Events

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

What are some of the obvious and less obvious risks of choosing and implementing D&I technology? In our recent study with Mercer, we examined the emerging market for D&I tech. As part of our exploration, we needed to take a step back to understand the potential gains or pitfalls that come when well-intentioned companies use technology and AI to solve endemic people challenges.

Here is an excerpt from that report which breaks down some of the risks and payoffs of implementing D&I tech:

What are the benefits and risks of D&I technology?

While there are many potential benefits of D&I technology, the most apparent one is the opportunity to create consistent, scalable practices that can identify or mitigate biases across organizations, often in real-time. Many people-related decisions leave a lot of room for bias, particularly when it comes to an assessment of a person’s skills, behaviors, or value (e.g., for hiring, performance evaluation, promotion, or compensation).

Much of the technology on the market today is designed to change the processes that enable bias or identify that bias exists. Another benefit customers see in D&I technology is the increased understanding of the current state of diversity and inclusion throughout the organization. With greater visibility, leaders can better measure and monitor the impact of D&I initiatives.

Benefits:

• Implementing more consistent, less-biased, and scalable people decision-making processes
  Increasing the understanding of the current state of diversity and inclusion across the entire organization, using both traditional and new metrics
• Measuring and monitoring the impact of efforts designed to improve D&I outcomes
• Raising awareness of bias occurring in real-time and at the individual level and enabling a range of people to act on it
• Enabling action at individual levels by making new, appropriate information available to employees at different levels within the organization
• Signaling broadly the importance of a diverse and inclusive culture to the organization

Risks:

• Implementing technology that itself may have bias due to the data sets on which the algorithms are trained or the lack of diversity of technologists creating it
• Creating legal risk if problems are identified and the organization fails to act
• Enabling the perception that the technology will solve bias problems, not that people are responsible for solving them
• Reducing people’s sense of empowerment to make critical people decisions
• Implementing technology or processes that are disconnected from other people processes or technologies
• Enabling employee perceptions of “big brother” monitoring, an over-focus on “political correctness,” or “reverse-discrimination”

“Metrics aren’t always immediately useful.”

Susie Lee, Degreed

One of the reasons so many L&D functions struggle with learning measurement and learning impact is that they have no consistent data. In fact, according to Brandon Hall, only 51% of companies say that they are effective or very effective at measuring formal learning. And even fewer are effective when it comes to measuring informal (19%) and experiential (29%) learning¹.

While these statistics focus on a more traditional way of viewing learning and development, the fact that only 51% of organizations are effectively measuring formal learning – which, by the way, they have complete control over and for which they have complete access to the data – is telling. By and large, L&D functions do not have a data culture. But they could have one.

How should they start? Leaders told us that they needed to overcome two major challenges in order to get consistent data: patience and standardization.

Be patient – it’s a virtue

Most L&D functions either really struggle to collect data and information on a regular basis, don’t do it at all. At least a part of this struggle stems from the practice of focusing on one-time measurements. When L&D functions focus on calculating the ROI or learner satisfaction associated with one course or initiative, the tendency is to collect only the information needed to serve that one purpose.

This focus on point-in-time results means that longitudinal data, interactions, and correlations are hard to come by in many organizations. Interactions and correlations over time provide ongoing insights about what is happening and why. Without consistent L&D data, it is difficult, if not impossible, to understand the impact employee development is having on organizational goals. Understanding this impact is the first step in being able to make intentional decisions about where to go next.

Collecting data over time can be challenging, and the fact that data and metrics may not be immediately useful can add to that challenge. But establishing continuous collection goes a long way in building a data and metrics culture.

In our conversations with leaders, three pieces of advice for how to consistently collect data stood out:

• Start where you are and keep at it. Metrics aren’t always immediately useful – it often takes time, dedication, and investment. But the results are worth it. Several leaders emphasized the importance of starting where you are and building capability as you go along. No need to boil the ocean, but you must be consistent. Rachel Hutchinson, director of L&D at Hilti, said her team collects data for 6 months on any given initiative or change: 4 months to get results and 2 extra months to make sure it wasn’t a blip in the data.
• Consider continuous data feeds. This bears repeating: L&D functions should think in terms of continuous data feeds instead of static reports or one-off calculations of metrics for two reasons. First, continuous data feeds provide the most recent data, giving L&D functions the ability to adjust to conditions more quickly. Secondly, it’s only slightly more difficult to set up a data feed than ask for a one-time data dump. Working with IT and other business functions to set up feeds will ultimately save the entire organization time and effort.
• Automate data collection. In circumstances where it is necessary to collect data (rather than using other sources), automate it! Learning leaders we spoke with do this by planning for surveys, evaluations, and feedback as a part of the design process for any initiative, utilizing scheduling software or investing in measurement software that helps you do it (Watershed, forMetris, etc.).

