Strategy formulation: The board said, “Use AI.” Now, prove it!

Your board has put you under pressure. It insists that you use artificial intelligence (AI) to improve the organisation’s strategic plans. Now, it wants proof.

Strategy VP Nancy is reeling. Before today’s meeting, she felt her team had done the hard work of incorporating AI into strategy development. Her board presentation was thorough. But board members remain dissatisfied.

“How do we know these changes are net positive?” some asked. They were right to ask. Plans filled with AI trendslop, the generic, trend-chasing advice LLMs tend to produce, were everywhere, and Nancy could not be sure AI was not playing the same tricks.

If this story resonates with your strategy team, you are in good company. A recent Financial Times/Infosys report shows that 75 per cent of directors expect AI to significantly enhance strategic decision-making, yet warns that “decision quality does not improve by default”. A Harris Poll found that 89 per cent of CEOs believe AI can develop an equal or better strategic plan than one of their executives.

If you sponsor corporate strategy, consider getting ahead of complaints that new plans look just like the old ones. How should you respond?

Your informed instinct

Process-improvement practices such as TQM, Lean and Six Sigma offer decades of guidance. Surely they can guide your use of AI techniques. Even the most skeptical board member could not deny these proven, measurable methodologies.

Consider 3M, a famous innovator. In 2001, it hired James McNerney, who arrived with a GE-inspired Six Sigma playbook. The factories benefited. But the labs struggled: researchers chafed under an approach built on conformity and standard measures. Consequently, the approach was later scaled back in R&D. The tool was not at fault. It was a hammer used where a screwdriver was needed: a placement error.

Like lab innovation, corporate strategy should produce something dramatically different from what came before. A possible Vision 2050 Jamaica should do more than extend today’s Vision 2030 by another 20 years. That makes strategy more like lab work than factory work. What should strategy practitioners do?

Different improvement methods

One organisation faced this problem decades ago. In the US Army, no two missions or training exercises are identical, so a fixed process could not be the unit of improvement. In response, the Army developed the After Action Review (AAR): a short post-event session built around four questions and facilitated by an external party.

Using this approach means acknowledging one limitation. The AAR only looks backward. Unfortunately, a corporate strategy cannot be fully proven until years after its formulation, once outcomes accumulate. That is too late.

Borrowing the AAR method means finding questions that can be used before a strategy is complete. It is a bit like designing software. You want to know the process is broken before the final product is shipped. Is there a way?

Find the defect before it ships

Fortunately, software teams have such a procedure. PayPal’s engineers write a one-page proposal, then run a pre-mortem on it to identify issues and expose blind spots. The team’s experience is worth considering.

A pre-mortem is a defect hunt. In this context, a defect is something wrong with the work that can be identified, ranked and fixed. I see the business world already developing defect-detection mechanisms for strategy creation. The one I use with clients is called Strategy Process Engineering for Analysis and Refinement (SPEAR).

The approach begins by dividing a strategy project into six logical stages. SPEAR adds a defect check at each gate between stages.

As you approach the next gate, stop the action for a few minutes. Ask the team: Where are we? What did we just do? What defects can we see? Which ones matter? What can we fix now? What do we record? What is the next gate?

Then, repeat the process at the following gate.

The proof your board members crave is the record you compile. In effect, you are building a rigorous defect library that can benefit future teams.

Importantly, the library also builds a case for AI’s contribution. The technology can now help remove, detect or prevent defects. That is a far cry from the popular “do stuff faster” credo, which has little place in most strategy-creation projects.

So, what does Nancy do differently? She can now bring the board a concise list of defects found, fixes made, and lessons recorded. Her proof is the record itself.

Francis Wade is the author of ‘Perfect Time-Based Productivity’, a keynote speaker and a management consultant. To search his prior columns on productivity, strategy, engagement and business processes, send email to columns@fwconsulting.com.