Conversations for Change: Powertilt: Examining Power, Influence, and the Myth of Meritocracy” With Dr. Catherine Ashcraft and Dr. Brad McLain

Evidence demonstrates that even when tech companies diversify their workforces, members of historically marginalized groups still face difficulty accessing core innovative technical roles. This lack of influence in key innovation processes results in what we term a powertilt phenomenon — that is, a differential distribution of power and influence along lines of gender, race, and other intersecting social identities. We present findings from our study examining what counts as power and how it operates on technical teams and provide an overview of a practical assessment tool that leaders can use to assess how power and influence are distributed within their teams. This instrument also helps teams implement strategies for creating more inclusive team cultures that improve team decision making and technical innovation.

Resource: Powertilt – Examining Power, Influence, and the Myth of Meritocracy

Originally aired on May 16, 2022


JOANNE ESCH: Hello and welcome, or welcome back, to the 2022 Virtual NCWIT Summit on Women in IT, which continues to be the world’s largest annual convening of change leaders focused on significantly improving diversity and equity in computing. My name is Joanne Esch. I’m a senior research associate on NCWIT’s Social Science team, where, among other things, we develop research-based strategies for building cultures of inclusion and belonging in technical workplaces. 

We’d like to thank the sponsors that make this event possible, and thank you in advance for your patience, should we experience any bandwidth or other technical issues. I encourage you to post your questions and comments on the Q&A board throughout the session, or upvote questions that you’d like to have answered, and we will answer as many as possible throughout the workshop. 

Before we begin, a quick welcome from one of the Summit sponsors, PNC Bank. 

DEB LINDWAY: Hello, Joanne. Thank you, and thank you very much. I’m really excited to be here today for this session. My name is Deb Lindway, and I work in Enterprise Technology and Security Business at PNC Bank. My responsibilities include our Intelligent Automation Center of Excellence, our Quality Engineering Center, and Business Delivery Enablement across all of tech and security. 

At PNC, you know we are really proud to be members of the NCWIT Workforce Alliance. We have been proud members since 2016. I have had the honor to be in some of the NCWIT opportunities, even going back to my former employer several years prior to that. PNC is thrilled to be a sponsor of this year’s 2022 NCWIT Summit. 

At PNC, our all-inclusive culture means that every employee matters to us and is truly empowered to contribute to our success. We strive to create a culture where our employees are encouraged to really bring their authentic selves to work, to share their diverse ideas and backgrounds, to help us collectively deliver an exceptional customer experience with new capabilities coming from the technology space. In technology, attracting and retaining women tech talent is truly a top priority in building out that strong and diverse workforce, which we know is so integral to our success. 

So again, thank you all for joining today. Really excited about the session coming up. Again, thrilled that we could be sponsors of this year’s event. So Joanne, thank you very much. I will turn it back to you. 

JOANNE: Thank you, Deb. We appreciate everything PNC is doing to help increase equity in this industry.

Let’s get started. I’m excited to introduce my colleagues – Dr. Catherine Ashcraft, Director of Research; and Dr. Brad McClain, Director of Corporate Research – here at NCWIT. Today, they’ll address a critical question for building inclusive technical workplaces. That is: How can we measure not just diverse participation, but influential diverse participation? Because increasing diversity in terms of headcounts is important, but isn’t enough if we want to create team cultures where everyone can participate meaningfully and influentially in the innovation process. Catherine and Brad, over to you. 

DR. CATHERINE ASHCRAFT: Thank you, Joanne, and thanks to all of you for joining us. It’s great to be back with you to talk today about how power and influence operate on technical teams. 

For those of you who were in the first session, you know that we kicked off this conversation with a talk by Julie Battilana. She talked a little bit about what power is, some misconceptions about it, and how people can access it in a general sort of way. So this session, we aim to build off of that session, and dig a little deeper into how power operates, like I said, on technical teams, in particular, and in technical organizations. 

We want to take a closer look at some findings through a pilot study we have conducted with several tech organizations on this topic, as well as give you a sneak preview of a practical tool that we have developed to help technical teams assess how power is currently operating on their team, as well as ways that they can improve the distribution and develop more inclusive forms of influence and power distribution. 

That’s a little bit of an overview of what we are going to do today. We do want this to be as interactive as possible as with a large group that we can’t see people, but we have some mechanisms for doing that. So, we are going to have some opportunities for chat, and polling as well. But also, like Joanne said, please go ahead and put your questions in the Q&A along the way, and we will try to be handling those throughout the session in a more kind of workshop style. So, that is the plan. 

