Getting the Question Right is at the Heart of Supply Chain Analytics

“If someone asked me to come up with the answer to the world’s problems in an hour, I’d spend the first 55 minutes coming up with the right question.” – Albert Einstein

I heard this quote from someone about a week ago, and it got me thinking more carefully about the importance of beginning with the right research question, and being careful to delineate what it is we are trying to do.  The need to identify a critical business issue is at the core of creating the right digital analytics.  The problem, of course, is not the data, but the question we are seeking to answer using the data.

As noted by many executives, there is too much data, and the issue is more on understanding what data is important, and what data holds the clue that lends insight to the right problem.  For example, the Internet of Things is exploding with massive amounts of sensor data that is being collected, but people don’t know what to do with it!  Genomics as a field is also exploding, which effectively gives us a “part list” or bill of material for the human body.  However, how this information can be used to help make us more healthy is still a mystery!

In a sense, supply chain managers must begin to think more like research and development scientists, and learn the art of discovery.  What happens in an R&D environment?  It begins with scientists, who are very good at being curious, exploring new ideas, and developing hypotheses, testing them against lab or other empirical data, and extending their knowledge as they learn what works and what doesn’t.

Similarly, supply chain organizations need to be able to define testable hypotheses and be continually querying their supply chain systems to understand what is happening according to their mental models.  The importance of cognitive awareness is key here.

A common excuse is that “our data is terrible.”  This is no excuse.  There are ways to collect the data and cleanse it, to extract it for a singular purpose.  But you need to know what data you need.  And to do that, you need to know what you want it for.  Hence the question.

But this also requires that teams be able to challenge one another to create new mental models, and be allowed to do so.  As noted in my earlier blog, challenging one another in a team environment with new ideas is at the core of this capability…

So ask yourself:  Do I have the question right?