Spend Matters welcomes a guest post from Teja Kappagantula of GEP.
Many mature procurement organizations have by now perfected how they go about strategic sourcing, leaving quite a few of us in procurement to ask what the next big thing is. Everyone is talking about big data, but sometimes we wonder what all this fuss is about. Hasn’t procurement been in the forefront of embracing large chunks of data in search of value for quite some time now? Isn’t spend data analytics our bread and butter? After all, spend data analytics is the basis for most of our strategic value addition efforts. Why then the perception that we are late in using big data?
The answer lies in the way the world perceives big data. Reading up about big data reminds one of the story of the elephant and the blind men. Every industry, every function, and even every person seem to have their own definition of what constitutes big data analytics. But most concur on two things – first is that big data as a philosophy is largely being able to manage the three v’s (volume, velocity, and variety of data sources), analyze, and thereby provide meaningful insights for the business; the second is that big data is no substitute for big brains.
For procurement, the first step in using big data analytics is largely about tying in the internal data sources such as spend data, contract data, and SRM data with the external data sources such as the Internet, supplier databases, financial ratings, and various news feeds in order to have “anytime, anywhere” information about our supplier markets at our fingertips. Strategic sourcing is now passé. For us to continue to grow in strategic importance to the business, it is essential to stay on top of our game. This approach to big data analytics for procurement will help us answer questions like:
- How can I identify the suppliers with whom my supply is at immitigable risk? What are the early signs of such trouble?
- How will El Niño affect the demand for my input raw materials?
- Will data analytics on the buying patterns and behaviors help me plan my spot buys better?
While it is nice to have a genie in a bottle that can answer such questions, it is also important to know that ultimately it is just one tool at our disposal. The outcome of any data analysis is only as good as the input data quality and the questions the analysis tries to address. We need to have a good handle on the right qualitative and quantitative data sources to be used for our needs. After all, we are going to determine the quality of the insights from the big data analytics and the decisions taken thereafter.
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