Events

Why We Care

Last year, in the aftermath of the social justice protests, many organizations made significant pledges to alter hiring and promotion practices to create greater equity and opportunity for people from diverse backgrounds. For example:

• Adidas said it would fill at least 30% of all open positions at Adidas and Reebok with Black or Latinx candidates
• Estee Lauder promised to reach U.S. population parity for Black employees for all levels in the next 5 years
• Facebook pledged to double the number of Black and Latinx employees by 2023

In the last few months, we’ve also seen an increasing number of diversity and inclusion reports published from firms, such as Deloitte, PWC and others, promising increased transparency and focus on this topic. There have also been announcements by companies such as Nike, Chipotle, McDonald’s, Google, and others, tying executive compensation to hitting diversity goals, underscoring the importance these firms are putting on DEIB.

This Might All Sound Familiar

As you might recall, in the mid-2010s we heard similar pledges (and saw the publishing of diversity reports) from Google, Facebook, and Apple, after women such as Tracy Chao and investor Ellen Pao brought attention to Silicon Valley’s diversity problems. And, to their credit, most of those companies (Apple being the exception) are continuing to publish those reports.

Those reports have revealed—surprise, surprise (or not)—that making progress on diversity representation is a slow and uneven business. For example, Facebook, which has one of the better public diversity reports, has improved its percentage of women from 31% to 37%—and from 15% to 24% for technical roles—from 2014 through 2020. However, they have only improved the percentage of Black employees from 2% to 4%—and from 1% to 1.7% in technical roles—across that same period.

This slow pace has not gone unnoticed, as commentators from all stripes (but most notably the mainstream press) have regularly flogged those companies for not making as much progress as we all want. As one commentator mentioned,

“These companies are data-driven, but if people are not hitting their diversity metrics, where’s the downside? You have metrics, but no consequences.” —Bari Williams, head of legal, at start-up Human Interest

It would be easy for leaders to conclude that they’re “damned if they do” track / publish data and “damned if they don’t” (because they don’t have data to understand what’s happening). When you combine this situation with the potential legal consequences of diversity (and inclusion) data, you end up with a whole lot of inaction—which is what we’ve generally seen to date.

This Time Is (Likely) Different

But this inaction is untenable for at least a few reasons:

1. Consumers want companies to take action—and will reward them if they do. According to the Edelman Trust Barometer, 80% of Americans want brands to help solve society’s problems and 64% want companies to set an example of diversity within their organizations. Further, corporations that take a stand on racism are shown as being 4.5 times more likely to earn / keep consumers’ trust and those doing well with addressing racial issues are 3 times more trusted. Brands’ responses to racism also influence purchase intent. 

To capture the potential goodwill of consumers, though, companies must show that they’ve acted or made progress on DEIB¹ —and the way to do that is through DEIB metrics and analytics.

2. Diverse employees left the workforce during the pandemic—and companies have to figure out how to get them back. Diverse people have borne the brunt of the pandemic:
   1. Women left the workplace at the steepest, most sustained level since World War II
   2. Black and Latinx workers suffered from higher levels of job losses, as reflected by their unemployment rates for February 2021 which were at 9.9% and 8.5%, respectively—as compared with 5.6% for White employees
   3. More than a million people with disabilities lost their jobs during the pandemic

As we all look to a post-pandemic world, there’s a good chance we will see at least two things: significant movement of talent (who may have stayed due to economic uncertainties, but now see a chance to jump) and a strong economy. To effectively take advantage of both of these changes, organizations will need to foster DEIB to both attract newly available talent (and retain existing talent) and to leverage the benefits DEIB brings, such as innovation, as they look to grow.

Beyond the potential business benefits, though, businesses have an opportunity to make a broader societal impact by redesigning work so that all employees can participate more equitably and inclusively.

Bringing back people who left the workforce will take intentionality, clear policies and practices, and data—lots of data—to understand what’s happening, what’s working, and what could be done differently.

3. New SEC human capital reporting guidelines are likely to result in more DEIB data disclosures. The Securities and Exchange Commission (SEC) revised its 10-K reporting requirements, effective 9 November 2020, requiring companies not just to report the number of employees, but also to provide:

“A description of the registrant’s human capital resources, including the number of persons employed by the registrant, and any human capital measures or objectives that the registrant focuses on in managing the business (such as, depending on the nature of the registrant’s business and workforce measures or objectives that address the development, attraction, and retention of personnel).”

While there’ve been a range of approaches to these new reporting requirements, it’s hard to imagine that DEIB metrics don’t count as “… measures or objectives that the registrant focuses on in managing the business,” especially when you consider the new ties for many companies between diversity metrics and executive compensation.

Further, given all the research that shows the connection between DEIB and business results, you would think that DEIB metrics would be an essential piece of information investors would want to know.

Or, viewed through a more cynical lens, investors might feel they are entitled to information that could result in potential future legal action, such as systemic (intentional or not) discrimination against a certain group, that would be revealed by DEIB representation numbers. If the company has at least disclosed this on its 10-K, then the company may be less likely to be open to legal recourse from investors. (At the same time, maybe it makes clear that potential discrimination exists? I dunno, there’s a reason I didn’t go to law school.)

In short, DEIB data is going to be more important than ever to investors, and companies must figure out how to provide it efficiently, consistently, and in an appropriate manner.

Recalibrating the System

Given all this, we think it’s safe to conclude that DEIB metrics and analytics are more important than ever. But, to our earlier point, it’s not as though DEIB metrics weren’t important before—it’s just that many orgs haven’t been terribly good at developing or using them. Why?

