A data-driven & mindset approach to increasing diversity

Learn from Jessica Skon about the importance of having leaders who embrace different skills and backgrounds as part of an effective workforce.
January 1, 2017
5
min read
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Throughout her more than 15-year career at BTS, Jessica has pioneered turning strategy into action through the use of customized experiences & simulations for leading Fortune 500 clients and many large and start-up software companies in Silicon Valley. Jessica leads BTS USA with P&L responsibility for offices in San Francisco, Philadelphia, New York, Chicago, Phoenix, and Austin.

Although one of the most-discussed topics in business today, meaningful diversity seems to be elusive for most companies. We sat down for a casual and candid conversation with Jessica and uncovered some surprising insights about our clients’ challenges in creating a more diverse and inclusive workplace, and what companies can do about it.

We are lucky to have snagged a few moments of Jessica’s time — squeezed between a flight to New York for a client meeting and her morning school drop-off duties — to hear her perspective.

JENNY JONSSON: We have a lot to cover today, so if it’s ok with you, we’re going to jump right in! First, we would love to hear a little about your journey to becoming a Global Partner (GP) – and of course, it’s hard to conduct research for a paper on diversity and ignore that there’s a gender imbalance at our GP level.

JESSICA SKON: Well first of all, while I may be the only female Global Partner, I don’t want to lose sight of the fact that we do have a lot of women leaders at BTS: 35% of our Heads of Office are women. With that said, what I can say about my experience is that it has been fair. I don’t think I would still be here if I didn’t feel the expectations and the performance processes over the last 17 years were fair, and I have never felt like gender has been a factor in performance conversations. When I reflect on that after talking to other female leaders, that’s a pretty big deal.

MJ DOCTORS: Why do you think your experience has been so different from what many other working women encounter?

JS: Before my first Global Partner meeting, where we were looking at candidates for Principal and above, I was told, “This is always the best meeting of the year.” I wondered how it could be so drastically different than any other meeting, but they were right — it is an entirely data-driven, unemotional, and fair process.

It was a simple process and there were no biases. There are three parts to how we evaluate partners up for promotion:

  1. The background information on each candidate includes all of the specific promotion criteria and supporting data.
  2. The leader recommending the promotion gives a 5-minute summary emphasizing their view of the candidate’s weaknesses and areas for growth in the coming years.
  3. A fellow partner who has done due diligence against the facts acts as the “inquisitor” and shares findings.

This approach ensures it isn’t just a pitchfest. And this process is also something that has trickled down to other areas of the business, reducing a lot of the biases in our hiring and promoting.

JJ: Have you been approached by clients asking for guidance on a similar data-driven approach?

JP: Absolutely, clients realize they need to make this shift. I think it’s going to happen really quickly: we already have one client whose CEO has asked us to rebuild their entire performance system so that it’s more data-driven, more accurate, and more fair. In many companies, the way things are now, it’s often gray and you can’t help but rely on relationships and favoritism to guide promotion decisions.

MD: As part of our research, Jenny and I took a look at how BTS USA is performing on diversity metrics. While most publications and companies measure diversity by simply looking at gender and race (such as Fortune’s 50 Most Diverse Companies), we believe diversity is much more than that. Our definition encompasses gender and race, but also age, socioeconomics, gender identity, sexual orientation, education, life experiences, disability status, and personality traits — and the list could go on. However, as we currently only have results across race and gender, that’s what we’ll share here. How do you feel when you look at these charts?

JS: You’re bringing me back to 5 years ago when we had the same color chart for gender as we do now for ethnicity — which was horrifying. I think we all knew it was a problem but we weren’t mature enough in our thinking to solve it. Once we all woke up and clearly defined that we had a gender parity problem across the company, we were persistent and fixed it, and now I am proud of our gender pie chart. That is something I love about BTS: if we can clearly articulate a problem, we tend to be able to solve it. That’s actually the key for leaders across most industries: the art is being able to clearly define the problem.

But I think that we’re at ground zero again for the next phase.  I would love for us to apply the same rigor we used to address gender disparities to other forms of diversity so that in 3 or 4 years we have a better mix, and why wouldn’t we?

JJ: Can you outline specifically how we made progress on our lack of gender diversity?

