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Business Intelligence: Using a Data Supply Chain to Focus on Data End Products
We’re not thinking about data the right way. That’s what Thomas Davenport, business management guru, is telling companies now.
Data should be treated like a product within a business and managed much like a physical product supply chain. Businesses need to work backward to determine what data enables the analytics and decisions that the company would like to be able to make. Once the end product is defined, the resources and path for achieving that goal can be derived.
The process flow of data moves from the point of creation to the end product, and along the way, much like a physical supply chain channels raw materials through design, production, and quality control processes, all phases of the data gathering and production steps are monitored, measured, and managed.
Davenport said that “companies have concentrated on the technical capabilities of data management, which are controlled by the IT function and are needed to acquire, store, and move data. This is no mean feat — building technical ‘pipes’ is a challenging job. But in so doing they have focused more on infrastructure and much less on the outputs: the data products that are used to make decisions, differentiate products and services, and satisfy customers.”
“Data supply chain management puts equal emphasis on all phases of data management — from collection to organization to consumption of data products. It’s a means of balancing the benefits of common data with those of unique and tailored data in products, and it’s equally suited to internal and external data. Relatively few companies employ data supply chain management, but those that do tend to report better results.”