In short, we think it’s because organizational realities have resulted in a system that’s made identifying, tracking, and using DEIB metrics hard. Specifically:

1. A gulf exists between most DEIB leaders and analytics leaders
2. It’s unclear what data to use and how they should be used
3. New DEIB tech vendors offer solutions, but it’s unclear how these solutions fit in

A Gulf to Bridge

Unfortunately, in most orgs, the gulf couldn’t be larger between the groups leading the DEIB efforts and analytics. It’s true that DEIB and people analytics often report to different leaders—DEIB to the CEO or an operations leader at least half the time, and people analytics to the CHRO, talent acquisition or talent management leader, or a centralized analytics team.

But there’s more to it than that—and those differences include the following:

• Background:
  • The leaders of DEIB teams are often folks who hail from a social justice or diversity-focused background
  • Whereas people analytics leaders often have a data, computer science, machine learning, or math background
• Focus:
  • Many (certainly not all!!) DEIB leaders focus heavily on activities that have comparatively little to do with data (at least on the surface), such as setting up employee resource groups, managing DEIB events, collaborating with the local community, etc.
  • Many analytics leaders (again, certainly not all!!) are only involved in DEIB efforts from the perspective of participating in them—but have had little knowledge of any of the theories and approaches underlying those initiatives

• It’s the ultimate situation with “quants and poets” needing to work together—and in most orgs they haven’t yet.

  This situation has resulted in questions, such as:

  • How should DEIB and people analytics leaders partner on DEIB data and analytics?
  • When should people analytics be brought into DEIB discussions?
  • What is people analytics’ role in determining a DEIB strategy, especially as it relates to public proclamations of changes to representation numbers (i.e., doubling the representation of a certain group in 3 years)?

  Data Uncertainties

  Beyond these organizational and dispositional differences, there’s the question of the data itself. Diversity data have historically been treated with kid gloves, with a super select group of leaders being able to see them. Further, much of that data analysis has focused on satisfying Equal Employment Opportunity Commission (EEOC) requirements, without much additional analysis, for fear that the analysis could potentially end with the company in hot water from a legal perspective.

  In recent years, we’ve begun to see a seismic shift (we don’t say that lightly) around the thinking about DEIB data. Leaders are realizing that the potential reputational risk of NOT doing something about DEIB could be larger than the potential legal risk of uncovering something no one wants to see. As a result, they’re moving ahead with analyses.

  However, decades of inaction have resulted in orgs having a noticeable weakness when it comes to identifying, tracking, and using these data. Many leaders want to know things like:

  • What types of data can we use, who can see the data, and what precautions must be taken from a legal standpoint?
  • What are the basic metrics and analyses we should focus on initially? How does that change over time?
  • How should we “productize” DEIB analytics and metrics? To whom should that information be made available?

  Unclear Role for Vendors

  Finally, as we’ve written about for years, the DEIB tech market has grown substantially—and the biggest growth in that market has been around DEIB analytics. That said, in our interviews, we’ve heard things like:

  “I don’t know how DEIB tech vendors should fit into my overall DEIB strategy. When do I use their analytics versus our analytics and how do I integrate all this information?” —Chief Diversity Officer

   

  “If I had a dollar for every time another people analytics leader told me that the Chief D&I Officer brought in a new tech solution without understanding what people analytics could do to help them—I’d be a very rich man. It is so frustrating! We can do so much of this work, but they don’t ask!” —VP of People Analytics

  This lack of clarity on how to work together is causing friction in the adoption of new technologies and the effective use of internal people analytics teams. Some of the important questions here include:

  • Are there particular types of work that vendors are best-suited for—versus people analytics or DEIB practitioners building the tech themselves?
  • When should vendors be brought in?
  • Who should manage the DEIB vendor relationship?
  • Where does the budget typically lie for DEIB tech?

  What We’ll Research

  We’ve laid out our thinking above on the specific questions we think are critical to answer in this research. To summarize, though, the top questions we plan to address are:

  • How should DEIB and people analytics leaders partner to drive DEIB efforts?
  • What are the different types of data and analysis approaches organizations are using / can use to understand DEIB in their orgs?
  • What’s the role of vendors? When should they be engaged by DEIB and analytics leaders?

  That said, we know we’re just at the tip of the iceberg on this topic and realize there is plenty we don't know about. To that end, we’d be deeply grateful if you could take 2-3 minutes to tell us in the questionnaire below what you most want to know about this topic:

  How To Participate

  This study spans the next 3-6 months, so there are lots of opportunities for you to participate. At the moment, we invite you to be part of this research in 4 ways:

  How should DEIB and people analytics leaders partner on DEIB data and analytics?

  1. Answer the above questionnaire. Help us understand which of the 3 areas we’ve identified that you care to learn about the most and what other questions you hope we’ll address.
  2. Let us interview you. We’re looking to interview 3 groups — if you're in one of them and up for a 30-45 minute interview, reach out to [email protected] and we’ll schedule you at your convenience:
     • DEIB leaders
     • People analytics leaders
     • DEIB analytics tech vendors
  3. Join the conversation. We’ll be conducting roundtables on this subject, starting in April. Keep your eyes open for information on the specific dates—or reach out to us at [email protected] and we’ll get an invitation to you.
  4. Share your thoughts. Read our research and tell us what you think! Shoot us a note at [email protected]. Your comments make us smarter and the research better.

Why We Care

We’ve been thinking, talking, and writing about the employee learning experience—its many parts and layers—for a long time. With past research, we’ve emphasized how critical it is for L&D to empower the entire employee learning journey: plan, discover, consume, experiment, connect, and perform.¹

Content’s always been a major part of this learning journey—and the time has come to gain a better understanding of how current content trends are affecting learners and orgs alike:

With so much content available in so many places—and many more learners now attempting to access content remotely—L&D must get a handle on how to enable employees to have the right learning experiences.

