The PricingBrew Journal guide, Visualizing Data: Seeing the Trees in the Forest, makes a great case for leveraging data visualization in the exploration and diagnosis of pricing anomalies and margin leaks.
In the guide, Walter R. Paczkowski, Ph.D. highlights and explains the three data features that a pricing analyst must be able to identify and understand in order to devise sound pricing strategies and make solid pricing recommendations. And, he even walks readers through a real-world pricing analysis—complete with waterfalls and boxplots—to drive home the concepts.
Along the way, Walter makes an intriguing point about the efficacy of data visualization versus people’s affinity for large tables of data:
Very simply put, we’re visual creatures. We have a difficult time identifying complex patterns, let alone trends and anomalies, in tables of numbers. Yet, we love large tables of numbers because they convey a false sense of authority.
It’s so true, isn’t it?
We may know full well that simple waterfalls, scatters, charts, and boxplots are the best ways to really get control of the data, and identify and illustrate what’s actually happening in our businesses. But at the same time, we can’t help deriving a certain sense of security and comfort from the monstrous tables of numbers behind those simpler constructs.
Recognizing this facet of human behavior, you can leverage it to send a strategic message. You can tap into peoples’ natural affinities for big tables of numbers to lend credibility and authority to your findings and recommendations.
But as Walter makes clear through the real-world case he illustrates, scanning large tables of numbers is not a very effective way to arrive at those findings and recommendations in the first place. And data visualization makes it possible to identify trends, patterns, and anomalies that would be challenging, if not impossible, to discern from a large table of numbers—no matter how comforting all those columns and rows may be.
