While holed up inside, like many others on the East Coast of the United States, suffering from record-breaking rainfall and watching the path of Hurricane Joaquin, I found a perfect metaphor for handling a problem in explaining analytics.
Many executives bemoan the fact that it seems to take forever for the analytical staff to deliver results. They ask, “Why can’t I get my answer by Friday?” I respond, “If you want an answer by Friday, then you needed to have made an investment six months ago in what I refer to as foundation systems.”
What are foundation systems?
Foundation systems are everything from, of course, analytical tools and databases, the big budget items, to a great deal of small important details including: query code that correctly links tables so those links don’t have to be researched in a time crunch; code to do the inevitable preprocessing to correctly calculate meaningful indicators like the marketing concept RFM (recency, frequency, monetary); checks for missing and bad data, etc.
The experienced analyst can name several other examples of potentially time consuming efforts that must be handled before the answer can be given on Friday. The analyst knows that if previous work has been accomplished, reusable code developed, and data cleansing accomplished, then the time to complete the analysis is shorter. This, however, requires the investment of time -- that is free time for the analyst to investigate the data, understand the data and develop useful concepts.
Needless to say, this response of “foundation systems” is a long answer, and while it may be understood, it is not exactly what I would call a “sticky” concept, one that is quickly understood and remembered.
A strong foundation is important
While waiting out the rain, an article in The New York Times caught my eye. The article, “Hurricane Joaquin Forecast: Why U.S. Weather Model Has Fallen Behind” discussed the issue that European models were proving to be more correct in forecasting an eastern movement of the hurricane to miss the mainland of North America. The discussion of the modeling was interesting, but it was a passage in the middle of the article that got my attention.
“Perhaps the biggest shortcoming {in the US models} is in data assimilation — the process of taking all of the available data and building an initial description of the atmosphere. The model runs from that, but a perfect model of the wrong atmosphere will yield a wrong answer.”
Wow, simple and clear – to better forecast hurricanes you must better understand the initial atmosphere. A perfect metaphor. To understand the impact of a new marketing program, you need to have a good foundation (model and data) of the market – the atmosphere.
A perfect metaphor – that is a “sticky” concept.
If you would like to learn more about explaining analytics, register for my SAS Business Knowledge Series course, Explaining Analytics to Decision Makers: Insights to Action.