But first before we dive in, just a little context, again, on why this is an important topic. As you can see here, I think most of you know by now that we have a lot of research over the past 20 years that demonstrates that diversity is very important and has significant benefits for productivity, innovation, and the bottom line; the so-called business case – and that, in general, this research shows that groups with greater diversity solve complex problems better and faster than homogenous groups. So, we won’t be going over that research today, but you can see at the bottom of the slide, if you are interested in seeing a summary of a lot of that research, you can access that at the link at the bottom of the slide.  

But, we also know that getting diversity in the door is not enough. Right? So, it depends on how that diversity is managed and activated. We know also, from additional research, that even when present in the organization, marginalized or minoritized groups often face difficulty in accessing power and influence, and in accessing core, creative, innovation, technical roles. So, we have designed this project.

We don’t have a lot of ways to assess this, right? However, we are very good at assessing headcounts. So, what we will talk about today is headcount data, and the number of people, or the percentages of people by gender and race, in a technical organization. We can count them, but we don’t have a good sense, or way, of assessing what they’re actually doing on a day-to-day basis, and to what extent they can meaningfully and influentially contribute to technical innovation. So, those are the kinds of metrics that we are trying to develop in terms of this Powertilt project.

We want to do this so that we can move beyond this focus on headcounts. That is really, as of today, the primary way diversity efforts measure progress. We want to move beyond headcounts because, I’ve hinted at some of the reasons, but there are many problems with relying primarily on headcounts. Brad is going to tell us a little bit more about some of those. 

DR. BRAD MCLAIN: Yeah. Well, one of the biggest ones, as you can see from the bullets right here, is that it takes the focus away from culture. You know? A headcount, if we think of it as the finish line, is fairly easy. It relegates diversity, equity, and inclusion to a pipeline issue and a pipeline issue alone. But as we often say in our workshops at NCWIT, which many of you will be familiar with: If the pipeline leads to a sewer of a culture that doesn’t promote inclusion but actually promotes exclusion by default, then people won’t stay. 

So, we need to move beyond headcount. Or, use a headcount, maybe, as the starting line, but not the finishing line. So, what we want to do is: refocus on the experience, the culture, the everyday workplace that we all live in and work in on our teams, even today as we enter the endemic stage of COVID and are working in a hybrid fashion. Most of us are partially online, partially in the workplace physically. The culture is still needing attention in order for inclusive and meaningful participation to be built. 

So, we need to ask questions. What kinds of jobs are people doing? Who has access to the most influential and powerful jobs? How can leaders promote greater participation in order to reap the benefits of diversity that Catherine was just talking about? 

Before we dive in, let’s move to our first interactive segment and find out a little bit about what you think about these issues. To do that, we are going to do a poll through the chat. 

CATHERINE: So, I’m going to put the link. 

Just as background information, our Zoom polling functions were disabled. So, we are going to do this a different way. I am putting  a link into the chat that, hopefully, everyone can access now. 

So, if you click on that link, it will take you to a separate screen interface where we will run the polls, and you can answer, and submit your answers, from that screen. Then, we will discuss them. We will also have you put some responses in the chat, as you are willing, based on explaining, maybe, why you chose the answer that you did.

This is going to be similar to if you’ve done a Take a Stand with us before. These polls are going to be statements that you agree with or disagree with, from anywhere to strongly agree to strongly disagree. So, we will start with the very first one. Are we ready? 

“Power is something we explicitly talk about in our organization.” Go ahead and indicate whether you strongly agree to strongly disagree. If you can, put in comments in the chat as to why you answered the way that you did. We’ll also attempt to discuss some of those. 

Give it a couple more seconds. Okay, I think that is the bulk of people answering. So, we have kind of a broad spread, but mostly in the strongly, or the disagree, category. 

All right. Terry says she’s never had a conversation about power with anyone, either below or above, in my organization. 

Take a few minutes to read other people’s comments in the chat. It does make people uncomfortable; talking about power. 

All right. Are we ready for the second one?  

BRAD: I think so. We have three, right? 

CATHERINE: Yes. We have three. All right. 

The second one: “When it comes to measuring diversity, our organization primarily collects headcount data.” For those of you who disagree or strongly disagree with this, we’d be interested in hearing in the chat what other data you might collect. 

All right. I think that is the bulk of it, too. So, most of us tilted toward strongly agree, agree side. All right. Ready for the last one?

BRAD: Ready to go. 

CATHERINE: “Our organization has good ways to measure how power and influence operate.”

A few more coming in. All right. This one skewed heavily toward the disagree, strongly disagree. 

BRAD: Not surprising, as we’ve seen.  

CATHERINE:  Taking a look at some of the chat. Yeah.

So, talking about influence being a huge part of the culture but not having a way to talk about it, or measure, or have metrics associated with it; yes, you are not alone. Hence, the reason for this project. 