JS: We took a few major steps:

  1. Our Heads of Office decided it was a top priority. Without top leadership’s buy-in, you can’t really make progress.
  2. Then we identified the key pain point: for us, it was the entry to the funnel. Then we brainstormed the best ways to attract more female candidates.
  3. This led to some “ahas” about the root cause of that pain point. Many people think that consulting is inflexible and it’s difficult for employees with children to succeed. But there’s nothing further from the truth at BTS. Our Global CEO is quite progressive and incredibly flexible and open-minded when it comes to letting employees do what they need for their lives.
  4. So then our leaders got on the megaphone: our (now retired) US CEO began flying to each of our offices to talk about it, and I got on the phone with candidates to tell them my story of being a young working mother. A lot changed once we started to focus on it.
  5. In reviewing our hiring interview process, we also realized we could be more clear in our criteria, with observable behaviors and a more robust scoring rubric. This change eliminated any unconscious bias and we found that woman were scoring as high as our male candidates. When we looked in the past, they were (on average) scoring lower.

MD: Besides clearly defining the problem, what other factors pushed forward this change?

JS: Clients started noticing and asking for more women consultants, so it became an easy sell to our leadership. Our demographics should match – or even be ahead of – our clients’ demographics. We shouldn’t have to be scrambling every time a client says, “Um… there’s a lot of men here.” Sure, some traditional clients may not have said anything, so for some folks internally it was more difficult to understand the impetus behind the huge investment we were making in changing our recruitment process. But we also had enough examples of women starting at BTS who didn’t have many female role models. And we realized, we have to change this or some of our best people are going to leave.

JJ: So what about our clients? You have spent significant time over the past 20 years with CEOs and senior leaders of some of the world’s top companies. What aspects of diversity are they discussing the most?

JS: In the last couple of months, I have heard many top executives discussing how to change the paradigm of their leaders to promote and move people around who don’t necessarily fit the makeup of the candidates from the past. So for example, one client said that they have been really good at keeping people for life, but realize that they might not be able to maintain that with millennials, unless they can keep having great careers for them.

Also, companies still tend to focus on “the résumé”: did the applicant go to an Ivy League school, did she have a fancy job, how long did he work in this department, etc. All of this has been the formula for success over the last 50 years. But if we don’t crack that mindset, there will be amazing people who don’t get put in the right positions, because unconsciously our leaders are not seeing them or they are not open-minded enough to realize that this candidate might be better suited than that more traditional-looking candidate.

MD: What is some advice you would give clients to change that mindset?

JS: You and all your leaders have to first recognize your beliefs and own them before any mindset change can happen. That may be kind of obvious, but getting yourself and your senior leaders to fully own their beliefs is hard. You have to be both very self-aware and constantly striving to improve. It’s a battle every single day.

So when an executive comes to me and says, “This is weighing on my mind at the company-wide level,” I don’t say, “Well there’s a diversity training that we can do.” I do say, “You’re talking about changing deeply rooted mindsets: this requires getting leaders to articulate, own, and put those issues on the table, and commit to changing their beliefs moving forward.”

This is crucial to making sure you have the right people in the right jobs and you’re retaining the people that you want, which ultimately enables you to make the company successful. That is an immense amount of work, including interventions, working sessions, and sometimes coaching. It’s sometimes getting the most skeptical leaders to become the owners of this and driving these change management efforts. It’s deeper than just a training class.

JJ: If it’s not just a training class, what do you see as the platform?

JS: Any time you’re trying to drive large scale transformation, it’s a good idea to run experiments. And once they get some momentum and prove to be successful, you should shine a really big light on them to get broad adoption and then begin the comprehensive change management process.

So even though it’s out of our core services, I try to give clients ideas on small stuff they can do that is totally different than anything they have done before, to shake up people’s way of thinking about how they recruit, hire, train, promote, and think about people. I think a strong example of an initiative a company has experimented with is a leading software company and their strategic partnerships with nonprofits who help them access more and different talent pools.

So – once those initiatives have gained that momentum, it would be fun for us to do some consulting with their executives first around owning the beliefs, the history (it’s important to honor the history and not just break it), what worked in the past, what beliefs do you now hold as a result, and what are you going to do moving forward. All of this can be built around an experience that shifts people’s mindsets. It’s not so much diversity training… it’s a mindset shift process that starts at top leadership.

MD: Are there any companies that are beginning to successfully make this mindset shift and use more data-driven approaches to evaluation?

JS: Not really… that’s what’s tough about this. It’s bizarrely new. The more BTS is asked to provide broader talent services, the more surprised I am. We’re basically back in the Stone Age. It’s not pretty.