By “right learning experiences,” we mean enabling learners to access the right content, at the right time, in the right format for their needs and situation. One big challenge: the “right learning experience” changes from employee to employee and from situation to situation.

A Flood of Learning Content

We’ve been witnessing rapid growth in the amount, types, and sources of content available to learners.

Until recently, almost all learning content was proprietary—created by a central authority (or authorities) in an org for employees of that org. First, we saw a boom in nonproprietary, third-party off-the-shelf content: Designed primarily for leadership development, it burst into areas like frontline training, sales, customer service, and much more.

Until recently, almost all learning content was proprietary. That's changed rapidly. Now there's a sea of content—proprietary and nonproprietary—that learners sometimes struggle to navigate.

Then user-generated content (a subset of proprietary content, but unique in that it's much harder to regulate) became a viable way to scale content creation and support collaborative learning for many orgs.

In response, we saw an increase in market demand for and vendor supply of user-generated content solutions. Figure 1 illustrates content types as we see them today.

Most recently, we’ve seen how L&D functions are struggling to account for (and tie to business goals) all the free, publicly available, uncontrolled content floating out there on the internet—that their learners are accessing and using.

As employees accessed more content in more ways, many L&D teams assumed (incorrectly) that more is better. They focused on giving learners access to all the content they could—proprietary and nonproprietary—including the proverbial kitchen sink. This strategy, they reasoned, would guarantee learners access to the content they needed!

Everything & the Kitchen Sink Just Doesn’t Work

In recent years, and especially with more employees working from home since COVID-19’s onset, the provide-everything content approach has shown its weaknesses—not the least of which is flooding learners with just too much.

• Cause: Employees are overwhelmed by the amount of content at their fingertips and struggle to navigate to what they really need.
• Effect: This situation discourages many employees from taking advantage of learning opportunities, ultimately hindering their performance and the org’s.

Providing tons of content also makes it difficult to ensure employees access the best (most relevant, highest quality) content or the content that most closely supports organizational priorities.

For example, let’s say the best content for a given employee and situation is a proprietary document created by a central L&D professional. But the easiest-to-access content is a public, nonproprietary video on YouTube. Which content is the employee more likely to consume? Probably the YouTube video—which isn’t ideal for the employee’s development or the org’s goals. This type of situation presents a challenge for L&D.

Learning depends not only on what the content is, but also on how it’s accessed.

There’s a growing recognition that learning depends not only on what the content is, but also on how it’s accessed. Successful learning means employees get the right content, yes—but they also get that content at the right time and in the right format / modality (in-person, virtual, mobile, coaching, on-the-job practice, etc.).

What We’ll Research

The challenge facing L&D has become:

How can orgs continually enable learners to access the right content, at the right time, in the right format—in short, to have the right (best) learning experience?

We want to understand this question in detail, with a focus on how the answers change based on content type—proprietary or nonproprietary. We sense that content type strongly influences what the "right content" is and how it should be delivered. In particular, we hope to understand:

• How orgs identify / select content that meets both critical org priorities and individual employee needs
• How orgs manage content to be delivered whenever / however it’s needed
• How orgs prioritize content so as not to overwhelm learners (i.e., identify the best content for a particular situation)
• How orgs tie all of these varied ways of learning to improvements in key business outcomes
• How these answers change based on content type (proprietary / nonproprietary)

How You Can Participate

Be an active part of our learning content research—here’s 3 ways:

• Join us for the roundtable. We’ll be hosting a roundtable on this topic—we’re looking for forward-thinking leaders to participate. The roundtable will be held on Tuesday, April 13 from 11am ET to 12:20pm ET. Apply to participate here.
• Let us interview you! Tell us what your org’s doing and how you're approaching content challenges. Reach out to us at [email protected].
• Join the conversation. Read our research and tell us what you think! Leave a note below or send us an email. Your comments make us smarter and the research better.

Why are we talking about mobility right now?

For many of us, 2020 has been a year of hard lessons. Many organizations are learning that the way they move and develop talent needs to change. Career paths (like everything else, it seems) are, out of necessity, becoming more flexible and less predictable. Interestingly though, they're not becoming less important. Why, amid a global health crisis, social unrest, natural disasters, and an upcoming election, is employee mobility more important than ever?

The answer is two-fold. First, investing in career development is one way to keep your most talented employees. Economic turmoil creates a unique opportunity to recruit top talent,¹ and if this talent resides within your organization the importance of invested employees becomes clear.

Second, great talent is becoming more difficult to find, with organizations facing the largest talent shortage in over a decade.² Looking internally, rather than externally, to find the skills to compete provides an often underused solution to the challenges plaguing many organizations.

Given the world's current state of affairs, organizations need to react more quickly to external and internal pressures. That often means ramping areas of the organization up or down quickly – something difficult in many of the structured career paths many companies use.

Why other models are becoming more prominent

Our dive into the research and conversation around mobility has revealed one common theme early in this research: the career ladder is not the only way. In fact, there are several models that are becoming more prominent – which we'll explore in more depth in this research. There are also several reasons we are seeing organizations explore other approaches to career development. Any of them sound familiar?

Increased unpredictability. As the world, and the organizations we work for, become less predictable individuals can no longer count on lifetime employment from their company. As such, individuals are taking ownership over their careers rather than relying on organizations to provide a clear path. Restructuring, layoffs, and global pandemics result in individuals moving across organizations, which has made skill development a centrally important topic to employees.

The gig-economy. Contract workers, consultants, gig-workers, and freelancers now make up approximately 30-40% of the workforce in the United States.³ Responsive organizations do not shy away from utilizing this sector of the workforce and may in fact rely heavily on it (look at Google).⁴ By nature, the independent worker does not stay with the company for an extended period – thus the career path for this growing population does not follow the typical trajectory.