BRAD: All right. Well, let us tell you a little bit about our Powertilt study. 

If you are on your browser, go ahead and navigate back to your Zoom meeting. We are sharing a screen there. We will have some opportunity for more polls later on. We will toggle back to your browser at that point, but go ahead and go back to the Zoom meeting if you haven’t already. 

We’ve been engaged in a Powertilt pilot study for about the last two years. That includes our Social Science team here at NCWIT, as well as five very brave and curious tech companies that are members of NCWIT who are helping us collect the data. What is this all about, and why do we care? Well, these poll questions were kind of priming us for why we should care. 

We needed to ask some questions about what meaningful and influential participation in tech looked like, and who has the most access to it, and why. These are the questions that we started out with when we embarked on the Powertilt project. 

“How do power and influence operate within technical teams engaged in innovation?” We are especially interested in how innovative teams make decisions. So, zeroing in on the general power theory that we heard earlier this morning from Julie, what does it mean when that’s applied to the decision-making process on a team of five, or 10, or 25 people; those teams that are actually inventing the tech that we all use today on the front end or the back end? 

In those teams, “what counts as power and influence” in their cultures? What makes someone able to influence team decisions? You know, not trying to coerce other people as much as affect the outcomes of decisions, or challenges, that the team is facing. 

“How do people’s actual experiences compare to their ideals around who influences team decisions?” In other words: We love the idea of a meritocracy, but in reality, we fall short of it. 

How are the gaps between those ideals and the actual ways that teams make decisions? How do they operate?

“How is access to power distributed among teams in terms of gender, race, ethnicity, age, class,” and other identity categories? That’s a big one that we’re addressing. 

Finally, “how can individuals and teams improve cultural factors,” especially the leaders, “to increase access to power and influence?” That’s all about reaping the benefits of diversity and inclusion after going through the trouble of assembling diversity around the table. It’s only good if we can activate it. So, these questions have enormous leadership implications. 

What we would like to do next is: share with you a video that we created for the recent Stanford conference on social innovation and change. It’s a 10-minute video. I’m going to share my screen so you can watch it. I’ll crank up my volume all the way that I can, but you can ride your volume on it up and down on it as you like. After the video is over, we will entertain some Q&A. So as thoughts may occur to you, go ahead and put it in the chat or the Q&A. We’ll take a few moments afterwards. It provides a really nice summary of the Powertilt pilot project, and the findings from that research, in a very engaging way. So that said, let me switch screens. 

Taking it away. 

[Video starts]

What counts as power and influence in tech today? Specifically, how is power used responsibly on technical teams engaged in innovation, and what happens when it is abused? How is access to power distributed among team members, particularly in terms of gender, race, class, and age? In this session, we aim to address these questions, exploring what we call a powertilt phenomenon. 

Despite 30 years-plus of diversity and inclusion efforts, a relatively homogenous slice of the population – disproportionately white and male – still creates the bulk of the technology that so profoundly shapes our world. We understand now that simply increasing diverse headcounts is not enough. Even when companies increasingly diversify their workforces, members of historically marginalized groups still face disproportionate difficulty accessing core, creative, technical roles, and influencing work team decisions; the place where innovation really happens. 

This is what we call a powertilt phenomenon. That is, a differential distribution of power and influence along lines of gender, race, and other intersecting social identities. This powertilt ensures that influence and innovation remains, primarily, a majority-group advantage. Our powertilt research is setting out to change that. 

Why focus on teams? Recent research, from patent studies to team cognition and decision-making, demonstrates that innovation in tech increasingly happens at the team level. This runs counter to the persistent – and persistently wrong – notion that innovation occurs at the level of the individual. We like to call this the “myth of the young rock star.” So powerful is this myth, that it has shaped our concept for what top talent looks like, distorting our view of who we should all stumble over each other to hire. 

Not only are teams increasingly the site of innovation, it has also been demonstrated that teams with greater diversity solve complex problems better and faster than homogenous teams – with one big caveat. In order to reap the benefits of diversity, leaders must activate the different viewpoints and life experiences on their teams, and ensure that all team members influence decision-making and innovation. Making this happen is all about team power dynamics; assessing and understanding how power operates, and who can access it. The way teams approach decision-making tells us a lot about their culture, how inclusive they are, and how they think about innovation. 

Culture and influence create each other. What counts as effective influence indicates the kind of culture you have. Conversely, the culture you have determines what kinds of influence are effective. This mutually-defining cycle challenges traditional assumptions about how influence in tech works, which we call the “myth of meritocracy;” or, the belief that the best ideas and most qualified people are the most influential. Merit is part of it, but influence also depends on who is exerting it, and the expectations and biases associated with that person’s gender, ethnicity, age, title, etc. Simply stated, influence is not that simple. 

