The 3 things you’re not doing in performance reviews

A while back I heard a few people talking about public speaking. Person A was talking about their anxiety about making presentations. Trying to make him feel better, Person B said, “Public speaking is just like riding a bike!”

That got my attention.  It seemed to be a comforting little sound bite. The only problem was that it was wrong.  Public speaking is not like riding a bike. But it got me thinking about leadership communication and learning in general.

What does it mean if we say that something is like learning to ride a bike?  We’re saying that it’s a skill that initially may seem pretty difficult to learn… but once we figure it out, we can do it successfully without thinking—even if we don’t do it at all for years at a time. It’s the reassuring idea that you’ve acquired a skill that you will never lose.

There’s no question that we all learn many skills that are like riding a bike. Driving is a good example. Most of us were white-knuckle drivers when we first got behind the wheel, but what about now? On long highway drives, I sometimes snap out of a daydream and realize I have no memory of anything that happened on the road in the last 15 minutes. That’s because I don’t have to think about driving when I do it—not unless there is intense traffic or some other unusual circumstance.

Many other skills are the same—reading, typing, doing simple math in your head, and so on.   But quite a few sophisticated skills are quite unlike riding a bike.  In other words, there are skills that are definitely learnable and where your level of mastery can improve substantially. However, you’ll probably never be really great at these skills without vigilant, ongoing practice, preparation, reflection, and reinforcement.

Some examples that come to mind with leadership communication: Selling, managing change, inspiring your teams, and, yes, public speaking. What’s so different about these areas?  A few things:

• They involve an audience. If you were making your first speech in several months or years, would you find that you could do it almost unconsciously? I couldn’t. You can never be on auto-pilot when you’re delivering any sort of message to an audience. Just as the saying goes that you can never step in the same river twice, no two audiences are ever the same—even if you’re speaking to your internal teams each quarter. All sorts of circumstances change regularly, and you have to consciously adjust your message to address the ever-evolving needs of your audience.

• To maintain performance at a high level, sophisticated skills require ongoing practice. Yo-Yo Ma may be the world’s best cellist, but he estimates that he still puts in roughly 2,000 hours of practice each year. That’s an average of 5.5 hours daily.  If he stopped practicing altogether, he obviously could still play the cello.  But he wouldn’t be the best cellist for much longer.

• Skill mastery typically requires continual learning and reinforcement over time. Practice is critical, but it’s not sufficient. When you think about areas such as selling, motivating, and public speaking, there is always more to learn. There is evidence now that 90% of what we learn at a workshop, for example, dissipates within one year. To ensure the needle keeps moving in the right direction, you need to be a perpetual student. That may involve reading about the subject, hearing about it, going to a workshop, and getting expert advice. Whether you’re a tennis pro, a psychiatrist, or a VP of Sales, having a coach to help you with your real-time challenges can have an enormous impact to give you that reinforcement over time.

As a leader, you’ll no doubt hear from companies that want to offer you “quick-fix” solutions for perpetual leadership development challenges—areas such as executive presence, employee engagement, and public speaking.

But lasting, meaningful mastery is not a quick fix.  Sophisticated skills need reinforcement: A better motto for these skills would be “use it or lose it.” Because some things are quite unlike riding a bike,

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AI is reshaping how work gets done—automating tasks, accelerating decisions, and raising expectations for speed and precision. Strategy is shifting faster than structures can adapt, leaving many leaders operating in systems that weren’t built for what’s being asked of them now. Employees are asking more of their managers—while the business is asking more of them, too. And leaders are stuck navigating it all with development priorities, operating norms, and support systems that weren’t designed for this level of speed, ambiguity, or stretch.

As expectations rise, leadership capability is under scrutiny.

But are development efforts evolving fast enough to meet the moment?

Where priorities and expectations diverge

Most leadership development programs today emphasize foundational strengths:

• Executive presence
• Personal purpose
• A growth mindset
• Empowering others
• Stretching others

In contrast, senior executives in the BTS study identified a different set of capabilities as most critical for leaders right now:

• Accountability
• Transparency
• Enterprise thinking
• Divergent thinking

The contrast reveals a disconnect between what development programs are building—and what executives believe their organizations need most from their leaders today.

How did we get here?

The expectations placed on leaders—especially at the middle—have always evolved alongside the business landscape.

