Is Big Data Really the Next Big Thing in Procurement?

Many mature procurement organizations have by now, perfected the art of strategic sourcing, leaving quite a few of us, the procurement wonder, what is the next big thing. With Big Data becoming the buzz word for businesses across the board at the turn of the decade, it is but natural for us to join the party. But sometimes, it makes us wonder, what’s all this fuss about Big Data? Haven’t we, procurement, been in the forefront of embracing large chunks of data in search of value for quite some time now? Isn’t the 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 embracing the Big Data?

The answer lies in the way we perceive, or rather, 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 all or most of them concur on two things – first, that Big Data, as a philosophy is largely being able to manage the three Vs – volume, velocity and variety of data sources, analyze and there by provide insights meaningful for the business; second, that big data is no substitute for big brains.

For us, the procurement, the first step in embracing the philosophy of 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 world wide web, supplier data bases, financial ratings and various news feeds capably to have at our finger tips, the anytime anywhere information about our supplier markets. 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 and 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 unmitigable risk? What are the early signs of such trouble?
• How will the El Nino impact 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 at the end of the day, 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 poses/tries to address. At the end of the day, we need to have a good handle on what are the right qualitative and quantitative data sources to be utilized 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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