In earlier posts, we used a recent New York Times article as a jumping off point to explore the concept of big data as applied to procurement and supply chain. Today we'll focus on excerpting a few areas of the piece that we think warrant particular attention. We'll also share some key takeaways to consider. The first highlight is really more of a proof point than anything else: investments in big data tend to pay off. Based on an analysis of three professors, the NYT references a study that "suggests that data-guided management" that is "spreading across corporate America" is "starting to pay off."
To wit, of "179 large" in this academic study, "those [organizations that adopted] adopting 'data-driven decision making' achieved productivity gains that were 5 percent to 6 percent higher than other factors could explain." Procurement and supply chain takeaway: big data is not just about breakthrough analysis, it's about making your current resources that much more efficient and effective (thank you Hackett, as your research we're guessing also shows).
Next up: mining data and the power of crowds and their activities. "The predictive power of Big Data is being explored -- and shows promise -- in fields like public health, economic development and economic forecasting. Researchers have found a spike in Google search requests for terms like "flu symptoms" and "flu treatments" a couple of weeks before there is an increase in flu patients coming to hospital emergency rooms in a region. Procurement and supply chain takeaway: understand what the queries and actions of your employees and suppliers might signal. For example, might an increase or change in search and shopping activity through a P2P system signal change in demand patterns? Might the frequency with which smaller suppliers from a particular geography market logging into P2P/e-invoicing portals to check on payment status (or make requests for early payment) signal rising supply risk?
Finally, "Big data has its perils, to be sure. With huge data sets and fine-grained measurement, statisticians and computer scientists note, there is increased risk of 'false discoveries.' The trouble with seeking a meaningful needle in massive haystacks of data, says Trevor Hastie, a statistics professor at Stanford, is that 'many bits of straw look like needles.'"
Procurement and supply chain takeaway: place as much emphasis on the analytics piece of big data as acquiring data itself. Moreover, evaluate the cost of false positives by considering the cost of false negatives -- and changes within or triggering data sets not being flagged at all. This is where a trained and empathetic expert eye with a background in procurement and supply chain -- not to mention context at the company, supply base and industry in question -- is likely to prove far more expert than a random offshore data cruncher with strong analytical skills but without the same context.
Kudos to the NYT for such a useful primer on big data. You can read the entire article here -- and watch for our continuing coverage of this topic.