In our Powertilt pilot study, we began by asking how team members perceive the power dynamics in their teams. Takeaways from the investigations fall into two main categories. One, perceptions of what characteristics and behaviors are most frequently influential in technical team decision-making. And two, gaps between how influence actually operates and how people wish it operated on their team. Let’s take a look. 

Our pilot findings show that the top influential behaviors were: addressing other team members’ needs or perspectives; presenting relevant data or information to make a compelling case; building coalitions among team members; and compromising with other team members.  The top four influential characteristics were: subject matter expertise; having a positive reputation; official title, or position; and being well-liked by other team members. 

Certain characteristics were reported to be more influential than people desired. These included: one’s title, or position; being well-liked; having budget control; and seniority.  But for behaviors, only “dominating the conversation” was reported to be more influential than people desired. 

Lastly, we asked respondents about their team’s decision-making styles. The top three reported were: decisions were made by perceived experts on the team; decisions were made hierarchically, but with group input where the leader makes the final decisions; and lastly, decisions were made by majority rule. 

So, what are some things we’ve learned from these initial findings? First, there is a clear mismatch between our aspirations for meritocracy and the difficulties in actually achieving it. Characteristics – like one’s title or position, being well-liked, or dominating the conversation – are not well-aligned with merit-based influence. Indeed, participants felt these characteristics and behaviors were more influential than desired. Awareness of, and attention to, this mismatch is an important first step in creating inclusive cultures that foster broader access to influence. 

Second, it is important to recognize the way that myriad biases play into accessing even the types of influence that initially seemed more based on merit, such as subject matter expertise, having a positive reputation, and presenting relevant data. Consider, for example, the complexities in how one comes to be known as a subject matter expert, or how one develops a positive reputation.  

Research has shown that biases related to race, gender, and other social identities greatly affect opportunities to demonstrate ability and to prove oneself. Task assignment, for example, is something that is largely out of each individual contributor’s immediate control, and is notoriously subject to bias. The types of assignments one receives, however, greatly affects one’s chances to build a track record of success, and therefore, a positive reputation. 

Opportunity then begets more opportunity, creating a positive feedback loop that can accelerate career progression and ability to influence. In this way, this reputation reinforcement spiral spirals up. Reputation reinforcement spirals can also spiral downward when one simply does not have access to those valuable task assignments, or produces negative results. A negative reputation may result. This can have a chilling effect on risk-taking culture so important to innovation. 

In the current stage of this study, we have developed a powertilt assessment tool that helps teams and leaders identify: one, the primary ways power operates in their team culture; and two, patterns in who might be favored, or disadvantaged, by the current culture of influence, particularly in terms of intersectional identities related to gender, race, class, and age. 

Powertilt tool includes three parts: the team decision-making distribution typology, which identifies a team’s decision-making style, and how power is distributed or concentrated on a team; the team influence profile, which identifies the characteristics and behaviors that are the most influential within a given team’s culture; and the individual influence profile, which identifies how powerful and influential individual team members perceive themselves to be in their team’s decision-making. 

Each team member takes the assessment individually and then reconvenes with the larger team to discuss their individual results compared to the team’s aggregate results. Once these influence patterns have been identified, the tool will guide technical teams through the process of having important conversations about these patterns. It will then help them identify concrete actions to improve the way influence operates in these teams, and enhance inclusion and innovation in the process. 

By examining how power operates and who has access to it, we move well beyond diversity headcounts and provide a new metric to help organizations broaden meaningful participation in computing and unleash the innovation potential that diversity brings. 

For more information on this project, or our other ongoing research and consulting at NCWIT,  visit

And thank you for your time and attention. 

[Video ends]

BRAD: All right. Fantastic. Well, before we move on to the powertilt Assessment Tool, we want to give you a look under the hood, and try it out. We will pause here for some questions in the chat or the Q&A, which I believe Catherine has been monitoring.  

CATHERINE: Yes. So far, we just have a question about when we examine diversity and innovation: “Is being an immigrant, male or female, a diversity category?” So, yes. It’s a dimension of diversity. 

We should say, possibly, that the Powertilt project, you can think of it as on two levels. One, it’s an assessment tool that teams can use as a practical way of improving influence. Well, first assessing how influence and power are operating, and then improving it in their own technical teams. But then, it’s also a larger research project. So, we are collecting that data across companies, across industry. Then, we can disaggregate it by various dimensions of diversity. Which, immigration could be one of those dimensions, as well as gender, race, ethnicity, and other kinds of demographic categories. 

BRAD: Yeah. In fact, right now we’re entering Phase 2, with the pilot study done and the tool assembled, which you’ll see in a second.  

