The 2025 Strategy playbook. What to do when you don’t know what to do.

One of my favorite Buddhist discussions talks about what to do when you don’t know what to do.  This sentiment seems to sum up my daily existence in 2025.  Maybe this also has a thread of truth for you as well.  In the end, the path forward is a combination of falling back on what you do know, what you believe to be true, those you can lean on, and those who have done it before.

However, this is not so simple when applied to business environments that are no longer merely complicated but genuinely complex.  Unlike simple systems—where few interactions yield highly predictable outcomes—and complicated systems—where many parts interact in patterned, analyzable ways—complex systems exhibit nonlinear interactions that can produce drastically different results from identical starting conditions. (Reference en.wikipedia.org.)

Three measures drive this complexity: multiplicity (how many elements), interdependence (how strongly they connect), and diversity (how heterogeneous they are). As these grow, so too does our inability to forecast outcomes using traditional analytic methods, since emergent behaviors lie beyond our cognitive maps.

Human decision-makers, constrained by bounded rationality, often misinterpret complexity as mere complication—risking costly mistakes when they assume past patterns will hold. (Reference on risk strategies arxiv.org.)  Cognitive limits mean that no single individual can grasp the full network of interactions in a large organization, and focusing too narrowly may blind us to systemic feedback loops.  Moreover, rare “tail” events, though infrequent, can dominate system trajectories, so models that rely solely on average outcomes underestimate true exposure.

A robust decision-making framework balances three types of predictive information: lagging indicators (what has occurred), current indicators (where we stand), and leading indicators (where we might go) (Reference: decision making under uncertainty en.wikipedia.org.)

Lagging metrics—like financial KPIs—tell us about past performance; current data—such as pipeline opportunities—reveal present conditions; and leading signals—scenario analyses or stress tests—illuminate potential futures.  Continually updating and integrating these buckets creates a more complete situational picture and reduces blind spots.

When true prediction is impossible, the best investments minimize dependence on foresight.  Employing a real-options approach—making small, reversible commitments that grant rights without obligations—locks in downside protection while preserving upside potential (Reference: Risk in decision making arxiv.org.)  Similarly, risk-reducing design and operations toolkits (RDOT)—including modular architectures, contingency buffers, and fast-fail experiments—provide strategic hedges that operate independently of precise forecasts.

Finally, decision-making in complex environments demands diverse perspectives and adaptive structures. Multidisciplinary teams, empowered to question assumptions, can surface hidden interdependencies and unintended consequences.  Reducing risk in complex decision models is critical. 

Here is a decision-making framework to minimize risk and uncertainty.

·  Acknowledge uncertainty and cognitive limits

Recognize that you’ll never have a full view of a complex system, so stay humble about your assumptions and remain open to new information.

·  Balance lagging, current, and leading indicators

Combine past data (what happened), real-time metrics (where you stand), and forward-looking signals (what could happen) to build a more complete picture.

·  Use small, reversible commitments (real options)

Make modest investments that give you rights—but not obligations—so you can limit downside risk while retaining upside potential as new information emerges.

·  Model extreme and rare events

Incorporate low-probability, high-impact scenarios into your simulations or stress tests to avoid blind spots created by relying solely on average outcomes.

·  Leverage diverse perspectives Involve multidisciplinary teams and challenge groupthink to surface hidden interdependencies and unintended consequences when information is sparse.

Moving forward when you don’t know what to do requires a bit of faith as well.  That is not easy when navigating constant change (impermanence) in a world that sometimes is moving far too fast.  By acknowledging our cognitive limits, diversifying thought, and combining forecasting with robust, flexible strategies, leaders can craft a decision-making framework that navigates complexity with resilience rather than paralysis.