But we’re starting to work on something internally to track an individual’s acquisition of skills in a moment-based approach. At the beginning of a project the individual comes up with specific skills that she wants to work on. Then, during critical milestones and at the completion of the project, the rest of the team gives feedback on those specific areas. That’s real curation of a skillset, where the individual can own her career progress, people can validate it, and the company can say, “oh, she’s telling us she’s ready for a promotion, look, she’s actually done all of these things and demonstrated she can be successful.”

JJ: So really it’s democratizing the job application and promotion process.

JS: Yes! That’s exactly why many of our clients have turned to selection and assessment solutions. Assessments enable our clients to reduce unconscious bias in the hiring and promotion processes and ensure that a candidate has the actual skills necessary for the role, as opposed to a particular degree from a particular university, which is, at best, only a moderate proxy for job fit. Through these solutions, our clients effectively expand their talent pool and improve the likelihood that the candidates they hire have both skill and culture fit, which can lead to increased cognitive diversity – that is, team members who have different backgrounds and thus approach problems in different ways – improved retention, and reduced recruiting costs.

MD: We are seeing some progress from expanded talent pools, but the critical question is, once a female or a non-white employee has joined a company, why aren’t they moving up as fast as white men?

JS: I think maybe it goes back to the issue that I heard from one of our clients: there’s a history of certain roles looking and acting a certain way. It’s hard to overcome the unconscious bias of hiring and promoting people who fit that perception.

It could also be that people aren’t putting their hat in the ring for those promotions. Women and people from certain cultures aren’t oriented toward self-promotion and won’t put their hat in the ring if they are only 10% confident they’ll be successful. So in that case, you really have to focus on the current leaders: it’s so important that they understand this dynamic. Even at BTS, there are so many outstanding individuals who don’t self-promote, and you have to be the megaphone for them.

JJ: When running our leadership development simulation experiences, BTS has always encouraged participants to form the most diverse teams possible (gender, culture, geography, role, tenure, etc.). What’s the origin behind why we ask our clients to create diverse simulation teams?

JS: Initially, this was primarily because our clients value enabling leaders to create networks across the company, more so than because of any inherent desire for cognitive diversity. Clients often come to us when they need a push toward a “one company” mindset, so simulation teams are built to bring people out of their silos and align around a single company goal.

But, nowadays, people recognize that cognitive diversity is a good thing. That being said, at BTS, we are very protective of our culture and team environment, and sometimes we’re guilty of mistaking like-minded people as a proxy for “I think I’ll get along with you”. So you have to have two heads when hiring: we want someone different who will shake us up, but we also want to be at peace and have fun and a strong culture fit.

MD: If you could leave one piece of advice for leaders hoping to create a more diverse and inclusive workplace, what would it be?

JS: In alignment with Liz Wiseman‘s book, “Rookie Smarts,” I’m trying to get leaders to crave being rookies again. If you’re going to learn as fast as the pace of change, and be able to transform yourself, you have to be a bit of an adrenaline junkie with a “rookie mindset”. I want people to realize that it’s not scary to do something different and new – it’s exciting. And, if you put yourself in an uncomfortable role, you get humbled, become curious, and seek advice from the best around you. As a result, you will most likely do the best work of your life.

There is a correlation between the “rookie mindset” and shifting beliefs in support of a more diverse team: we need leaders who crave differences. That has to be the overarching mindset when you’re recruiting and looking to add members to your team. If you crave differences in skills and personal history and combine that with culture-fit, then innovative ideas, high performance, and fun should follow. Others will notice the benefits of the diverse team and follow, assuming the appropriate recruitment and performance systems are in place. That’s how you start to shift mindsets at the top and eventually throughout the company.

About the Authors

Diversity has been a passion area for both MJ Doctors and Jenny Jonsson, both of whom have spent significant time – prior to and while at BTS – working to improve economic opportunities for women, immigrants, and individuals of varying socioeconomic backgrounds.

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Planning an AI reset off-site? The agenda decides everything. Four common design mistakes, and how to build two days that change what your company is capable of.

There’s a specific kind of strategy meeting getting scheduled right now, in nice hotels with bad coffee: the AI reset off-site.

And for good reason. In a 2026 WRITER survey, 48% of leaders described their AI rollout as, in their own words, a "massive disappointment." That's nearly half the room.

What that number really measures is the distance between what these tools can do and what people are doing with them. In our experience, that distance is almost entirely human.

Which is why the off-site is the right instinct. Making the most of that time is the harder part.