The Phase 2 is to expand the sample size across the tech industry, and across companies beyond the five original companies we worked with, in order to do the disaggregation. Where is power and influence distributed, and where is it not, along the lines of identity categories? We have some hypotheses, as I’m sure you can imagine, but we don’t have the data. The data will, no doubt, lead to more questions and nuances on how we can improve leadership.  

CATHERINE: We have a second question about veteran status: I understand this might not be relevant in all situations, but have you also collected data on military veterans and retirees to see how that experience changes perspectives?

We have not done that, to date, but that is certainly a possibility that we could look into that sort of dimension. Also, feel free to put.. I see some of the questions are going to the hosts and panelists, which we can see, but feel free to put them in for everyone if you want everyone to see your question. But, I’m going to go ahead and read them, so the people who can’t see them…

That’s what we have so far. So, unless there are … At least, as far as I can tell. Let me just check. Yeah. 

BRAD: What we have for you next is a chance to do what our participants in the pilot study did, and that is to answer some of the questions from the tool – the powertilt tool – in order to gauge how your experience working on your teams compares with others. As Catherine mentioned, the benefit of using the tool is at the team level, because you can see your results for your team. Then, discuss it, and discuss explicitly how power and influence operates on your team in order to, hopefully, distribute it more to the people who are there. 

But also, the aggregate of this study allows us to compare across the nation and internationally. Today, we are going to compare across the participants on this call. As you recall, there are three categories. 

The team decision-making distribution typology, which is a fancy way of saying your team’s decision-making personality type. If you have ever had a Myers-Briggs or something like that, it gives you a little code. Well, the first three questions we will share with you are all about that. What does your team think? What do your team members think about how decisions are made? That is what that is all about. 

The second part is the team influence profile, which is to say, which characteristics and behaviors are the most, and least, influential when your team is making decisions? 

Finally, the third part: the individual influence profile. How influential do you think you are on your team? How much power do you have? It is all anonymous, so we are going to move again from the PowerPoint to the same link, I believe, but Catherine is going to repost it in the chat. 

CATHERINE: I did. I reposted it in the chat. So, you can access it again there. 

BRAD: Great. I will share my screen as well when I go over there, but it’s probably best if you are on your browser before we come back to the PowerPoint later on. 

CATHERINE: So, this is just an informal way of doing this; this isn’t actual. The real assessment is done through different software. We are doing this through the polling features so it is all anonymous, and it will be displayed differently in this case than it is actually when we do it for real. This is just to kind of give you a feel for it, and what it’s like in the kinds of questions.

If you aren’t a member of tech, it’s going to ask you questions about your team. So, you can be thinking about whatever team you want, and kind of just make up answers for the sake of experiencing, or playing with, the assessment itself.

BRAD: Dummy data. Yep.

CATHERINE: Like Brad said, we’re going to do the first three questions as a set. So, I am going to start those three. Then, he will probably walk you through the process of navigating between them. These are three questions related to the team decision-making typology; how your team goes about making decisions. The first is to please describe the formal power structure of your team as you see it. 

We see some answers coming in there, in terms of very hierarchical versus flat. It’s okay if you are not completely sure what those terms mean, or how you define them. You can define them however makes sense to you, and then, that comes out in the discussion. 

BRAD: Now, you can navigate on your browser to the next question. There are three questions in this step. I would encourage you to do so. I am doing so as well, as I share my screen. Then, you can navigate back-and-forth with the previous and next buttons as more people chime in, and our response rate goes up.   

CATHERINE: Feel free to put, again, explanations for why you answer the way you do in the chat, if you’d like. 

BRAD: Well, we have more than half of the participants responding. In social science, we think that’s pretty good. It could always be better, but you can see we are all answering for our different teams, of course, which is a fly in the ointment here. Ideally, we all look at data from our own perceptions of the same team. Our experiences of the same team’s culture can be very different. But, aggregating the data across several different teams is what we are doing today in this poll. 

So, please describe the formal power structure of your team as you see it, from very hierarchical to very flat. Most of us are falling into the categories of hierarchical or very hierarchical. This is traditional, command-and-control-style leadership, or what you might think of as org-chart leadership. 

I thought it was very interesting this morning when Julie pointed out that the org chart doesn’t necessarily map the power structure of an organization or a team. In many ways, if we are not paying attention to power, it is invisible to actually how it operates. This is very similar to the findings we had in the pilot. 

The next question was: “In general, please describe how people contribute to your team’s decision-making process.” Everything from “only one voice really matters – the leader’s,” to “a few voices consistently contribute more than others.” That’s where we have the biggest answer, as well as “most voices consistently contribute” to “all voices.” This is also in line with our pilot study, where a few voices consistently contribute. 