Different kinds of work. The rapidly changing external environment calls for a change in the way we do work. Taking inspiration from the gig-economy, some companies are organizing work around projects and teams. AT&T, often cited as a leader in innovative talent ideas, imagines that the future of work will be project-based.⁵ This approach allows for a quick response to the demands of the environment, but also requires an understanding of the skills and capabilities available within the organization.

Employee expectations. Organizations aren’t the only ones changing their perceptions of work. Employees no longer expect to stay with one company or even in one career (our team is quite familiar with this idea – with some of us experiencing 4 career changes!). Career paths are looking less like lines and more like Pollock paintings. Employees are looking for a different kind of work experience – to develop more holistically, learn new things, and expand their skills stack.⁶

What we'll research

In the coming months we will be exploring what successful internal mobility looks like. While there is no “one size fits all” solution to career mobility, we expect that some approaches work better for a set of circumstances.

Our Hypothesis: While we don't think there is a "one size fits all" solution to employee mobility, we expect that some approaches work better for organizations with a set of characteristics or circumstances.

To find out, we're diving deep into the current conversation on mobility – investigating topics like strategic workforce planning, career progress, internal mobility, gig-economy, and reorganization. We hope to learn:

• Approaches that organizations are using to manage the careers of their employees.
• Characteristics of organizations that make one approach more appropriate than another.
• Other areas within the organization that are influenced by or influence career mobility (e.g. people analytics, leadership, learning and skill development, etc.).

How to participate

Join us for a roundtable. We’ll be hosting 3 separate roundtable events and are looking for forward-thinking leaders to participate. We'll cover a broad range of topics, from new talent pools to technology that can help. (Click below to register.)

• Oct 13, 9am EDT: Mobility Roundtable #1: Talent Sources and Employee Preferences
• Oct 21, 9am EDT: Mobility Roundtable #2: The Virtuous Cycle – Mobility for Skill-building and Development
• Nov 12, 9am EDT: Mobility Roundtable #3: The Supports: Leadership, Tech Stacks, and Messaging

Let us interview you! Tell us what your organization is doing and how you're approaching the ever-increasing role of mobility in staying agile. Shoot us a note at [email protected].
Join the conversation. Read our research and tell us what you think! Leave a note below or shoot us an email. Your comments make us smarter and the research better.

The frenzy over “skills” (reskilling, upskilling, unskilling, skilling 2.0, etc) has recently ratcheted up from a philosophical discussion to a verifiable necessity. While many leaders thought they had time to ease into a strategy, COVID-19 and some of the other unrest the world has experienced in 2020 have left leaders scrambling to help their employees develop new skills, establish new mobility patterns, make decisions on how to rearrange departments, functions, and make tough decisions about which skills (and employees) are mission critical, and which ones are not.

We’ve been watching the skills discussion for a few years. We've had regular conversations with academia, consulting firms, and leaders of big and small companies. We’ve also listened carefully to what was being said and written on the topic, and until now, we weren’t sure that the conversation was mature enough to warrant research – they didn’t seem to matter enough. For example, prominent discussions have included:

• Which skills will be the most prominent in 2025, 2030, or 2050. While this has been somewhat interesting (e.g., will soft skills become more important, who will lose their jobs because their jobs can be automated, etc.), it seems a bit inane to assume that all workers and all organizations will need the same skills. We believe that determining necessary skills is a do-it-yourself-job. It's contextual, and it's specific, and organizations can’t cheat off of their neighbors.
• What we call them. Are skills the same as competencies? Are competencies the same as traits? As we have looked into this, there is obviously some overlap and there are obviously some differences. We think, however, that this conversation detracts from the bigger question of, “How do we determine what people have, need now, and need in the future, and help them develop it?”
• Skills as discrete and finite. Most of the stuff we’ve read talks about skills as finite: what skills – individual tasks – we need employees to do. Thinking this way limits an organization in that it takes care of this point in time only, which is a hopeless process, as by the time you have determined a structure for those skills, the world has moved on. We’re more interested in how organizations are developing the right culture and systems to ensure ongoing skills development.

In the coming months, we want to add to the skills conversation in a meaningful way. Specifically, we’d like to research a few areas that leaders and practitioners will find most useful in making plans and decisions. So we’d like your opinion.

As always, we’d love your thoughts. Feel free to shoot us a note, contact us directly, or leave comments in the Feedback section to the right.

It goes without saying that the killing of George Floyd and the subsequent protests have laid bare the significant race-based differences prevalent in American society. Unfortunately, despite many leaders’ best efforts, those differences don't stop when people pass through the doors of corporate America.

We all know that diversity and inclusion (D&I) is important to business outcomes. But, even more, it's critical to our humanity. Seeing and respecting others for everything they bring – and ensuring that everyone feels safe, valued, respected, and like they belong – is a critical part of a human environment, not just a work environment.

Why we care

Given everything that's happening, there's an even greater need to bring all of our resources to bear on understanding and improving diversity, inclusion, equity, and belonging in companies today.

Responses from corporations with statements supporting the protests against racism have been swift and numerous. However, only a small fraction of those have been turned into actions by taking tangible steps. Companies, such as Goldman Sachs, Lego, and Cisco¹², donated millions to charities to help fight racism and inequality, but there's still much that remains to be done to improve levels of diversity, inclusion, equity, and belonging within organizations.

Aware of this heightened call to action, we're undertaking our 2020 update to our D&I technology research. While we recognize technology is only one part of how leaders can address the underlying challenges within their organizations, it's still an important part.

