Five Thinking Skills Every Strategist Needs
Developing evidenced-based strategy requires a straightforward approach to discovering the signal in the noise.
Life would be easier if everything we needed to know in solving a client problem was listed neatly and orderly in a single spreadsheet; Unfortunately, relevant data and information often come from multiple sources and can sometimes have conflicting or unclear meaning. The trick for me was always determining what was important, why and the ramifications for the client’s existing resolution or strategy i.e. what needed to change and how.
Certainly, as a strategist I was thrilled when I thought I had discovered and understood everything I needed within a single data source – how convenient was that! What I quickly learned was the more data sources I looked at the less clear were the causes of the problem and the less confident I became about the corrective action needed. For example, when last month’s revenue fell, looking only at sales executive performance and product portfolio sales might conceal the real source of a problem: a fall in customer satisfaction or a new competitor product launch or price adjustment eroding competitiveness.
But first, some of my key learning in solving client problems
The problem is not always the problem. Before rushing into analysis, first sense-check you’re dealing with the right problem. Is what the client describes the symptom(s) of another problem that exists elsewhere?
Many business problems resemble each other more than they differ and so try to avoid reinventing the wheel. Clients assume your prior experience and know-how is being leveraged in your recommended next steps. That’s what they’re paying for.
Every client situation is unique. Avoid rushing to a conclusion without evidence or using ‘cookie-cutter’ recommendations without first checking their contextual-fit.
80% of an effect under study will often be generated by 20% of the examples studied. Think about inputs and outputs, causes and consequences, effect and results.
Establish the most important variables or factors causing the problem (try and get to just three) and first focus your attention here. This saves a lot of unnecessary peripheral analysis and time.
Don’t lose sight of the bigger picture. Regularly take a step back and ask yourself: is this the most important thing I should be working on right now to solve the problem?
If you don’t know the answer – tell the truth, admit you don’t know but convince the client how you’re going to get to the right answer.
I use five techniques to help me see the bigger picture and make the right commercial judgements for clients. Ordinarily, I make use of them all and in the order listed below.
Commonalities – searching for similarities and patterns in data. This can be represented in the form of an increase/ decrease in the unit of measure, variance, timing, frequency and impact. For example, a fall in sales in the same week every quarter or below average customer satisfaction for a product category.
Differences – searching for and explaining differences in the data. This is especially useful when looking at data over time or when contrasting between different situations and conditions, for example different retail outlets, people, hire potential.
Segmentation – searching for categories that can be profiled to make heterogeneous groups. In its simplest form dividing the data into quartiles or comparing the top 20% of customers (by annual spend) with the rest. A more complex analysis would involve profiling distinct categories/type (e.g. behaviour descriptive) and the discriminating variables between them.
Linkages – searching for the cause and effect relationships that exist. A rise in one variable being strongly correlated with an increase or decrease in another. I’ve learned that correlation doesn’t always mean causation but it’s the place to start.
So what? – ultimately, this is what clients pay for. It often manifests itself in a direct question from the client: What does your analysis reveal or not reveal about what I should or shouldn’t do to solve ‘X’? – the evidence=-based recommendation.
Whilst it sounds counterintuitive and too time consuming, I try to make a new chart everyday about everything new I learn in the problem-solving process and revisit my initial hypothesis about the client problem and possible solution. This often results in me changing my mind about what the problem is, it’s causes and the solution. It also helps me keep focused and ensure I’m working on the right things tomorrow to advance my thinking.