When Your Crystal Ball Cracks
The Death of Workforce Planning (And Why That's Actually Good News)
Picture this: It's 2019, and you're sitting in a mahogany-paneled boardroom, presenting your masterpiece—a five-year workforce plan so detailed it could make McKinsey weep with joy. You've got heat maps. Succession matrices. Talent pipelines flowing like carefully choreographed water features. The CEO nods approvingly as you explain how you'll need exactly 10,000 more consultants by 2024.
Fast forward to 2024. Not only do you not have those 10,000 consultants, you've actually reduced headcount by 15,000. Oh, and revenue? Up 40%. Turns out, AI tools made your entire consulting model about as relevant as a fax machine at a TikTok convention.
Welcome to the BANI world, where your carefully crafted workforce plans have the shelf life of gas station sushi.
Remember VUCA? That comforting acronym we've been clinging to since the military gifted it to the business world in the 1990s? Volatile, Uncertain, Complex, Ambiguous—it sounded so manageable. Like something you could strategize around with enough PowerPoint slides and scenario planning workshops. Here's the thing about VUCA: it assumed chaos had rules. It was like playing poker—sure, you couldn't see all the cards, but at least everyone agreed on what game we were playing. VUCA promised that with enough analysis, enough data, enough strategic thinking, you could navigate the uncertainty. You could find patterns in the volatility. Map the complexity. Clarify the ambiguity.
How quaint.
Enter BANI—the framework that's less "strategic poker" and more "Calvinball during an earthquake." Where VUCA assumed change had patterns we could detect, BANI acknowledges that the patterns themselves are dissolving faster than we can recognize them. It's the difference between navigating rapids and discovering the river has turned into mist.
Imagine this, you think you’ve built the most robust talent pipeline in Silicon Valley. Partnerships with top universities. A two-year leadership development program. Succession plans three levels deep. Then, one Tuesday morning, your top AI engineer resigned. By Friday, 40% of the AI team had followed. Not to a competitor—they'd all joined a startup that didn't exist the previous month. Like watching dominoes fall, except the dominoes were on fire, and they were falling upward.
That's brittleness in action. Systems that appear strong, even antifragile, until they suddenly aren't. Your talent pipeline isn't a pipeline at all—it's more like a house of cards in a wind tunnel. And this brittleness is everywhere, hiding in plain sight behind our polished processes and refined frameworks. But brittleness is just the opening act. Let's talk about the ambient anxiety that's become the background radiation of modern work. The Great Resignation—or the Great Reshuffling, or the Great Reprioritization, or whatever we're calling the phenomenon where 47.4 million Americans quit their jobs in 2021 alone, according to the U.S. Bureau of Labor Statistics—barely scratches the surface. Microsoft's 2023 Work Trend Index found that 76% of employees would struggle to prioritize their work if leadership changed direction. Not when. If. Because in an anxious system, change isn't just expected—it's assumed.
This isn't the productive stress of a deadline. It's the existential dread of not knowing if your role, your team, or your entire industry will exist next quarter. It's every employee becoming a mercenary, not because they want to be, but because loyalty to an organization that might evaporate feels like bringing a knife to a gunfight. As one CHRO told me over coffee last week"We're not managing human resources anymore. We're managing human anxiety."
And then there's nonlinearity, where cause and effect don't just disconnect, they start dating other people. Imagine a mid-sized software company deciding to implement "Wellness Wednesdays"—no meetings, flexible hours, encouraged self-care. Engagement scores would surely improve, right? Wrong. Within six weeks, productivity plummeted 30%. Not because people were slacking, but because the informal Wednesday check-ins had been the glue holding cross-functional projects together. Remove the meetings, and suddenly nobody knew what anyone else was doing. But wait, it gets better. When they tried to reverse the policy, engagement scores tanked even harder. Employees saw it as the company "taking away" a benefit. The company ended up in a worse position than where they started.
In linear systems, small inputs create small outputs. In nonlinear systems, a butterfly in Beijing doesn't just cause a hurricane in Houston—it might cause a sudden shortage of software engineers in Seattle, a spike in demand for prompt engineers in Singapore, and somehow, inexplicably, make everyone in Stockholm decide to become beekeepers. One resignation triggers fifteen more. A minor policy change causes a talent exodus. A casual comment in an all-hands meeting becomes the catalyst for a cultural revolution nobody saw coming.
Which brings us to incomprehensibility, the final boss of the BANI framework. When the U.S. Bureau of Labor Statistics reports that the median tenure for workers aged 25 to 34 is just 2.8 years, we nod knowingly and cite "generational differences" or "the gig economy." But what if the real answer is that we simply don't know? What if the system has become so complex, so interconnected, so influenced by factors we can't even perceive, that comprehension itself is a luxury we can no longer afford?
And just when you think you've wrapped your head around BANI, along comes the skill half-life crisis to really mess with your mental models. According to the World Economic Forum's 2025 Future of Jobs Report,”if the world’s workforce was made up of 100 people, 59 would need training by 2030. Of these, employers foresee that 29 could be upskilled in their current roles and 19 could be upskilled and redeployed elsewhere within their organization. However, 11 would be unlikely to receive the reskilling or upkskilling needed, leaving their employment prospects increasingly at risk.” While global job numbers are projected to grow by 2030, existing and emerging skills differences between growing and declining roles could exacerbate existing skills gaps. Skill gaps are categorically considered the biggest barrier to business transformation by Future of Jobs Survey respondents, with 63% of employers identifying them as a major barrier over the 2025- 2030 period. But that's practically geological time compared to what's happening in tech. A recent Stack Overflow survey found that the half-life of technical skills has dropped from 5 years to just 2.5 years. And that's the average. For AI-adjacent skills? We're measuring in months, not years.