In the 1990s, leadership development focused on emotional intelligence and team empowerment. The 2000s brought globalization and lean operating models, with a sharper focus on efficiency and agility. Then came digital transformation, agile ways of working, and flatter, more matrixed structures.

Each wave expanded the leadership mandate—asking leaders to become connectors, coaches, and change agents.

What’s different now is the pace and proximity of change. Strategy no longer shifts annually—it flexes monthly. And mid-level leaders are no longer simply executing someone else’s vision. They’re expected to interpret it, shape it, and deliver results through others—in real time.

At the same time, the psychological contract of work has changed. Employees want more meaning, flexibility, and support—and they often look to their managers to provide it. Add in the rise of AI and the frequency of disruption, and the expectations placed on leaders have outpaced what many development efforts were designed to support.

What’s driving the disconnect?

What we’re seeing isn’t disagreement—it’s a difference in vantage point, shaped by the distinct challenges each group is solving for. This isn’t about misaligned intent—it reflects different priorities and pressures.

Talent and learning teams often prioritize foundational capabilities because they’re proven, scalable, and critical to developing confident, human-centered leaders. These programs are designed to grow potential over time.

Executives, meanwhile, are focused on the immediacy of execution—strategy under strain, shifting priorities, and the need for alignment at speed. Their focus reflects where progress is stalling now.

Both perspectives matter. But when they remain disconnected, development risks falling out of sync with business reality—and the gap is most visible at the middle, where expectations are rising fastest.

What’s the takeaway for talent leaders now?

This moment offers more than a gap to close—it offers insight into how leadership needs are evolving.

What if the differences between these two capability lists aren’t in conflict, but in sequence? Foundational strengths help leaders show up with purpose and empathy. Enterprise capabilities help them lead across systems and ambiguity. The opportunity isn’t to choose between them—it’s to connect them more intentionally.

What’s uniquely now is the acceleration. The stretch. The pressure to reduce friction and support faster alignment. Talent leaders aren’t just being asked to build capability—they’re being asked to build momentum. That means designing development experiences that reflect complexity, enable cross-functional thinking, and help leaders decide and adapt in real time.

It also means listening more closely. The capabilities executives are calling for aren’t just wish lists—they’re signals. Signals of where transformation slows, and where leadership must evolve for strategy to move forward.

This isn’t about shifting away from what works—it’s about expanding it. To connect what leaders already do well with what the business needs next—and to do it in ways that are grounded, human, and built for today’s pace.

Shifting momentum

Leadership development isn’t just a pipeline priority. It’s a strategic lever for how your organization adapts, aligns, and accelerates through change.

This research doesn’t just reveal a skills gap—it surfaces a systems opportunity. The disconnect between talent priorities and executive expectations highlights where momentum gets lost, and how leadership development can close the space between vision and execution.

Talent leaders are uniquely positioned to reconnect the dots—between individual growth and enterprise outcomes, between what leaders learn and how they lead, between what the business says it needs and how that shows up in behavior.

So the next question isn’t just: What should we build?

It’s: How do we enable leaders to build it into the business—faster?

Every organization is navigating this differently. If you’re revisiting your development priorities or rethinking what leadership looks like in your context, let’s connect. We’re happy to share what we’re seeing—and learning—with others facing the same questions.

In late 2023, we set out to answer a question we kept hearing from clients:

How do you prepare for what’s next—when “next” keeps changing?

That question has only become more urgent in 2025. Today’s leaders are navigating rapid shifts—from AI’s integration into nearly every role to volatile markets and a growing disconnect between employee expectations and organizational readiness. Planning feels harder than ever—because the future keeps accelerating while our tools and assumptions stay anchored in the past.

Too often, strategic planning is built on outdated logic: start with what’s already in motion, layer on incremental improvements, and forecast trends forward. But in today’s environment, that approach isn’t just ineffective—it’s risky. It reinforces legacy thinking. It prioritizes what’s easy over what’s essential. And it creates strategies built for a version of the world that no longer exists.

That’s why we took a different approach. We gathered a team of I/O psychologists, academics, and senior talent leaders—not to react to trends, but to reimagine what the future of talent, leadership, and learning might truly demand.

To guide the process, we used a method we often apply with clients: future-back thinking.

What is future-back thinking?

Future-back thinking flips traditional strategy. Rather than starting with today’s constraints, it begins with a bold vision of future success—and works backward to define what it will take to get there.

