Traditional management and decision-making processes were designed and normalized when things were stable and predictable. For better or for worse, that world is gone. Instead, thinking of decision-making and leadership as a continuous building process - similar to how scientists innovate through the scientific method - improves success rates of both current and future initiatives. This isn’t about following a rigid process—rather, it’s about adopting a mindset of ongoing experimentation, intentional progress tracking, and continuous improvement.
Problem Validation (Asking the Right Questions)
In science: Researchers start by clearly defining the question they’re trying to answer. They observe symptoms, form initial hypotheses, and look for patterns that might explain what’s really going on.
In business: Decision-makers must avoid jumping to conclusions about why results are lagging or teams are unhappy. Instead, applying tools like root-cause analysis and systems thinking guide understanding beyond the obvious symptoms and on to the core issues for more intentional resolution. This includes clarifying the business case—why and when it’s worth investing time and resources to address this particular challenge, and the level to which it makes the most sense to address it.
Research & Roadmap (Gathering Information and Planning the Approach)
In science: Before running experiments, scientists study existing research, collect background data, and develop a hypothesis about what might solve the problem. They plan their experiments with care, considering what evidence they’ll need and how to handle different outcomes.
In business: Decision-makers and their teams can do something similar. Relevant information can be hiding inside the company and outside—results of related past initiatives, market trends, competitor benchmarks, economic forecasts, and relevant case studies. They then use this information to map out a plan that includes triggers for changing course, if results are either more or less in the direction expected - even if they don’t exactly know what those plans would be yet. By laying out a clear roadmap with checkpoints, they know not just where they’re headed, but what they’ll do if conditions change unexpectedly.
Implement & Iterate (Testing Solutions and Adjusting as Needed):
In science: With a hypothesis in hand, scientists test it through experiments. They set follow through with pre-set checkpoints, collect data across multiple variables, and keep detailed records of every step and outcome. If the results aren’t as expected, they refine their approach.
In business: Professionals can treat the strategy rollout like a controlled experiment. They use established analytics—both early indicators and long-term metrics—to see if things are moving in the right direction. They schedule regular check-ins, track everything, and remain open to changing their approach if initial results aren’t matching expectations - long before the initiative fails as a whole or excess resources are wasted. By documenting these attempts, they also create a valuable record that the team can learn from in the future.
Solution Validation (Reviewing Results and Confirming What Really Works): In science: Even if initial experiments show promising results, scientists don’t assume their hypothesis is proven. They re-check data, run additional tests, and confirm that it’s their specific intervention—rather than a random fluke—producing the effect.
In business: Avoid the temptation to claim victory too soon. After implementing an initiative, it’s important to not just assume success. It’s important to look at the data to confirm that the presumed solution, not some unrelated or coinciding factor, is driving the results. Instead, reviewing records and refining the understanding of what truly directed outcomes prevents wasting time through persistent “fixing” of what wasn’t broken or letting flawed solutions persist.
Manage & Mitigate (Ongoing Care and Adaptation):
In science: A proven theory still needs ongoing scrutiny. Conditions can change, and new discoveries can emerge. Scientists revisit their conclusions over time and remain ready to adjust their understanding. In business: Professionals must resist the “set and forget” habit. Team performance expectations must often be echoed over time, markets inevitably evolve, competitors react, and the workforce changes. Continuous oversight ensures that the newly implemented solution isn’t unraveling behind the scenes. By keeping an eye on developments, adding safeguards, and knowing when to make small course corrections, you can ensure that once-stable solutions remain stable and that they don’t morph into new, hidden problems down the road.
The Cost of Failure to Adapt
Following these steps when addressing complex problem solving or strategy design scenarios —defining the real problem, doing your homework, testing solutions thoughtfully, confirming what truly works, and staying vigilant—sets the stage for individuals and teams to operate ‘in the grey’ with steady improvement, smart growth, and long-term resilience. Failure to do so costs companies upwards of $1B in failed initiatives annually.
Start now. Pick one ongoing initiative and apply a more scientific approach through PRISM (Problem Validation, Research & Roadmap, Implement & Iterate, Solution Validation, Manage & Mitigate). Identify the root cause of a nagging issue, research the environment around it, then run a small experiment with clear checkpoints. Document everything, and confirm that your changes actually move the needle. Finally, keep watching for new signals of trouble and use the insights you gain to guide future decisions.
With the minimal ramp-up time for PRISM framework integration, it's possible to replace outdated processes with a practical, objective approach. Over time, you’ll find larger problems feel more comfortable to tackle with results that are more predictable and aligned with goals than traditional management practices.