Consider the tragic tale of prompt engineering—the skill that was going to be the next gold rush. From "doesn't exist" to "must-have skill" to "largely automated" in 18 months flat. If skills were cryptocurrency, prompt engineering would be Luna: worth $119 in April 2022, worth $0.0002 by May. Companies that spent millions building prompt engineering capabilities are now watching those investments evaporate faster than venture capital at a WeWork reunion.
So what's a talent leader to do in this brave new BANI world? How do you plan for a workforce when you can't predict what skills you'll need next quarter, let alone next year? The answer, surprisingly, may not be more sophisticated prediction tools.
What if the answer is to stop predicting altogether?
Instead of five-year plans, operate in 90-day sprints. Instead of rigid talent pipelines, maintain talent clouds that form and reform based on project needs. Instead of predicting the future, build systems that can adapt to any future. It's jazz, not classical music. Improv, not Shakespeare. Street basketball, not chess.
Organizations should be building organizational radar systems —continuous monitoring of weak signals that might indicate emerging trends. Think about tracking everything from TikTok hashtags to patent filings to GitHub repository growth rates, looking for early indicators of skill shifts. Instead of betting on one vision of the future, smart organizations are placing multiple small bets. Rather than big betting on Return to Office think about running multiple organisational and team structures simultaneously—from traditional organisational hub hierarchical teams to AI-augmented pods to fully distributed networks. When the industry shifts, you don’t have to transform; just scaled up the model that was already working.
The holy grail is antifragile design—systems with Adaptive Resilience that don't just survive chaos but actually get stronger from it. What if you deliberately introduce random "chaos events" into their organization—surprise team reshuffles, sudden project pivots, arbitrary constraint additions. Like a controlled forest fire, these small disruptions prevent larger systemic failures. Every policy, every process, every structure is treated as a hypothesis to be tested, not a solution to be implemented. The new mantra isn't "fail fast"—it's "learn constantly."
Here's the paradox: organizations that have given up on prediction are actually performing better than those still clinging to their crystal balls. A recent Deloitte study found that companies with "adaptive" workforce strategies saw 2.2x better financial performance than those with "traditional" planning approaches. Why? Because they waste less time planning for futures that never arrive and spend more time building capabilities to handle whatever does arrive. It's like the difference between trying to predict the weather and building a house that works in any weather. One is increasingly impossible; the other is just good engineering.
The shift from VUCA to BANI isn't just about new frameworks—it's about asking entirely different questions. Instead of "What skills will we need?" ask "How quickly can we develop any skill?" Instead of "How do we retain talent?" ask "How do we make every departure strengthen our network?" Instead of "What's our five-year plan?" ask "What can we sense right now?" Instead of "How do we reduce uncertainty?" ask "How do we thrive in uncertainty?"
The irony is that abandoning prediction doesn't mean abandoning data—quite the opposite. The organizations mastering BANI-world adaptation have invested heavily in what amounts to data infrastructure on steroids. They're building sophisticated skills taxonomies that can evolve in real-time, creating knowledge graphs that map capabilities across their entire ecosystem, and developing APIs that can instantly surface talent capabilities from any corner of their organization. Think about building a "skills fabric"—a living, breathing data foundation that tracks not just what skills people have, but how quickly they acquire new ones, what adjacent capabilities they possess, how their skills combine in unexpected ways and how this compares to the outside industry and their competitors. The goal isn't to predict what skills will be needed, but to maintain perfect visibility into what skills exist at any moment, how they're evolving, and how fast they can be deployed. It's like having perfect inventory visibility in a warehouse where the products keep shape-shifting. This isn't the old world of annual skills assessments and static competency frameworks. It's continuous capability sensing, that can detect skill emergence from project work, collaboration patterns, even the tools people choose to use. The deeper and richer these data foundations, the more nimbly organizations can pivot when the next incomprehensible shift arrives.
You know what's funny? Besides everything, if you've developed the requisite BANI-world gallows humor. The organizations that are thriving in this new reality aren't the ones with the best plans. They're the ones who've accepted they can't plan at all. They've traded their crystal balls for kaleidoscopes. Instead of trying to see the future, they've built organizations that can dance with whatever future shows up.
It's messier. It's more uncertain. It's definitely more anxiety-inducing. It's also more honest. Because if the past five years have taught us anything, it's that the future isn't just unknowable—it's stranger than we can possibly imagine. And maybe, just maybe, that's exactly the opportunity we've been waiting for.
Whilst standing in the ruins of your five-year workforce plan think about how to pivot and learn to surf chaos. And honestly? It's way more fun."
Who knows? By the time you finish reading this newsletter, the half-life of skills might have dropped again. BANI might have been replaced by another acronym. The entire concept of "work" might have evolved into something we don't recognize. And that's okay. Because in a BANI world, the only prediction that matters is this: whatever happens next, it won't be what we expected.
And we'll be ready for it anyway.