In particular, technology can help identify patterns that may not have been previously known to exist, determine areas that need to be worked on, heighten awareness at critical decision points, and provide predictive data that can guide better insights for the future.

How you can participate

We invite you to participate in our research if you are one of these 3 groups:

• Customers of D&I tech vendors. If your company uses D&I technology in any form, we’d love to hear about your experience in our short 5-7 minute poll at danditech.com. Below is a list of companies previously included in our research (any of which might be one of your vendors) that you can give us feedback on. If your vendor isn’t on there, tell us which they are and give us your feedback – we'll track them down to get the other information we need from them.
• D&I tech vendors who participated in our 2019 research. Your company should have already received an email informing you of the detail of our process and inviting you to take our survey. If you haven’t received this email, send us a note at [email protected].
• D&I tech vendors who have not yet participated in our research. If you think you should be included, send us an email at [email protected], explaining your solution and why you think you should be part of the study. We'll get back to you as soon as we can.

When we launched our first D&I tech study, it was in the midst of the #MeToo movement. We are at the beginning of another movement that also requires our utmost commitment. Our fervent hope is that our work – when combined with the good work of so many of you – will help move the dial on the inequities we see all around us. Thank you in advance for taking yet another step on this long journey to drive necessary, critical change.

Why we care

In 1776, Adam Smith wrote in The Wealth of Nations:¹

“It is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their self-interest.”

In essence, Smith was saying that businesses exist to make money for themselves, not necessarily so they can feel better about feeding their community, providing high-quality jobs, or producing their goods using environmentally-sensitive methods. This line of thinking – that businesses exist to increase the wealth of their owners (shareholders) – has been a foundational principle for many business leaders.

But not for all business leaders. Since the 1800s, leaders such as Robert Owen, James Cash Penney, and William Lever (among many others) have focused on more than the bottom line, by caring about employees, the environment, and their stakeholders.² These leaders represent a sense that businesses have a large obligation to their employees and communities.

The tension between these two perspectives has tipped one way and then the other for years. Last fall, though, the balance tipped firmly to the side of businesses having a broader responsibility. In August, the Business Roundtable, a group of CEOs from large and significant companies, stated that, in addition to generating long-term value for shareholders and delivering value to their customers, they commit to:

• “Investing in our employees. This starts with compensating them fairly and providing important benefits. It also includes supporting them through training and education that help develop new skills for a rapidly changing world. We foster diversity and inclusion, dignity and respect.
• Dealing fairly and ethically with our suppliers. We are dedicated to serving as good partners to the other companies, large and small, that help us meet our missions.
• Supporting the communities in which we work. We respect the people in our communities and protect the environment by embracing sustainable practices across our businesses.”³

Assuming you take the group at their word, this represents a significant shift from a laser-focus on shareholders to a broader one on stakeholders.

Hypotheses

Our hypotheses for this study include the following:

1. The underlying factors contributing to CEOs, senior leaders, and boards of directors embracing stakeholders, in addition to shareholders, are meaningful and different from previous times business leaders have attempted this shift.
2. Organizations with a purpose that focus on a broader set of stakeholders organize, manage, enable, grow, and amplify their people differently than those primarily focused on just generating shareholder value.
3. These practices can be codified and scaled such that they are not limited just to a single organization.
4. These organizations are developing novel – yet potentially standardized – approaches to measuring the impact of their purpose.
5. These practices can positively impact an organization’s ability to generate shareholder value.

As alluded to above, this isn't the first time business leaders have focused on broader social good. However, we believe there may be some systemic changes, such as global climate change, that are different from previous iterations of this attempt. In this research, we plan to identify those factors and better understand if it really is different this time.

There are numerous examples of organizations who are already attempting to be more purpose-driven. We believe that there are similarities in these organizations’ people management practices.

We plan to better understand:

• What does “purpose” mean in these organizations and how is it measured?
• What does “purpose-driven” mean in terms of how organizations attract, engage, develop, and retain their people?
• How, overall, is the employee experience different at purpose-driven organizations?
• What do leaders do differently at purpose-driven organizations?
• What are the implications for HR?
• How do purpose-driven organizations track their quantifiable impact on stakeholders (e.g., revenue, profitability, engagement)?

This Project

We examine the following concepts in this research project:

Why we care

Organizational support for gender diversity – or at least the talk around it at executive levels – is at an all-time high. Yet, women still remain woefully under-represented at nearly every level in organizations.

While organizations have taken steps – particularly in performance management (PM) – to address this disparity, the difference grows steadily at each level as more men are promoted than women. The result: men end up holding more than 60% of managerial positions, while women hold less than 40%.¹

Clearly, something happens – something fundamentally different – that changes the upward career trajectory of women, even when they enter their careers on equal footing to men. While there are many potential factors, including work / life integration, employee benefits, leadership development, etc., we know that one of the biggest factors is performance management, as it influences both compensation and promotion decisions. Given this, we wanted to investigate what might be happening differently for the different genders² within PM.

Hypothesis

Our hypothesis for this study:

Given the impact of performance management practices on promotion, it's likely that men and women are having different experiences within PM that are negatively influencing women’s advancement in organizations.

The myth of gender differences

Oftentimes, we assume that, because a practice is fair on the surface, it must result in similarly fair outcomes for men and women. Thus, when we see differences, it can be easy to assume that the individuals are different in some fundamental manner. This is the case with men and women in the workforce, where different outcomes have been explained away by apparent “fixed” gender differences, such as women desiring to leave work more frequently to care for family or women not having the same expertise or competence – especially in critical fields.

Yet, when we dig into these arguments, we find they don’t hold water.