That is to say, it’s somewhat hierarchical, in this sense. But then, the question is: What is it about those few voices that allows them to have influence? Which, we will get to next. 

Finally, “please describe how final decisions are made on your team.” “The leader decides.” Now, that may be with group input, but the final buck stops here. “The leader decides” is the most common here, and in the pilot. What’s an interesting thing? The distribution among these other ones, with majority rules, minority rules, and consensus – which is very hard to achieve. 

CATHERINE: So now, the way this works with the full assessment is: You would complete these questions that are associated with the typology. Then, like Brad said earlier, based on the answers of each individual team member, the team is assigned a personality type. There is a series of eight personality types that this would lead to.

Then, like we said, every team member takes it individually. You get the personality type of however you perceive the team to be operating. It may differ from the personality types that come from other individual team members, based on their responses. 

So, the next step, then, is for the group to discuss the differences. There is a discussion guide that prompts, that helps facilitate this kind of discussion with the team so that the team members can discuss their different perceptions of how the team goes about making these decisions. 

I am just checking the chat now. Right, so some people are talking about collaborative teams, but the decision is made by the leader – but there is collaboration going in. And, somebody who feels their PhD advisor is a dictator. 

Probably not the first time that’s happened. Factors in here about what shuts down discussion. Yeah, and again, make sure if you want everyone to see that you are posting the chat, comments to everyone; not just the host and panelists. 

BRAD: One pattern that we saw in the pilot, by the way, was that the leaders of teams often felt that their teams were much flatter, and more collaborative, than the members of the teams thought. The members of the team would often say it’s more hierarchical. Then, after seeing the data, the teams had a lot to discuss in terms of those gaps. Just to show, again, those who have power and those who don’t have power experience the culture and the participation opportunities very differently. 

CATHERINE:  This is a great question. We get this often, actually. Before I start talking about this: “Is the suggestion that non-hierarchy is best, and doesn’t that potentially devalue how hard women are worked when in a diverse setting?”

We actually don’t intend to suggest that hierarchy is best, or that non-hierarchy is best. What you’ll see when you get the typology is a continuum that shows a distribution from most concentrated types of power to most distributed. But we do try to make the point that this isn’t necessarily evaluative in that simple of a way, where the goal is always to be on the most-distributed or less-hierarchical side. Because it depends on the kind of decisions being made, it depends on the context; it depends on a lot of things.

So, sometimes a fairly concentrated decision may be what the team feels is a good way to go, but sometimes, a more distributed decision is. It’s opening the conversation around that, but yes; the assumption sometimes is that the least-distributed or non-hierarchical is the implied objective, but that is not necessarily the case. 

BRAD: Some prior research, which was identified by our research associate Joanne Esch on the call today, had previously established that teams that are more interested in efficiency and speed in decision-making will often resort more to hierarchical decision-making, where those that are engaged in exploration, or problem-solving innovation, are more likely to benefit from more collaborative decision-making. There are a few studies to show that, but the jury is still out on how it operates in tech cultures today. 

All right. I think we are ready for set two. 

CATHERINE: Yes. All right. Let me start those.

This is for determining the kinds of characteristics and behaviors that are most influential on your team. We’re going to start with characteristics. Then, you’ll have a second question that asks how satisfied you are with the situation. 

The way? Let me do this. You can rank each of these. You will see the characteristic listed, like official title or position, subject matter expertise, etc. One, meaning that it has very little influence or it’s not so important in the decision-making or who has power, to four, being it’s very important. 

BRAD: Don’t forget to scroll down on this screen. You won’t be able to see each of the categories at once. After you get to the bottom, you will see a big button that says “submit your answer.” I encourage you to do that. When you do, you can scroll down even farther to see a data chart, which I will walk you through in just a few seconds. 

CATHERINE: Then also, when you are done, go to the second question about how satisfied are you.

BRAD: Oh, thank you. Yeah. While you are waiting, that is perfect. 

Okay, I am navigating back to the first question of this set, down to the results; scrolling down to the results section, where you see some nested polygons. This is a distribution shape chart. 

What you see here, if you have looked at these before, is pretty cool. Your vote, your personal response to all the questions, is shown in green. The average from everyone who has responded to this is shown in blue. So, what we look at here is: where the distribution falls. 

For example, we have a pretty circular distribution of blue. The shape of the blue is not leaning towards one side more than the other too much. Although, it is leaning toward the right side of the graph a little bit. That is to say, that official title and position, subject matter expertise, demonstrated track record or positive reputation, and being well-liked are more influential than some of the items on the left. However, institutional knowledge has a spike off to the side. 