Standardization

The other part of the consistency story is data and metrics standardization. Why? In order to consistently monitor and make good decisions, data and metrics need to be correct and comparable.

Standardization also ensures that L&D data and metrics are consumable by other business functions, by central data analytics teams, and by other technologies and systems. L&D functions should start by identifying any existing data standards their organization may have and adopting them.

That said, our interviews with L&D leaders indicated that the first challenge was often standardizing data and metrics within their own department. They talked about three types of standardization:

• Consistent formats. If data will be compared over time or with data from different systems or functions, using consistent formats is key. One leader mentioned the first time she realized the importance of this was in trying to pull a dataset for a given timeframe. Since she worked for a global organization, dates were stored differently depending on where in the world they were. While technology is getting smarter and better able to correct some of the challenge, identifying standards for data formats upfront can save a lot of headache down the line.
• Consistent scales and data types. In situations where data needs to be collected, particularly through surveys or evaluations, consistent scales and data types should be used. Three-point scales vs. 4-point scales vs. open-ended answers all affect how easily data can be compared. One leader told us of the struggle he had of simply trying to get the entire organization to use one form so that course evaluation information was standard and could be compared.
• Consistent collection methods. How and when you ask questions, who you ask them to, what words you use to ask them, who is asking them, and the format in which they are asked, can have an effect on responses. More evolved L&D functions are standardizing some of these things – sometimes with the use of technology – too ensure that bias doesn’t creep into their data and to ensure consistency.

Unfortunately, developing a data and metrics culture within L&D functions is most likely not second nature: it takes work and investment. And it’s often not the sexy part of what we do. But we think that this culture and the ability to consistently collect and analyze data is the first nut L&D functions need to crack. As organizations begin to collect and assess information regularly, they will better understand how employee development is affecting the organization and their options for having impact will increase.

Why are we seeing more attention on D&I right now? When we began our recent study with Mercer, we recognized there were many factors driving the emerging market for D&I technology solutions. Here is an excerpt from that study with some of our thoughts on why D&I tech is a market that is gaining so much momentum.

There are numerous trends driving the increased attention on the D&I conversation, not least of which is the changing racial and ethnic mix of the U.S. population. Image 1, below, shows the projected growth of ethnic diversity among younger Americans through 2065.

People between ages 15 and 24 make up close to 20% of the world’s population. Further, by 2025, millennials (those born between 1980 and 1996) are expected to comprise three-quarters of the global workforce. Younger and increasingly diverse populations often bring with them evolving expectations and a willingness to bring D&I to the forefront of societal conversations.

Figure 1: Changing Face of America,1965-2065 (% of the total population) | Source: Pew Research Center 2015 report, "Modern Immigration Wave Brings 59 Million to US, Driving Poplation Growth and Change Through 2065" | Note: Whites, black, and Asians include single-race non-hispanics. Asians include Pacific Islanders. Hispanics can be of any race.

In addition, workplaces are becoming more multicultural with global talent moving across countries and positions. Non-traditional forms of work continue to gain popularity, such as freelancing, virtual work, and short-term project-based assignments.

There is also a shortage of talent that is especially acute in knowledge industries. The financial and business services industries expect a shortage of 10.7 million candidates by 2030, which will continue to fuel this upward trend in global talent interconnectedness. These workplace changes in demographics, non-traditional workforces, and talent shortages are strong forces pushing diversity and inclusion to center stage.

The amplified attention on D&I is also due to its increasingly well-documented relationship to business outcomes. Research shows that more diverse and inclusive organizations outperform those that are not. A survey of 1,700 organizations across eight countries found that organizations with above-average total diversity had both 19% higher innovation revenues and 9% higher margins.

Therefore, organizational leaders are increasingly seeing D&I as critical to achieving financial goals. These trends, accelerated by the rise of #MeToo in October 2017, created a seismic shift in the discussion around sexual harassment that has spilled over into other diversity and inclusion topics such as gender identity racism, ableism, sexual orientation, national origin, age, veteran status, religion, and more. For example, 56% of millennials believe that “business leaders have a greater responsibility to speak out on social issues now than in years past.”