This approach helped us look past short-term pressures and surface deeper signals. It made the future feel more actionable—and more human.

It also reminded us why innovation is so rare: Most organizations are wired to protect what’s familiar. We prioritize feasibility, optimize what exists, and assume continuity. In uncertain times, we tweak around the edges instead of reimagining what’s possible.

Future-back thinking breaks that cycle. It turns ambiguity into alignment—and strategy into design.

It starts with a better question:

What will the future demand—and what will we wish we’d done sooner?

Because it’s not about being right. It’s about being ready.

Five bold predictions—and how they became reality

When we applied future-back thinking to the future of talent and learning, five provocative themes emerged. Each was grounded in signals we were already starting to see—but at the time, they felt ambitious.

We captured them in our original blog, Navigating the New Dawn of Talent Strategy—a look at what might shape how organizations attract, develop, and lead talent over the next 3–5 years.

Now, just two years later, those signals have become strategy. Here’s how the predictions stack up against today’s reality:

1. Skills × jobs (the remix)

Then: We predicted that rigid job architectures would give way to more fluid, capability-based models—ones that reflect how people actually grow and how business needs evolve.

Now: That shift is well underway. Many organizations have begun redesigning roles around transferable skills and capabilities, creating more dynamic paths for growth, mobility, and performance.

2. AI-powered learning

Then: We anticipated GenAI would unlock personalized, real-time learning at scale, integrated into the flow of work.

Now: GenAI is now embedded in many organizations’ learning ecosystems—powering smart coaching, adaptive learning paths, and knowledge retrieval in the flow of work.

3. Diversity as differentiation

Then: We forecasted a shift from DEI as a compliance mandate to DEI as a core driver of innovation, adaptability, and growth.

Now: High-performing organizations are building cognitive and cultural diversity into teams, treating it as a strategic advantage—not a checkbox.

4. AI as a leadership partner

Then: We imagined a future where AI would augment—not replace—leaders, supporting better decisions, planning, and communication.

Now: That’s exactly what’s happening. Leaders are using AI to model scenarios, synthesize insights, and communicate with more speed and clarity.

5. Decentralized, human-centric leadership

Then: We projected leadership would decentralize, moving closer to the front line and defined by mindset more than title.

Now: Leading organizations are scaling leadership behaviors across levels and embedding psychological safety, inclusion, and empowerment into day-to-day work.

These predictions weren’t about chasing trends. They were about imagining what the future might require—and preparing for it before it arrived.

That’s the power of future-back thinking: it doesn’t just forecast change. It helps leaders design for it.

Start thinking differently now

Most strategic plans start by looking around—at what exists, what’s already in motion, what feels feasible. But the brain doesn’t just collect data. It builds habits. It channels information into familiar paths. And it reinforces what it already knows.

That’s good for speed. But bad for imagination.

Future-back thinking challenges that. It deliberately disrupts those neural paths. Instead of adjusting today’s structures, it starts at the endpoint: a bold future state. Then it reverse-engineers the shifts required to get there.

This shift—from refining the familiar to reimagining what’s possible—is what organizations need now.

Here are three provocations to help you start:

1. What assumptions are we treating as facts? The most dangerous limits are the ones we no longer see.
2. What would someone from a completely different world do? (A customer, a child, Beyoncé?) Try role-storming to unlock new angles.
3. What if we had no legacy systems to maintain—what would we build from scratch? Imagine a blank slate.

These questions aren’t just creative warm-ups. They help you unstick your strategy from old grooves—and build what’s essential.

Because in a world that’s constantly changing, the biggest risk isn’t getting it wrong. It’s staying stuck.

How BTS helps leaders and teams think beyond today

Our brains—even at their most capable—get stuck in “rivers of thinking,” defaulting to what feels safe instead of what the future demands.

At BTS, we help organizations break that cycle.

Future-back thinking is more than a framework—it’s a provocation. A way to disrupt habitual planning, reframe challenges, and design from a place of possibility.

We work with leaders and teams to:

• Break from old patterns by surfacing the assumptions quietly guiding decisions
• Align around vivid, future-state scenarios that challenge status-quo thinking
• Role-storm bold ideas into strategic options that unlock creativity
• Simulate future decisions to build confidence and agility
• Build the mindsets and capabilities your strategy requires

Because the real risk isn’t change. It’s standing still.