For example, suggesting that women are not as competent as their male counterparts ignores the fact that women continue to earn more college³ and graduate degrees⁴ than men. In addition, while women earn roughly half of the science and engineering (S&E) undergraduate degrees, they're less likely than their male collegiate peers to actually end up participating in S&E occupations.⁵

Further, arguing that women want something fundamentally different from their careers and they're leaving the workforce in droves to have babies and take care of family is not a true representation of turnover rates. Especially when we see that women and men have similar turnover intentions and only 2% of women leaving the workforce do so to focus on family.⁶

The truth is, the different outcomes that we see aren't due to innate gender differences – but instead are a result of the different ways in which men and women experience work. From fundamentally different interactions with managers and peers to policies that inadvertently hinder women’s progress, women experience the workplace differently.

Good intentions: We've paved a PM system full of them

Fairness has been a foundational concept in PM since we started measuring performance. In fact, we began measuring production to help organizations make administrative decisions and determine how much to pay people (an idea still foundational in pay-for-performance approaches). However, as work has changed – so too has PM.

In the last 7-10 years, organizations have taken many steps – often times dramatic ones – to modernize their approach to performance management. While the primary aim of PM redesign was to provide a more growth-oriented approach to drive performance, many of the changes also touched upon ideas of fairness.

Modern PM extends the concept of fairness beyond a paycheck, including:

• Capturing a more accurate picture of performance by rethinking ratings and expanding performance evaluation criteria
• Gaining a more holistic perspective of the individual through more frequent conversations between the manager and employee
• Decreasing bias by increasing the frequency and the sources of feedback (e.g., crowdsourced feedback)
• Ensuring that individuals are evaluated against relevant objectives by setting and updating goals in a continuous and agile manner
• Leveraging PM to develop employees in more meaningful ways (e.g., starting out with career or development goals before determining performance goals, assessing managers on the extent to which they develop employees)

All of these changes – and many others – have been made with good intentions. Organizations want to create PM systems that provide a more accurate picture of performance and foster an environment that is inclusive, fair and equitable to support growth and development. Yet, good intentions and superficial fairness does not mean these practices are experienced by men and women similarly in their day-to-day interactions within organizations.

Creating a level playing field

Given these different organizational realities, organizations need to better understand how their practices play out in reality for women and men. This will likely require organizations to rethink (at a minimum):

• The relationship between managers and employees and how managers are held accountable to developing talent
• The access that all employees have to relevant, value-added information, feedback and critical people / influential networks needed for development and performance
• The underlying theory that employee development is the primary responsibility of employees, when men and women – as a result of their relationships – have access to different types of development and may have different levels of confidence in pursuing development of their own accord⁷
• The way organizations define, identify, and measure disparities between men and women
• The lack of confidence and faith that women – across levels – have in their organizations to actively address gender diversity in real, meaningful ways

These changes could have profound impact on how women experience PM and, ultimately, move the needle on the advancement of women in organizations.

This project

With this study, we want to gain an understanding of the ways in which men and women experience performance management differently. More importantly, we want to uncover ways organizations can move beyond superficial fairness, and ensure that men and women are experiencing the same organizational reality. In our initial discussions, several themes have emerged that serve as the basis for the research:

 

Why we care:

Organizations, and the employees within them, are often compared to machines: leaders give employees a task, tell them to execute it, and approve any deviations. While this approach can work well for creating large efficiencies on clear tasks, it fails in times of massive and rapid change and complexity. We are now in one of those times.

We think it is time for an alternative approach – one that rethinks how we design organizations’ systems, processes, and measures to enable the entire organization to be more responsive.
This has been an ongoing conversation at RedThread for over a year and a half. Thankfully, the good folks at Glint agree with us, and have been kind enough to sponsor this research on understanding and creating a “Responsive Organization.”

Hypothesis:

Our hypothesis for this study is fairly simple:

The world has changed and requires a different kind of organization. Those that focus on being responsive – not just efficient – adjust better to external market pressures, which results in a competitive advantage.

What got us here won’t get us there

For at least the past 100 years, the corporate world has heavily focused on efficiency – and that has driven everything from the way we measure success to how we structure our organizations. And while a focus on efficiency has led to some excellent gains in productivity in the last century, signs point to the fact that it’s no longer enough. Specifically, as you can see in Figure 1, the last decade has experienced a much slower rate of productivity growth (which is essentially a measure of efficiency), than the two decades before it.

Figure 1: Multi-factor productivity, 1987-2018 | Source: Department of Labor, Bureau of Labor Statistics

Why are we seeing this flattening? There are a significant number of potential reasons, but we believe that at least part of the problem is that we may be reaching the limit of efficiency. It is impossible to make a machine or system infinitely efficient; at some point, the effort required to make something more efficient is greater than the resulting benefits from the efficiency. At that point, a fundamentally new system is necessary to improve efficiency gains. Let’s use a second industrial revolution example: people can only weave textiles so quickly, no matter how hard they worked and how efficiently they moved. At some point, the only way to do this more quickly was to use a sewing machine.

Here in the fourth industrial revolution, we believe we are at this point where we have to fundamentally rethink how we conduct business to adapt to the fast-moving, technology-saturated world in which we all work. Our organizations need to become more responsive to all that change. However, to do it, we will have to change organizational structures, measures, and practices that were designed for efficiency, but not responsiveness.

Technology alone won’t solve our problems

We recently read a pretty interesting (and disturbing) study done by Korn Ferry that indicated that CEOs are so enamored with technology that they see it as a larger source of competitive advantage than their own people. Other disturbing statistics from that study are shown below:

Figure 2: CEOs think that technology, not people, will create most value in the future | Source: Korn Ferry CEO survey, 2016.

