A new kind of partnership: what consulting should look (and feel) like
The recently published book “The Big Con: How the Consulting Industry Weakens our Businesses, Infantilizes our Governments and Warps Our Economies” makes some pretty damning claims about the consulting industry. The authors suggest that consulting companies actually stunt the clients they purport to serve by denying them the ability to build institutional capabilities. A direct quote reads: “The more businesses outsource, the less they know how to do, causing organizations to become hollowed out, stuck in time and unable to evolve.”
It may come as a surprise that our first reaction was not to cringe, but to exclaim an emphatic “YES! This is what we have been saying all along!” Furthermore, we have been actively working as a firm to engage very differently with our clients to make sure they – and we – don’t go down that road to ruin.
The book also prompted us to put pen to paper to share our point of view and advice to all companies out there – whether they are our clients or not – on how to expect more and get more from their consultant partner. Below we share a recent conversation on this topic and what your organization can take away.
The good and the bad about consulting
Anne: Kathryn, you are a long-time consultant with a deep love of consulting. Why would you want to share with the world what’s wrong with something you care about so deeply?
Kathryn: When I “found” consulting, I was in awe that companies would pay you money to have so much fun helping organizations solve really difficult problems. But over time, I lost faith in the big consulting model. I saw it delivering too little value, creating too much dependency, while consulting firms keep making money doing the same things over and over again because their clients didn’t learn how to do it themselves.
Don’t get me wrong, I do believe that there is a place for consultants. Organizations and leaders need outside perspective, and we bring that from working across many companies and industries. They need someone to hold up an objective mirror to see what is no longer obvious to them. They sometimes need skills in the moment that they won’t need over the long term. Those are all situations where consultants make sense. But organizations need to be careful about what they outsource – they cannot outsource thinking, judgment or accountability for business decisions, leadership, and results.
Anne: You mentioned “over and over again” – isn’t that part of the consulting business model? To turn one engagement into the next engagement?
Kathryn: I love having long term relationships with clients. You learn how to complement each other’s skills and knowledge. You build a strong foundation of trust to try new approaches. You stand on the shoulders of your collective accomplishments. But I never want to solve the same business problem with a client over and over again, because that means they haven’t increased their capability and I’ve failed. If clients are not better off – more skillful, more capable, more confident – after our engagement or initiative, we haven’t earned our money. If they have to hire a consultant one to three years later to solve the same problem, was the problem solved in the first place?
Anne: I am interested in your response to this quote from the book, “The more businesses outsource, the less they know how to do, causing organizations to become hollowed out, stuck in time and unable to evolve.”
Kathryn: Unfortunately, it’s an accurate description of how the industry has evolved. The good news is that it doesn’t have to be that way. Companies hire consultants for all kinds of services, but here’s the key: Don’t hire someone to make the decision for you or do the job for you. Instead, benefit from external expertise and build internal capability at the same time. This is the best of both worlds, and it’s actually why I came to BTS in the first place.
The founders of BTS and I share a common origin story. BTS was founded by former management consultants who also got tired of making recommendations that never went anywhere in organizations. They started building high-fidelity simulations that their clients could use to help people more deeply understand the new strategic direction. Then, the portfolio of tools and approaches grew from there.
Changing the approach to consulting for the better
Anne: Explain more about the role and power of simulation and practice, and how they help change the consulting game for clients.
Kathryn: I’ve learned over time that you can’t tell anyone about change, but you can help them experience it so that they become owners and authors of the future. BTS’s history of leveraging simulation to make strategy and behavior concrete and practical with real tools, approaches, and expertise is different. I saw breakthrough possibilities in the way BTS created alignment and excitement about a future that felt real and tangible for their clients. It was compelling for me when I first saw it – and a large part of what I saw was missing in the larger consulting space.
The future is never as scary as we think it is when it only lives in our head. When you can simulate the future, when you can “work through it” with others, then it becomes concrete. Even when the future is uncertain, after experiencing it, it feels less scary, and people and organizations can move forward in a more productive way.
Anne: Another fundamental element of consulting you share is that people are at the heart of an organization’s ability to change and thrive. You have said “you have to pay more attention to the people than the things.” Tell us more about how our clients should think about this.
Kathryn: In almost all cases, strategies don’t fail because they are bad. They fail because people don’t see themselves in the strategy and in the picture of the new future for their organization. Because of the way the consulting industry has evolved, clients think there is a tradeoff between getting stuff done and engaging people. But it’s actually a false tradeoff because at the end of the day it’s people who are doing the work. The paradox is that, the more you try to exclude people from the process in service of speed, the slower you will go. As we saw in stark contrast during the pandemic, while supply chains, processes and systems were challenged and disrupted, people changed, adapted, and improvised to keep thing going. We know this can happen outside of a crisis.
Great consultants work to make sure that your people have more than just an understanding of where they’re going as an organization. They help employees discover the intrinsic motivation to actually work in a new way and make new choices by connecting behavior and strategy, values and vision to initiatives in action.
What it feels like to work with a great consultant
Wondering how to ensure you are getting the most value from your consultant partner? And more importantly setting your organization up for success long term? Consider this checklist.
✔︎ Great consultants don’t make things more complex: they simplify, and help you connect the dots. They go beyond understanding the analytics and economics of your business model, your market, and your strategic aspirations. They bring deep understanding of what it takes to create real change – which only happens through people.
✔︎ Great consultants know how to effectively help your people find meaning and purpose in your organization’s new direction because ultimately that’s what will create progress.
✔︎ Great consultants should make you feel smarter and more capable after working with them. So many consultants have made people feel bad for so long that we almost accept it as a given, which is a shame.
✔︎ Great consultants hold a mutuality mindset. They live out the perspective, “We’re in this together — you bring value and so do we.” Great consultants bring insights AND respect and rely on their client’s wisdom about their organization.
✔︎ Great consultants get to root causes. They get to the underlying limiting mindsets because they come from a place of mutuality, curiosity, and respect.
When should you NOT hire a consultant
At the same time – heeding the learnings from our own experience, and the challenges unearthed in the book – there are instances when you shouldn’t hire consultant:
- Don’t hire a consultant when you want to rubber-stamp a tough decision you know you need to make (layoffs, restructuring, strategy pivots). This is about leadership courage. While it might provide air cover in the short term, in the long term it will damage your leadership brand and organizational trust.
- Don’t hire a consultant to redo consulting work you did with them before. If that way didn’t actually solve the problem, don’t do it over again.
- Don’t hire a consulting company to do something your own employees, or lower priced resources could do – like program management or research.
Check out this podcast if you want to hear more of our conversation on this important topic.
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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.
- They don't think it will help them
- Nobody around them is using it
- They don't feel capable
- 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.
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.
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.