Commercial progress entails the ceaseless overcoming of both strategic and operational challenges. At the nub of each, is a problem that if not solved retards advancement of some sort. A useful way for management teams to engage problem solving is to divide them into three categories:
- A combination of or a transitioning between
This distinction was originally proposed by Gregory Treverton and was expanded upon by Malcolm Gladwell in his book “What the Dog Saw, and Other Adventures. The distinction matters. The nature of the challenge they present and the manner in which each gets solved differs. Puzzles and mysteries may both present high levels of complexity but their archetypal makeup and “solutioning” vary across an interesting array of traits.
Puzzles are problems that have definitive answers but lack key information required to get to them. Puzzles are solved by sourcing the missing data and rationally solving, via a sense making or solutioining model for the required outcome. Optimizing a stock model, detecting fraudulent financial activity or writing a complex piece of software are examples of puzzles. The problems and outcomes are definable, parameters are clear, information is gettable (albeit difficult) and the solutioning logic understandable or even pre-codified.
Mysteries are problems that have approximate and contingent answers that may have too much or inappropriate information. Mysteries are characterized by difficult to figure sense making or solutioning mechanisms. This is further complicated by the often-asymmetrical nature of the parameter relationships and data needed to solve them. A mystery has an approximate answer best gotten at via the use of judgment, iteration and an adaptive sense making framework. Optimizing your media spend across traditional and proliferating media platforms, launching a new and innovative product into an emerging market space, predicting a future state political dispensation and competitorresponses as a determinate of market attractiveness, are mysteries.
Thinking in this way forces us to start making explicit the differences between defining and solving problems, open vs. closed ended problems and how we need to adapt when confronted with too little, too much or imperfect information
Strategy in practice offers both mystery and puzzle problems. One of the most difficult strategy challenges is the need to investment in assets, resources and activities in the present based on a bounded understanding of the future. The future is by its nature a range of potential outcomes. The ten-year economic impact of BREXIT on the UK economy is contentious and filled with a wide array of competing views. Each scenario has a myriad of data, relational logic, assumptions and predictive outcomes. The end games are materially different, ambiguous and yet plausible given the sense making framework deployed. Within this context, should you build your much-needed factory in the UK or France, increase your automation spend as a wage escalation hedge, sell off selected European assets, reconfigure your supply chain etc. Your banked-on future is contingent and no amount of current data can solve the need for clarity. Judgement trumps analytics. We either shorten our decision horizons to more proximate futures or back a certain range of future state spectrums. In so doing we start to transition from mystery to puzzle. Information needs become more specific and available, sense making frameworks become more nuanced and scenario odds shorten. BEXIT is thus a mystery that will deconstruct itself into a puzzle over time.
Solving Puzzles and Mysteries
Puzzles are typically solved by refining the information you have and/or finding ways to access missing or better information. Once attained we can apply rational analysis, solving for the desired outcome. The truth confesses in a clear an unambiguous manner.
Mysteries are solved through hypothesis, experimentation, iteration and refinement. This process gathers and shapes insight. It builds on an increasingly refined sense making mechanism delivered through experiential feedback. You meander your way towards an acceptable answer. Mysteries are less solved and more discovered.
Puzzles and mysteries become more difficult to engage when the nature of the problem shares attributes of both. Using an abstract example, establishing the number of birds in flight in the world at some point in time, is a case in point. There is a definitive answer but we lack the information needed. Practically the sourcing of such information is improbable. We are thus left with approximate answers. Does this classify as unsolvable puzzle or a puzzle nested within a mystery?
The management implications are as numerous as they are subtle:
- Have we defined the problem correctly?
- Is this an information or sense making problem?
- Is there a definitive answer or solution?
- Do we have the correct and/or appropriate information?
- Do we have sufficient information?
- Are our information gathering mechanisms appropriate for the challenges we face?
- Does more information help or retard our ability to solve the problem?
- What principles underpin judgement based decisions?
- How are we judging, valuing and interpreting experiential based outcomes – progress or waste?
- Are we using the correct decision making approaches given the nature of the problem we face?
- How do we deal with big here and now decisions within the context of contingent futures?
- How do we move from mysteries to puzzles?
Puzzle or Mystery?
Given the above how would you classify the following:
- Missing Malaysian MH370 airline
- The Trump – Russian election collaboration and manipulation claims
- Countering the spread and threat of terrorism in large cities
- Implications of North Korea delivering on their nuclear warhead objectives
- Global warming’s 50 year impact on agricultural yields