Of particular concern, is the last finding – that 44% of CEOs say the prevalence of robotics, automation, and AI will make people “largely irrelevant” in the future. While some of the technologies that are becoming embedded in our daily lives seem amazingly “smart,” they have limitations. For example, Jonathan Zittrain in The New Yorker shares the following point:

Consider image recognition. Ten years ago, computers couldn’t easily identify objects in photos. Today, image search engines, like so many of the systems we interact with on a day-to-day basis, are based on extraordinarily capable machine-learning models. Google’s image search relies on a neural network called Inception. In 2017, M.I.T.’s LabSix—a research group of undergraduate and graduate students—succeeded in altering the pixels of a photograph of a cat so that, although it looked like a cat to human eyes, Inception became 99.99-per-cent sure it had been given a photograph of guacamole… Inception, of course, can’t explain what features led it to conclude that a cat is a cat; as a result, there’s no easy way to predict how it might fail when presented with specially crafted or corrupted data. Such a system is likely to have unknown gaps in its accuracy that amount to vulnerabilities for a smart and determined attacker.

While we certainly believe in the power of technology, we cannot lose the human aspect of work. People are the ones who design the systems in which we all live – and are the ones who can do the deep thinking to identify when we need to build different and better ones.

A fundamental re-think on how we measure and manage

As organizations realize the benefits of moving away from a focus solely on efficiency, we think they will begin to rethink their organizational structures. This will lead to changes in the following (at a minimum):

• Communication channels – Individuals at lower levels will have data and information they need to react to needs “on the ground.”
• Power structures – Decision-making will be more decentralized.
• Employee development – More autonomy and continuous development will ensure that employees have the skills and knowledge needed.
• Metrics – Measurements of efficiency will begin to give way to other types of productivity metrics that focus more on innovation, agility, and responsiveness.

These changes will have profound implications for organizations’ people practices and require different types of leaders than in the past.

This Project:

With this study, we want to gain an understanding of the characteristics that make organizations better able to respond to their markets. In our initial discussions, several themes have emerged that will serve as the basis for the research:

Efforts to improve women’s representation in leadership are decades old, yet the numbers remain stubbornly low:

• For every 100 men promoted, only 79 women are promoted¹.
• Approximately 40% of women in senior roles/technical positions report being one of the only women in the room².
• The World Economic Forum³ estimates it will take 168 years for North America to close the global gender gap.

So, why don’t we see more women in leadership?

There are many potential answers to the question of why women do not rise at equal rates as men. However, of all the potential solutions, our research identified one we think deserves more attention than it has received to date: women are not gaining access to the information and opportunities they need from their professional networks in order to advance.

Our network connects us to the right groups, people, and information and inclusion at work – through our networks – can be a critical factor that influences promotion and advancement opportunities. Unfortunately, research indicates 81% of women report some form of exclusion at work, yet 92% of men don’t believe that they are excluding women at all⁴. This difference highlights the critical, yet less obvious influence of our professional networks.

Based on our interviews, women tend to advance when three conditions are present:

• People work with them and experience them as equally competent professionals.
• They are given access to opportunities and experience.
• They are included in conversations and have access to information at the right level.

Focusing on networks can help with all these things. More specifically, networks – and the information they carry – are one of the primary ways people learn about career advancement and development opportunities. By being in the right networks, women have an opportunity to work alongside and for others who would support them in their advancement. They also have access to high-quality opportunities and can have the conversations that help them advance.

However, research suggests that women and men's networks – and the information within them – are different. Understanding these connections between people – who knows whom and why – could help organizations understand why some employees rise and why others do not.

How are men and women’s networks different and why does it matter?

Traditional social dynamics – along with promotion rates, power, and rank – influence the creation and composition of professional networks.^5,6 In general, as men move up the ranks in organizations, they join higher-status networks with more information and power. They also are more likely to be surrounded by men, because men, statistically speaking, are more likely to be promoted. Women – who tend to be promoted at lower rates – more often find themselves in lower-status networks (which can be women-dominated).

Network status influences the extent to which someone has access to key conversations, information, and projects that would help them advance in an organization.⁷ Since men tend to be in those high-status networks, they tend to have access to higher-quality information and gain access to opportunities that support advancement. Women in lower-status networks do not receive the same benefits.

While this is an incredibly simplified version of a very nuanced and complex problem, the key message is that the mechanisms that have created traditional organizational hierarchy, policy, and practice have also created echo chambers that disproportionately benefit men and hamper the advancement of women.⁸

What should women consider when building their network?

The research is great, but what does it mean, practically speaking, for women and how they build their network? For starters, it means understanding that networks – left to haphazardly build by chance – are likely to disproportionately negatively impact women. The good news is that women who use this information to intentionally build their network can increase their likelihood of advancement.

Research reveals there are four foundational principles (see Figure 1) women should keep in mind when building a professional network that can help them advance.⁹ These four foundational principles are critical for organizations to consider when designing initiatives to help women advance; we will discuss them in that context at further length later in the report. For more information on these four foundational principles, see the Appendix.

Figure 1: Four foundational principles women should follow when building their networks | Source: RedThread Research, 2019.

Are organizations considering networks today when trying to advance women?

Given the huge preponderance of research¹⁰ we’ve seen that points to the importance of networks in enabling women to rise, we began this research with high hopes of finding examples of organizations using network theory in their approach to advancing women. After all, there are decades of academic research¹¹ on the topic of how networks differ among genders and how network status and power influence professional advancement. Further, most professionals are on various social networks that are technologically enabled, so our awareness of networks – and how they can be accelerated or changed by technology – is higher than ever. Therefore, it seemed logical that a number of organizations would be thinking about gender, networks, and how to use technology to help women rise.

