A key issue for action-driven NAMs in unprecedented times is how to derive meaningful and actionable insights from well-intended but over-simplistic averages currently produced by ‘internal’ research.
A major problem with this approach, and a great deal of business reporting in general, is that it presents senior management with a host of averages:
category average margin
average space in store
average basket size
average customer spend
average shelf life etc.
We know these are important measures - the buyer keeps reminding us - but as measures, they have gone too far. In other words, they are a starting point, but we need to find ways of getting behind the averages, and data animation can help.
Guy Cuthbert, of Atheonanalytics, in a fascinating article, starts with a retailer’s average gross profit margin and shows via exploration and visualisation of underlying data, how to discover and communicate far more about the richness of shoppers' buying behaviour, helping us move towards the goal of any commercial analytical exercise – the oft-requested “actionable insight.”
In his graph-by-graph process he drills down and visualises by Customer Segment, Product Category, Sub-Category, Individual Customer, and converts a 2-variable scatter-plot to a 3-variable bubble-chart. He then adds total Profit (or Loss), using colour for this fourth variable, to highlight the variability in cash impact of the customers.
We are then in a position to loop back to the original question posed by the buyer – “How can we improve profitability?” – via a simple visual explanation of profitability, which can be explored by Customer or Product, and a recommendation to review customer discounting policy in the light of long-term customer value.
In other words, the data animation process has helped us move away from Averages of Averages, and provides a reasonable balance between simplicity and complexity, yielding actionable and communicable insight, far better than the average....