What separates an AI reset that actually changes the game from an expensive two-day conversation? In our experience, it comes down to avoiding four common design mistakes.

Mistake 1

Blaming the bots

The gap between AI investment and real adoption is almost always about people, not technology. And when adoption stalls, we usually find it's one of four things.

  1. They don't think it will help them
  2. Nobody around them is using it
  3. They don't feel capable
  4. Or they don't have real access to the tools they were promised

Four different problems, and four completely different fixes.

That's why diagnosis comes first. If you don't know which barrier you're dealing with, every intervention becomes an educated guess. And you cannot tell which one you have by staring at a dashboard. A belief gap and a skill gap look identical in a status report and need opposite interventions. Show up guessing, and you'll spend real money teaching people to use a tool they simply don't trust yet. Congratulations - you've just catered the wrong conversation.

Mistake 2

Letting leaders off the hook

One of the biggest predictors of whether change sticks is also one of the most overlooked: leadership.

If your executives show up as observers, nodding along and quietly answering email under the table, your people clock it in about four minutes.

That doesn't mean your CEO has to emcee the thing. It means they use the tools in front of everyone, participate in the conversation, and make it clear this isn't someone else's initiative.

Recently we’ve been working with a Fortune 200 global professional services firm who’s top 120 leaders were at very different points with AI. Some were redesigning entire processes. Others were using it to summarize emails, or not at all. Rather than focus on the technology, the four-hour session focused on what leaders could do with AI, applying it to a live strategic challenge and ending with a personal commitment to lead differently. The response was strong enough that the organization is now cascading the experience globally.

The lesson is simple: when leaders experience AI as a strategic capability, they're better equipped to model the behavior that makes adoption stick. Nothing you build during those two days survives without that entire chain of leadership doing its part.

Mistake 3

Chasing the wrong outcome

Without a behavioral baseline, you have no way to prove anything actually moved. No baseline, no ROI. You're just hoping the energy in the room was good, which is a wonderful feeling and a terrible metric to bring to your CFO.

But the baseline isn't just about proving the off-site worked. It's about understanding where you're starting in the first place. And you'll want that clarity, because the quiet resistance is real. In that same 2026 research, nearly a third of employees admitted to actively working around their company's AI strategy. If you don't win their belief in the room, some of them will keep politely ignoring the whole thing from their desks. You can't measure your way out of that. You have to earn your way out of it.

Which brings us to the biggest reframe of all.

Mistake 4

Leaving follow-through to chance

We've been working with a Fortune 100 medical device company on their AI strategy for three years. It started with their leadership team, a three-hour session built around what those leaders would do differently, and it landed. What became clear afterward was that the same experience needed to happen everywhere else. So, it expanded: 90-minute activations for 15,000 people, and this year intact teams redesigning their own workflows.

Three years in, that first session is the smallest part of the story.

Your event is where momentum gets created. What happens at 30, 60, and 90 days is where results get made.

If you're planning one of these and want to change what happens on Monday, not just how everyone feels on Friday, that the work we do.
We'd be glad to help you design it.
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Every candidate looks like a great hire now. AI made sure of it.
Polish is no longer a hiring signal. See how organizations use role-relevant simulations and predictive validity data to hire for high-stakes roles.

Candidates now arrive at interviews pre-coached by AI, with their resumes optimized to pass every checkpoint. Polish has stopped being a signal. The traditional hiring process was built to read exactly the cues that AI is now best at producing, and the signals hiring managers once relied on have weakened as a result. And for roles where the wrong hire carries real business consequences, losing the ability to tell who will actually perform is not a minor inconvenience. It is a material risk, and it exposes the business to unnecessary turnover, reduced performance, and heavier investment for talent growth and development.

So how do you observe the behaviors that matter most, before someone is in the role?

Not by asking better questions, but rather by putting candidates in situations designed to elicit that behavior.

The limits of predicting from paper

Credentials tell you what someone has done. Structured interviews tell you what someone says they would do. Neither lets you observe what they actually do in the moments that count.

This distinction matters most in client-facing, relationship-driven roles, where the performance gap between a strong hire and a weak one plays out in real business outcomes (revenue, retention, client growth). Organizations that hire at scale in these roles carry that gap across hundreds of decisions at a time.