We were wrong. After our 50 interviews with organizations of very different sizes, industries, and geographies, we found that relatively few organizations are thinking about how to help women design and build their networks intentionally. And even fewer are thinking about how to use technology to help. This was deflating.

However, all was not lost. Through our interviews, we gained significant insight into what organizations are doing today to advance women and found some examples of organizations tweaking common practices to account for network dynamics. We also uncovered a lot of existing technology that could help organizations evolve their existing practices to help with network dynamics. Further, we identified some novel practices that are showing early promise in advancing women.

In the pages that follow, we describe the common and novel practices for advancing women that we identified through our interviews. For all of these practices, we explain how network dynamics – in particular, the four foundational principles for women building their networks – play out. We further highlight the technology we think could help and give ideas for how new, yet-to-be-invented technology could assist in the future. We provide case examples wherever possible to bring the research to life.

Our hope is that this paper serves as a call to action for all leaders to re-think the practices and technology they use to advance women, and to much more substantially integrate an awareness of networks and how they play out differently for women into their efforts.

We know our connections matter. Both who we know and what those connections provide (information, resources, access, visibility) matters to career progression – so let’s make sure that women have the right connections that can help them advance. Our organizations’ future successes – and many women’s livelihood – depend on it.¹²

Why is this important?

One of the most impactful ideas in recent learning technology is that of ecosystems. Obviously, ecosystems are not new: we’ve been talking about them for years. But the conversation is resurfacing with a vengeance for two main reasons.

First, organizations need ecosystems. Flatter structures, greater connectivity, increased collaboration, thinner organization walls (e.g., gig economy workers), and a shifting focus on creating a positive employee experience have many leaders searching for solutions more customized to the challenges their organizations face.

This is beginning to lead them away from a solitary learning platform and toward a network of point solutions that work together to better serve their purpose. We think that having a thoughtful and strategic learning tech ecosystem will help organizations compete.

As organizations need to be more agile to respond to their markets, L&D functions need to be more agile to develop their workforce. An ecosystem (instead of one platform) allows organizations to adapt their technologies to fit those development needs.

We think that having a thoughtful and strategic learning tech ecosystem will help organizations compete.

We think that organizations with successful learning ecosystems will be more strategic and intentional in their employee development efforts in an attempt to help their organizations respond more quickly to the marketplace. Since different workplace skills and capabilities are needed, the best way to develop them also changes. An ecosystem approach allows organizations to add to or take out technologies to accommodate those changes more easily.

Second, solution providers are making ecosystems easier. In the recent past, the buzz in the learning tech space revolved around being the “front door” for learning and having all learning (and therefore all data) exist on one platform.

Things have changed. Solution providers are providing some really unique and interesting tools and specializing instead of platformizing. Roughly 60%¹ of providers in the space do just a few things really well and focus pretty heavily on making it easy to both launch and integrate their tools into existing ecosystems. And not only are they doing it better than they ever have before, they’re touting it in their marketing: they can clearly articulate what they do and how they fit into the larger ecosystem.

Solution providers can clearly articulate what value they provide and how they fit into the larger ecosystem.

Interestingly, however, while the idea of ecosystems seems to resonate with both L&D functions and with vendors, there isn’t much information out there about how to intentionally design one. Sure, leaders have begun to dip their toes in, but they often do it in a way that leads to a smorgasbord of technologies rather than a cohesive ecosystem.

In fact, 85% of organizations report having a fragmented ecosystem.² Today, we’re launching a formal research study, sponsored by Axonify, Degreed, and NovoEd, into how organizations are purposefully designing these ecosystems to meet their specific needs, how they integrate into the wider technology ecosystem, and how they better serve the individual as well.

Learning Tech Ecosystem Research

The purpose of this research is to gather and share information that may be helpful to organizations who are currently trying to figure out their learning technology. To that end, we’re starting with three assumptions that we’ll test throughout the study.

1. Different conditions call for different types of learning tech ecosystems

While we recognize that each learning technology ecosystem needs to be tailored specifically to the organization, we think there are likely “personas” or types of ecosystems that are likely to work in certain situations. For example, smaller organizations, or organizations in certain industries may have similar configurations of technologies. Likewise, organizations where the majority of the workforce works on the front line may require a different type of ecosystem than those where most employees sit behind a desk. We want to identify these “personas” and in what types of organizations they’re most likely to be used.

2. Capabilities first, technology second

Right now, the market classifies learning technologies by the type of technology: LMS, LXP, microlearning, and the like. While this makes sense, particularly given that there are general line items in the budget for these types of purchases, we think there’s a better way.

In our initial discussions, leaders in more evolved organizations don’t start with the technology; they start with how they want to enable their employees to learn. We first noticed change this last fall when we looked at the learning technology landscape. While there are 28 different learning technologies, they can actually be grouped into how they help to enable development. As we interview leaders for this study, we’re interested in their approach as well as which functionalities they’re enabling.

3. Integration with the larger ecosystem

Last, but definitely not least, learning technology ecosystems should not be stand-alone systems. In fact, because work and learning are so closely integrated these days, they cannot be. As organizations think through the technology they want to use to develop their employees, they should be considering more than just the line items in their budget.

Learning technology both integrates and interfaces with technology used to do jobs. We’re betting that more evolved organizations understand where their technology (and resulting data) should hook into the larger organizational tech infrastructure.

This research

One of the reasons we feel compelled to research this topic is because not a lot of information currently exists. In fact, we have started the literature review and have broadened the scope slightly because we think some key information can be found in tangential topics. Some of the ideas we’ll be exploring in this research include:

Tell us what you think.

If you have questions or comments or even critiques about our initial theories, please reach out – we would love to hear from you. Drop us a note here or comment below. We read them all.