This growing and collective frustration has increased the desire for a new approach to diversity and inclusion.

We’re about two-thirds of the way through our research process for our people analytics technology (PAT) study, so thought we’d provide three initial insights on what we’ve learned to date. (Please note, this research is ongoing.)

And now, without further delay, let’s move on to what we’re learning…

1. It's all about the Benjamins. We’ve known for a while that the PAT market was receiving significant interest from the investment community – a point that was underscored by the $45 million Series D investment in Visier in 2017. However, our analysis of the market shows that interest has continued with great enthusiasm across the last few years. For example, in 2018, Humu raised $30 million and Culture Amp raised $40 million, among others. Earlier this year, Peakon raised $35 million in its series B, and Perceptyx just announced today a strategic investment from TCV, a private equity firm. New players, like Cultivate, are also off to the races with fair-sized seed rounds. There’s also been significant investment in people analytics technologies as a result of people analytics vendor acquisitions where the acquirer intends to invest significantly. Prime examples of this are Glint (acquired by LinkedIn/Microsoft, but had raised $80 million beforehand), Shape Analytics (acquired by Reflektive, which itself received a $60 million series C investment in 2018), and of course, Qualtrics (acquired by SAP in late 2018). And finally, there is Medallia, which just had its IPO last month, which provided it with plenty of cash to invest.
2. Mo’ money… All that money appears to be making an impact, if you ascribe to the idea that more investment should eventually equal more revenue. Now, we aren’t going to spoil the surprise of our research by giving overall market growth numbers here, but we will tell you that nearly all vendors are reporting accelerating revenue growth, with 2019 looking to be the best year yet. In addition to the significant investment mentioned above, additional reasons for this revenue growth appear to be a healthy economy, broader corporate investment in people analytics teams, and people analytics teams’ increased sophistication (and therefore ability to use some of these tools).
3. …Mo’ (user) problems? But there are some challenges ahead. As these vendors grow, they are looking to expand their user bases (the old “land and expand” approach) within existing customers. However, people analytics tech isn’t like a lot of other tech. First, not everyone should have access to the insights available within people analytics technologies – at least not carte blanche. Second, there are a wide variety of users within any given organization who have varying levels of data maturity, which requires different levels of sophistication and customization of dashboards, data structures, and data analysis tools and capabilities. Third, most of the vendors’ technologies were originally built to cater either to really sophisticated people analytics teams or to less data savvy HR business partners.

This combination of issues is resulting in challenges for these vendors as they try to expand their user bases. Essentially, we are seeing:

• Really sophisticated technologies trying to simplify aspects of their tech for a less data-savvy user (but the technology still being too difficult) OR
• Less sophisticated technologies struggling to make their technology adequately sophisticated for people analytics teams to justify the investment (versus those teams building it themselves)

As a result, we’re seeing instances of product/market fit when it comes to secondary users (the ones to whom these vendors must expand their offerings). Vendors are aware of this challenge (in some of our practitioner interviews, less-than-expected end-user adoption rates have come up as a real issue), but the path forward for many of them is not totally clear. We expect we will see some vendors shift their target users or potentially break up their offerings into more discrete packages to make it easier to build for and sell to different users. We see this as being one of the critical issues many PAT vendors will have to solve for in the coming 18 months.

We are analyzing our people analytics technology vendor data, and will be uncovering a lot more insights in the coming weeks. If you’re able to join us at PAFOW Philadelphia, September 5 & 6 for the sneak peek of the results, we strongly encourage you to do so! Otherwise, stay tuned here for more information on this research.

We just had a wonderful preliminary meeting with members who will be joining us in Washington D.C. for our collectives on Building Skills for the Near Future. In all, around 40 leaders joined and participated in an open exchange of ideas.

Below is the mind map of that discussion. Click in the box to explore! As always, we'd love your comments or thoughts!

On July 31, 2019 we conducted the second roundtable in our Performance Management study. We sincerely appreciate the group of thoughtful leaders (you know who you are) that came together to review some of the initial numbers from our survey and provide their insights and experience

The highlights from that hour-long web-chat are succinctly outlined in the mind map below. Big branches represent main discussions, smaller branches represent some of the responses and detail.

Click in the graphic to make it bigger, move it around, etc.