The better approach is to watch candidates do the work before you hire them. Put them in simulated, role-relevant scenarios, and pair the simulation with a second, different kind of measure so no single method carries the whole decision. That combination is what lets you evaluate real performance before anyone is in the role. Organization-specific simulations provide a clear read on who is ready and capable of performing on day one. In a world of AI-supported candidate signals, the use of simulations makes the process harder to prep for. It is harder to fake. And, when designed well, it is substantially more predictive than other hiring methods.  

What counts as evidence

Claims about predictive power are easy to make. Evidence for them is rarer than you would expect.

A predictive validity study, the kind that links pre-hire assessment scores to how someone actually performs once hired, is some of the hardest evidence to produce and the rarest to see. Many assessments are validated against proxies: another test, or a theoretical model of the role, rather than real results on the job. Connecting scores to concrete business outcomes and doing the statistical work to show the link holds, takes years of shared data and a level of commitment from both the assessment provider and the client that most partnerships never reach. That is precisely why it is worth asking for. A provider who can show how assessment scores track to training completion, retention, and first-year output is offering something categorically different from one who can only show a correlation with another test.

Why simulation holds up where other methods do not

When a candidate sits across from a trained assessor (someone playing the client or prospect on the other side of the conversation) and has to work through a real situation, they cannot rely on a rehearsed answer. The scenario is specific. The stakes feel real. What you see is close to what you would get on the job.

That is the value of simulation-based assessment: it does not test what candidates know about the role.

It shows how they use what they know when a real person is on the other side of the conversation, before the stakes are real.

For roles that carry significant business responsibility, this distinction is the whole game. The cost of the wrong hire in a high-stakes client-facing role is not just a missed quota for a quarter - It plays out in relationships that do not develop, clients who leave, and productivity losses that compound over time. Getting those hiring decisions right, at scale, with consistency, requires methods that are built for predictive accuracy, not just candidate experience or hiring speed.

What this means for how organizations think about hiring

Most organizations are still optimizing the wrong things in their hiring process. They invest heavily in employer branding, application flow, and interview structure, all of which matter, but less in the core question: does our hiring process actually predict who will succeed in this role?

AI has sharpened the stakes here. If every candidate can present as polished and prepared, screening based on presentation becomes less useful. What holds up is direct observation of the behaviors that the job requires.

A few principles worth building from:

  • Measure what the job requires, not what is easy to measure. Cognitive tests and personality questionnaires have their place, but they do not look much like the job. The closer the assessment is to the actual work, the better it predicts performance in it.
  • Ask what your assessment predicts. Training completion? Retention? First-year output? Most organizations cannot answer that question today, largely because providers have rarely been asked to prove it. It is a fair thing to ask for.
  • Take the human element seriously. In a simulation, a candidate is having a real conversation, responding in real time, navigating a situation that requires judgment. Even with the help of AI, that is hard to game. And it remains one of the strongest predictors of on-the-job performance available.

The data exists to make hiring decisions more accurate, fairer, and more directly tied to business outcomes. For organizations operating in high-stakes roles at scale, there is too much on the line to rely on methods that cannot hold up to that standard.

You may be interested in BTS’ thought leadership in the five talent shifts AI is forcing now.  

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El GPS no maneja el auto. La IA cambió el mapa, no el viaje…(ES)
La IA ya no es una ventaja competitiva en ventas. Descubre por qué el verdadero diferencial está en el criterio comercial, el conocimiento del negocio y la capacidad de construir relaciones de confianza.

La IA ya forma parte del día a día de las ventas. Hoy cualquier asesor puede llegar a una reunión con datos, tendencias e insights generados en segundos. Sin embargo, disponer de más información no garantiza conversaciones de mayor valor.

A través de una experiencia real con un consultor comercial, este artículo explica por qué la inteligencia artificial funciona como un GPS: ayuda a interpretar el entorno, pero no conduce la conversación ni entiende las prioridades del cliente.

En este artículo descubrirás:

  • Por qué el acceso a la información ya no supone una ventaja competitiva.
  • La importancia del business acumen para interpretar los datos con criterio.
  • Cómo hablar el lenguaje del cliente genera credibilidad y diferenciación.
  • Por qué las relaciones B2B evolucionan hacia relaciones P2P basadas en la confianza.
  • Qué capacidades consultivas seguirán siendo exclusivamente humanas incluso en la era de la IA.

La tecnología seguirá evolucionando, pero la ventaja competitiva estará en quienes sean capaces de combinar inteligencia artificial con conversaciones centradas en el cliente, pensamiento estratégico y relaciones de largo plazo.