answer that question, we began with a review of the competencies literature. Four themes emerged in response to this question:

1. Definitional Chaos. There is little agreement about the definitions of “skills” and “competencies.”
2. Agreement on Goals and Benefits. There is considerable agreement about the goals and benefits of any skills or competencies effort.
3. Competencies Support Performance Management. In some parts of the literature – mainly written for HR audiences – competencies are clearly linked to how a job is performed.
4. Skills Leverage Tech. Organizations derive practical value from skills platforms that leverage huge amounts of data.

Definitional chaos

There is very little agreement in the literature about the definitions of “skills” and “competencies.” In some articles, the terms are used interchangeably. In others, skills are listed as one component of competencies – for example, “a competency is a measurable pattern of knowledge, skills, abilities, behaviors, and other characteristics.”¹

Often a distinction is made in the granularity of skills vs. competencies, with skills being more granular – although one article suggested the opposite.² Sometimes competencies are contextualized for a specific job or role (more on this below). The definitions and distinctions vary widely from author to author and audience to audience.

To further confuse the matter, when we compared skills databases to competency models many of the same terms showed up in both places. For example, the U.S. Office of Personnel Management’s MOSAIC Competencies framework and the U.S. Department of Labor-sponsored Career OneStop Skills Matcher tool both list items like, “Accounting,” “Client Engagement/Change Management,” and “Project Management.” OPM calls these items competencies; DOL calls them skills.

The same confusion plays out in the private sector. Some excellent vendors focus on skills; others on competencies – but if you look at their databases and lists of terms, there is considerable overlap.³

Agreement on goals and benefits

Given how inconsistently the terms “skills” and “competencies” are used, there is surprising agreement in the literature on the ultimate goal of a skills or competency effort: Organizations need to be able to identify what they (and their people) can do now and what they must be able to do in the future. They need to be able to use that information to plan and prepare for the future – to align talent with business goals. Job-seekers (internal and external) need to understand what’s expected of them and what they are good at vs. what organizations need them to be good at.⁴

Both competency models and skills frameworks attempt to facilitate these discovery and planning processes.

There is also agreement on the benefits of skills frameworks and competency models. Organizations can use skills and/or competencies to:

• Use the same terminology to talk about what employees should be able to do
• Understand what employees can do vs. what they need to be able to do
• Fill key positions quickly and effectively
• Target employee development to close key gaps
• Help employees understand their gaps and options⁵

Most of the literature also agrees that there is no standard, universal set of skills or competencies that all organizations need. Organizations need to identify their competitive advantage, then tailor the models they are using to focus on the key skills/competencies that drive that advantage.

Competencies support performance management

In some of the literature, competencies were clearly linked to the performance of specific jobs or roles. In these cases, skills specified what a person can do, whereas competencies specified not only what but how the task or activity should be accomplished.⁶ They answered questions like, “How does an individual perform this job successfully?” and “How does an individual behave in the workplace to achieve a desired result?”⁷

This part of the literature is particularly helpful for leaders concerned with performance management, as it provides standards against which to measure behaviors and results. Skills tend to be decoupled from the performance of any specific job, making skills frameworks less relevant to performance management.

Skills leverage tech

Skills databases and competency frameworks are built and managed very differently. Developing a competency framework tends to be a top-down exercise run by a few people in the organization. It often involves intensive human effort to complete observations, job analyses, interviews, surveys, and document reviews.⁸

By contrast, skills databases tend to be built from the bottom up, using advanced computing power to glean skills information from job postings, resumes, HR repositories, and other data sources.⁹

Because they leverage technology to pull in and leverage massive amounts of information about employees, skills offerings tend to provide users with tens of thousands of skills options to choose from. This huge menu of options allows users to be far more granular in choosing and describing what they can do. This granularity lends flexibility and transferability, as it is easier to see how a particular skill might apply in different functional areas or organizations.

Thoughts on the topic

Regardless of terminology, we see enormous potential for vendors that help organizations answer the question, “what can we do, and what do we need to be able to do?” using the massive amounts of data now available about employees and their abilities.

Tech solutions have made it possible for many more organizations to start answering this question by automating many of the processes involved. The pace of change in today’s world will only increase the demand for organizations to maintain a very up-to-date understanding of what they can do and what they need to do. Any tech or methods that can shine a light on this question will bring huge value in the near, medium, and long term.