Too often, organizations invest time and energy planning for a version of the world that no longer exists. They reinforce legacy mindsets, delay bold moves, and miss the moment.

Future-back thinking offers a way out. It gives leaders a structured way to reimagine what’s possible, align teams around the future, and start building toward it—now.

Let’s build what’s next—together. Learn how we help organizations prepare for the future.

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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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.

Leadership is the work of creating shared understanding, and language is the primary tool for doing it. Yet we spend remarkably little time examining our words. Every decision, expectation, priority, and piece of feedback reaches another person through words. If those words aren't doing the job, neither is the leadership.

The lighthouse

Some years ago, a large company hired a strategy consulting firm to rethink its leadership model. The firm came back with a beautifully produced framework built around a central metaphor: the lighthouse.

Leaders, the model declared, should be lighthouses.

The metaphor quickly found its way into playbooks, performance reviews, onboarding decks, and town halls. People repeated it with the confidence of those who had paid a lot of money for it.

There was just one problem: nobody could agree on what a lighthouse was supposed to do.

Was it warning people away from danger? Guiding them toward a destination? Standing firm while everything else changed?

Eventually, the company hired another team to translate the metaphor into specific, observable leadership behaviors.

It was an expensive way to discover that a word everyone confidently repeated wasn't creating nearly as much shared understanding asthey thought.

Why jargon prevails

• Parking lot that
• Double-click
• Close the loop

Business jargon survives because it’s largely designed to manage social risk. Using it signals, I know how this world works. It demonstrates membership, competence, and credibility.

Business is messy, and leaders don't always have complete information. Abstract language lets us project confidence while preserving flexibility.

Altitude without traction

Specific language creates accountability. The more specific you are, the easier it is for people to disagree, question your thinking, orhold you accountable. That's part of the appeal of jargon. It creates distance between the speaker and the detail. The more abstract and elevated your language, the more strategic you sound.

A 2020 study by Harvard Business School professors Laura Huang and Andy Wu, published in the Academy ofManagement Journal, analyzed over 1,000 early-stage startup pitches and found that founders who spoke in abstract, visionary terms were significantly more likely to advance in the funding process.

A separate study, published in Applied Cognitive Psychology in 2025, found the other side: jargon raises how credible a speaker appears and lowers how much the audience retains.

The very language that helps people see you as a leader can make you less effective once you're leading.

The most trusted leaders tend to be the ones who resist impressive-sounding language and say the plainest version of what they mean.

In fact, four words probably do more for a leader's standing than any carefully crafted message: I made a mistake. Not "we encountered some headwinds," not "there were learnings from this experience," but the plain version.

The cost of comfort

When a conversation gets uncomfortable at work, it almost always feels easier to soften your message than to say exactly what you mean. You hedge, add qualifiers, cushion the point with extra reassurance, or leave the hardest part unsaid. Most of the time, you mean well. You don't want to discourage someone, damage the relationship, or create unnecessary conflict. The conversation becomes less uncomfortable for a moment, but the work often becomes harder afterward.

Amy Edmondson, Novartis Professor of Leadership and Management at Harvard Business School and author of The Fearless Organization, found that the fear of making a negative impression pushes people to stay silent exactly when clarity is most needed. According to her research, silence is one of the most consistent predictors of teams that miss problems early and never learn from them. The friction avoided in the meeting resurfaces later, at greater cost.

KimScott, former executive at Google and Apple and author of Radical Candor, calls this ruinous empathy: softening your message to protect someone's short-term feelings comes at the cost of the clarity they need. Her argument is simple and uncomfortable: clear, direct communication, even when it is hard, is an act of care.

The quiet power of saying what you mean

None of this is an argument for bland, colorless language.Vivid, precise writing does the opposite of jargon: it sharpens meaning instead of hiding it. Before reaching for a word, pause on two questions:

• What do I mean by it? 
• What will my audience hear? 

A surprising amount of corporate language wouldn't survive those two questions.

Leaders have more influence over language than they often realize. Whatever tone, vocabulary, and level of directness they model becomes the standard everyone else copies. Word choice is one of the quietest ways leaders shape culture.

This matters even more as we hand our language to AI. These tools can already learn to write in our voice. The question now is whether we've been deliberate enough about that voice in the first place to like what we see.