A couple years ago I looked into some issues a large retail supplier had with some of their processing. One of my recommendations was to increase the amount of historical data they were storing so that they would be able to look backwards in time to the actual documents that were being questioned by their customers. At the time they were only maintaining a 90 day history. That meant any disputes regarding transactions older than 3 months became difficult or impossible to respond to in any meaningful way.

That recommendation was made during a time when storage space was becoming significantly less expensive, but before the concept of big data had really taken hold as a standard - or at least a reasonable option for data retention.

I came across a report from McKinsey & Company that discussed the concept of big data and a study they had performed. The report dates back to 2011 and covers 5 domains. One sector they studied was "retail in the United States." Even at that time (before many new tools and storage techniques, not to mention cost reductions) the report indicated, "Big data can generate value in each [sector]. For example, a retailer using big data to the full could increase its operating margin by more than 60 percent."

Check that out again - an increase in its operating margin of more than 60%. OK that's 'operating margin' and not overall profitability. But what other kinds of measures could even be considered that could reduce expenses and create this kind of an increase? How many employee salaries would need to be eliminated in order to do this? And besides the obvious financial benefits, what other business benefits and advances could be derived?

Here's an excerpt from McKinsey's report that discusses some of the other benefits big data could deliver:

"...as organizations create and store more transactional data in digital form, they can collect more accurate and detailed performance information on everything from product inventories to sick days, and therefore expose variability and boost performance. Leading companies are using data collection and analysis to conduct controlled experiments to make better management decisions; others are using data for basic low-frequency forecasting to high-frequency nowcasting to adjust their business levers just in time."

Where is your data going? Does it fall off the data cliff after a few months? I'd suggest there is value to the data that moves through your supply chain interactions in ways that have yet to be explored and monetized.