A problem well stated is a problem half solved
What does it mean?
There are many variations of this quote including - If i had one hour to solve a problem I would spend 55 minutes diagnosing the problem and five minutes solving the problem - attributed to Einstein. If I had six hours to chop down a tree I would spend four hours sharpening my axe - attributed to Abraham Lincoln. Laying the groundwork to solving a problem can not be underestimated - too often we see projects that have focused on the wrong question, or have embarked on a project with an incomplete or only partial understanding of the problem to be solved. This inevitably leads to costly errors and time spent delivering an outcome which is not desired.
Why do we believe it’s important?
Often the problem as described to us as we enter a client engagement is not the problem we find when we get there. Framing a problem properly ensures that all aspects are acknowledged by all stakeholders. Issues identified may have different priorities; however, it is best to understand the problem in its entirety. Only once the problem statement is precise, comprehensive, and agreed, should we allow teams to begin thinking creatively about solutions (across people, process and technology).
How do we put it into practice?
We jointly set a series of input questions designed to unpack a problem statement, and investigate issues with our clients. We collect enough evidence to validate our hypotheses, and ensure that all stakeholders are part of the process to ensure we all agree we have defined the scope of the problem (and what is out of scope). This sets out clearly the logical flow of issues we will experiment around and prove with the solution moving forward.
This team has previously worked with a FTSE 100 client in which two halves of the organisation (commercial and operational) had differing views on the problem and therefore the solution. Had we not gone broad before we went deep, and not created a consensus prior to implementation, this would have led to an operating model and tech solution that was rejected by a significant portion of the company and never adopted wholesale. Worse, it wouldn't have solved the critical business challenge at hand.