That’s how we think, together, about our various teams that we work on in our various institutions. How you think about your team is represented by the green shape. So looking where it is skewed, or leaning, gives you an idea of how that works. Now, there’s very powerful data, if you are looking at your team together with your other team members in order to see how your team’s influence works on the individual level. 

Moving on to the second question. “How satisfied are you?” turned out to be a very important question in the pilot study. Now, the question is: “How satisfied are you with the way you think your team is operating?” That is the question. So, we would see the distribution of satisfaction. 

Our sample size is pretty small, so we’re going to approach this in Phase 2 with a larger sample, but it seemed to indicate that the people who have more power are more satisfied. Again, not too surprising. But if you don’t have access and opportunity to power, your experience of the workplace is less satisfying, is the suggestion. It remains to be tested, but it certainly follows common sense. 

All right. In the interest of time, I think we should, maybe, take a couple questions – if there are any – and move on. What do you think, Catherine? 

CATHERINE: Yes. I was just looking at the chat. There’s a couple really interesting questions about, or comments about, the subject matter expertise. Thank you for those, Giovanni and Judy.

“I find it disappointing, when subject matter experts – especially women and other people of other, less-privileged identities – are ignored for other traits, and dealing with not being listened to for long periods of time until the manager finally admits that the subject experts were right.”

This relates, I think, a lot to some really, very important points that relate to some of the things we were noting in the video about this whole idea subject matter experts as well. It seems, maybe, like a foregone conclusion, but we know, also, that lots of biases play in who gets seen as having subject matter expertise, or having a demonstrated track record. I think there are lots of complications there that are important for the team to talk about. So, in the discussion guide, we have some follow-up prompts about: could it be that there are subject matter experts that you’re not recognizing, or that aren’t recognized as such because of other kinds of implicit biases?

BRAD: Certainly, moving us away from the notion of a meritocracy. 

All right, do we have two question sets left, or just one?  

CATHERINE:  We have just … Well, we can do one or two. 

BRAD: Okay. 

CATHERINE: Yeah. The influential, and here’s the behaviors.

BRAD: All right. The previous question was about characteristics that a person has, or traits. This question is all about behaviors; actions that they take in team settings. 

Same drill as before: two questions, ranking 1 to 4, submitting your answer at the bottom as you scroll down. Then, you can move on to the satisfaction question.  

Oh, is there…

CATHERINE: There were just a couple other comments, so I was just going to say: Just to clarify that when we chuckled about the PhD advisor dictator, that was in solidarity and support, having recognized those dynamics ourselves. 

BRAD: Yeah. Two times for me, but okay. All right. Taking a look at some of the data.Under the results, you have 25 people chiming in; 26. So, the shape is changing every time somebody else inputs new data – which, I find very cool. 

In any case, again your vote is shaped in green, and you can see what your perceptions of your team are. The average from all of us is shaped in blue. Here, we have kind of more of an egg-shaped distribution, where we have a skew towards “addressing the needs of others and the perspectives of others,” and also, “frequently speaking up” and “presenting relevant data” on the bottom. But, not so skewing towards the sides. This, again, is in line with the pilot findings. 

Which was a little surprising to us, that “addressing the needs and perspectives of others” was ranked as highly amongst all of these choices as it was. It was very encouraging. It indicates team members are listening to each other, and having a voice. 

But again, coupled with the data that says not everyone has a voice. We have to then ask: Well, whose needs and perspectives are being represented, and whose are not? Then, we can ask the question: Why is that? 

Thirty-nine people; 40 people now. Still seeing a basic shape. 

CATHERINE:  All right. Do we have time for one more? 

BRAD: One more? I think we do.

CATHERINE: Okay. This moves us to the individual influence. That was the focus of the team: influence. The next two questions ask about your own individual influence. 

“How much influence do you have on your team decision making?” Then, “how much influence do you think other team members think you have on team decision making?”

BRAD: After you click on your answer, you’ll get the “next” button.  

CATHERINE: Then meanwhile, the question in the chat, or the Q&A: “How can we improve team dynamics to make the situation better and more feminist?”

That is one of the goals; to make the team environment more inclusive, both in terms of gender, and race, and other intersecting identities. In a second as we close out, part of the design of the tool is to have people discuss these dynamics, and to consider ways they might improve on just those kinds of dimensions you are talking about. At the end, before we leave, we will have a quick slide that shows some brief suggestions – very high-level suggestions, but there’s more where that comes from. 

BRAD: Going back to the first question here as there are a few more people chiming in, you see the data distribution here. As is expected, people perceive themselves – especially on a smaller team, if you have five or 10 people on your team – to have about the same as most other team members, about the same level of influence. That is also more common among the majority group members than it is among marginalized group members. So, breaking this data down by identity class gives us more illumination about the structure and culture of a team. In fact, it is a team’s chance to look in the mirror and see the different reflections that people are seeing differently. 