What caught our attention:

Of the literature we reviewed, several sources stood out to us. Each contained information that we found useful and/or intriguing. Although much of the competencies literature was written 5-10 years ago, it is particularly helpful to review in light of the question, “what’s the difference between skills and competencies?” Interestingly, many of the more recent articles on competencies were primarily written by vendors trying to clarify how their competency offerings fit in the skills marketplace.¹⁰ We learned from these perspectives and encourage you to do the same.

Policy, Data, Oversight: Assessment & Selection – Competencies

United States Office of Personnel Management  |  opm.gov, 2020

“Competencies specify the "how" of performing job tasks, or what the person needs to do the job successfully.”

 Highlights:

• OPM’s Multipurpose Occupational Systems Analysis Inventory (MOSAIC) methodology for collecting occupational information has been used to build one of the most comprehensive competency databases available, covering over 200 U.S. federal government occupations.
• The MOSAIC information has been used to develop competency models for a range of occupations, including cybersecurity, grants management, IT program management, and executive leadership.
• All MOSAIC information is available in downloadable Excel spreadsheets or PDFs for public use.

How Ericsson aligned its people with its transformation strategy

Simon London and Bina Chaurasia  |  McKinsey & Company, Jan 2016

“[W]e literally took every single function in the company and all of its roles, mapped out the stages of each job, and laid out the competence needed for each one. That took a couple years.”

 Highlights:

• A major shift in strategy led telecom giant Ericsson to change skills, technology, and processes on a global scale.
• This shift also required an overhaul of the HR team, strategy, and processes.
• The company completed a massive, years-long competency modeling exercise but reports that now every position in the company is mapped out.

The essential components of a successful L&D strategy

Jacqueline Brassey, Lisa Christensen, and Nick van Dam  |  McKinsey & Company, February 2019

“At the heart of this process is a comprehensive competency or capability model based on the organization’s strategic direction.”

Highlights:

• This article puts competency management in the context of L&D’s responsibility to develop employees in line with organizational strategy and goals.
• Once a strategic direction is set for the organization, it is critical to verify whether employees are equipped to deliver on that strategy.
• To make this verification, this article recommends taking a deliberate, systematic approach to capability assessment, starting with a comprehensive competency model.

What’s the Difference Between Skills and Competencies?

Sarah Beckett  |  HRSG, March 2018

“In some ways, a skill and a competency are similar. On a basic level, they both identify an ability that an individual has acquired through training and experience.”

Highlights:

• • Skills define “what” an individual can do. Competencies define “how” they perform a job successfully.
  • Competencies = Skills + Knowledge + Abilities
  • Competencies improve HR processes by introducing consistency, visibility, structure, progression and coordination.
  • Competency management software solutions can ease much of the burden of using competencies to define job success.

Additional readings

1. “Competency Frameworks: Core Competencies & Soft Skills,” Randstad, 2019.
2. "Hard Skills vs. Soft Skills," Indeed, 2020.
3. "Return on Leadership – Competencies that Generate Growth," Egon Zehnder International and McKinsey & Company, 2011.
4. O*Net Resource Center, O*Net, 2010.
5. "Competency Management at Its Most Competent," Deloitte and DDI, 2015.

In the face of a global pandemic, a critical social justice movement, and significant natural disasters, we’ve all done our best to manage our workloads, our employees, our home lives, our finances, and our health. As in all situations, some folks have done it better than others.

We wanted to understand what responsive managers and organizations did in the last 6 months – and how those practices are different from before the pandemic. But even more importantly, we wanted to understand:

• What types of management practices do the most effective managers use?
• How has HR supported those most effective managers?
• What lessons can we take from this as we design our organizations and support our managers while moving into 2021?

This research is a culmination of more than a year of research, with new survey data collected and interviews conducted in September and October 2020, to ensure a focus on the manager and organizational behaviors critical to the events of 2020.

This report summarizes the collective knowledge of over 30 learning leaders, providing an in-depth discussion about the rise of the learning tech ecosystem.

Specifically, it provides:

• A framework for thinking through ecosystem functionalities
• 6 complete example case studies, complete with learning tech ecosystem diagrams
• Examples of structures and characteristics of companies that generally subscribe to them
• Best advice from leaders for creating ecosystems

Click the graphic below to access the PDF version of this report.