“Big Data” Means Unstructured Data for Supply Chain Managers

Feb. 21, 2013
Here are five recommendations for dealing with a wider diversity of data sources.

As supply chain managers get more information from more sources, they must also deal with new forms of data. Pundits have characterized this as the era of Big Data, and as supply chain managers deal with data gathered from the customer’s customer to the supplier’s supplier, they find the data is no longer structured.

This is the conclusion of a new report from Supply Chain Insights LLC titled “Big Data: Go Big or Go Home.”

“We cannot listen, test and learn about consumers without embracing unstructured data,” writes the report’s author, Lora Cecere, founder of Supply Chain Insights LLC. “While the largest complaint in enterprise supply chain systems is dirty data, we will slowly realize that the current data is not dirty, but different. We will also learn that the road before us will magnify the differences. Supply chain leaders have not seen anything yet.”

This report offers five recommendations for dealing with Big Data:

• Sidestep Hype. There is no ONE Big Data solution. Instead it is a set of techniques for using large data sets that have high velocity and data variety. It is not about stuffing new forms of data into old architectures. It is about building organizational capabilities by learning and networking.

• Start with the business need, analyze the data set requirements and then look for appropriate technology. The new data forms do not neatly fit into traditional enterprise applications.

• Most of the initial funding for Big Data will need to be investment dollars targeted at value-based outcomes, not cost reduction initiatives. That's why business leaders need to drive the funding, guided by IT leaders.

• Start where the data is the most available and the business requirements are the highest. After plotting these projects, look for data source similarities and build a skills capability matrix to begin the process of education and awareness.

• Don’t be limited by traditional paradigms. Think unstructured, mobile, streaming and geolocation data.

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