The second question: How much influence do you think other team members think you have? This is called a reflected self-appraisal. It’s what you think others think of you. In this one, we can see a greater distribution that we saw in the pilot as well. The big one here is, of course, that people, you, think that others think they have more power than they do, for whatever reasons.Now, the question, of course again, is disaggregating this by identity category; is that true for majoritized and marginalized group members, or is there a distribution that we need to look at there? 

The pilot study was too small of a sample to draw conclusions, so we are not presenting conclusions on it. So, we are not presenting that data. But Phase 2, which we hope many of you will decide to join – and your organizations – to help us compile a greater amount of data, will allow us to disaggregate by identity category, and layer down into these questions more deeply. With that, I think a couple Q&As, and then, we’ll move to our closing. 

CATHERINE: Yeah. I think we can show the last slide that has the initial suggestions; some of these suggestions I was just referring to, about ways to improve inclusive influence. These are some high-level suggestions. Again there’s more detail with the full toolkit. 

Then, yes, also we want to invite people. We are looking to test this on a broader scale, like Brad said. So, there will be information on ways to contact us if you want to participate in this larger project. You can see the links there too, or you can find more information. Although, something has gone blurry on the screen.

BRAD: Oh, is it mine?

CATHERINE: My screen. It’s back now. Okay.

BRAD: Some of our workshops, and many of you will be familiar, touch on invitational leadership, which is a different style than commanding and control, or other traditional leadership modes. Doing a powertilt assessment with your team is a step into that invitational leadership space. 

Some of the research-based best practices are listed here, many of which leaders commonly do – but of course, their great power is in constellation with each other. So, when you put more than three or four of these together, it greatly influences the culture of the team and how the team decision-making is made. So, take a snapshot of that. We’re not going to have time to unpack each of these, since it’s not a workshop about that today.

On the right, the Powertilt pilot working paper is on the NCWIT website. It goes more deeply into the theory and research behind what you experienced today, as well as next steps for the study, which we hope you will contribute to. As you know, NCWIT is all research-based, but that only works with the partnership, sponsorship, and participation of our member organizations. So, what we hope is that, leaders in attendance today, you can help bring your organization into the powertilt arena. 

We also have a blog on the powertilt phenomenon, and a podcast. You can listen to the podcast wherever podcasts are found. It’s called Tech Culture Interrupted, by NCWIT. One of the episodes is about powertilt, where we have a nice discussion with our sponsors for the pilot; the team at Intuit, who is very supportive of this research. 

CATHERINE: The link to the Powertilt project is in the chat now as well, and there was one more question: “Did we look at power and influence in daily decisions on a team versus influence and power on more structural decisions, such as pay, benefits, promotions, etc.?” 

So yes, that was a theme. That comes up during the conversations around how some answers would differ depending on which kind of decision that you are talking about. So, there’s a way for people to kind of decide to narrow the decision focus to a particular kind of decision, whether it is daily or more structural. Or, to take it as a whole, and then, tease that out in the conversation that happens amongst the team. But, that’s a super important factor in how people answer. 

BRAD: Finally, the direct contact for Catherine and I. Also, an acknowledgment of the crackerjack team here at NCWIT – from Lucy Sanders, the CEO; Joanne Esch, who is tirelessly supporting the work for the research, and the literature review behind this, and continues to be a huge influence on it; Tim Faiella, our tireless research coordinator who keeps all the cats herded pretty well – for cats, you know; and Terry Hogan, of course, who you know from hosting this, our president and CTO at NCWIT. Thank you all.  

CATHERINE: With that, I think, back to Joanne.

JOANNE: Thanks, Catherine and Brad, for sharing this exciting research. If you would like to use the powertilt tool with your team, then reach out to us. I will drop my email in the chat. You can reach out to Catherine and Brad as well. We hope that you will check out that powertilt paper for more information. 

Also, don’t forget to order your NCWIT Summit swag box, featuring an issue of our re:think magazine, and some other fun stuff too. 

Please join us tomorrow for a conversation with Dr. Damon A. Williams, called “Navigating the New Normal: Renewal, Allyship, and Joy During the Twin Pandemics.” Please register at 

Also, save the date for our next Conversation for Change on August 24, 2022 at 11 a.m. MT. Dr.  Maya Israel will focus on her research, on strategies for supporting academically diverse learners’ meaningful engagement in computer science education.

Finally, please take a moment to complete our survey by following the link that will appear on screen. We read every single response, and really appreciate your taking the time to provide feedback. The survey link will also be sent out in our follow-up email. Thank you again. We really appreciate your participation.

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