Procurement in the Data Age

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Data has become “currency” as Ginny Rometty, CEO of IBM, describes their corporate strategy for competitive advantage. Analytics has grown in popularity to gather, standardize, interpret and deliver competitive value for companies in the digital age. Procurement organizations in today’s world must “evolve or die” in Big Data to retain a seat at the leadership table. Focus areas in Big Data should include contracts, spend, tail spend and sourcing.

In a data-driven world, the Procurement organization would require data from different systems, business units and functions to analyze spending patterns and come up with actionable insights to source & negotiate smarter. The procurement functions have been dealing with large amounts of data and analyzing spend, suppliers, contracts, payments, etc. Spend data analytics is the basis of all the strategic value addition efforts that go on at the side of procurement.

The Proacure Experience: creation of a holistic value-based experience

Proacure’s experience in delivering value through analytics has shown that every spend analytics process must begin with consolidating, cleansing and categorizing spend data before analytics can begin. More often than not, procurement organizations find themselves working with unstructured data (e.g. siloed ERP systems, budgeting, contract file repositories, purchase orders, travel and expense reports) with varied formats, data definitions and business rules. Identifying baselines, “rogue” spend, and supplier contract information becomes labor intensive and a scavenger hunt. Although companies achieve savings through this manual effort, Proacure offers technology leveraged solutions which take much of the grunt work from procurement and sourcing leaders.

Through client partnerships, Proacure has helped procurement organizations move up along the procurement maturity curve with operational benefits and cost savings. Now that you have your data cleansed, “report-able” and insightful, what’s next? Will the firm be spending the same amount on the same items in the future? How do leaders account for these changes to define corporate strategy?

In the Data Age, it is time for companies to move from descriptive spend analytics to predictive analytics. Predictive models empower companies to be able to see what opportunities to target for greater savings in the future.

How does Big Data Analytics position itself amidst the procurement process?

The next big thing that procurement is concerned about is Big Data Analytics, which has become a hot topic as well. Big data analytics helps manage the three Vs- Volume, Variety and Velocity of data.

For the procurement professionals, the first step in the process of embracing the philosophy of big data analytics is about connecting the internal data sources such as spend, contract and supplier data with the external data sources. These include the supplier ratings, news feeds, market insights through primary and secondary research etc.

The Procurement professionals would like to stay abreast with the technological innovations to help them optimize the strategic sourcing processes. They would like to answer questions like:

 

  • How will I be able to identify the suppliers who are risky to my business?
  • What are the early signs to capture and how to mitigate such risks?
  • How will a cyclone impact the demand for the input raw materials?
  • Can data analytics on the consumer behavior patterns help me to plan the spot buys for my product in a better way?

While it is good to think of the scenario where data analytics can answer these questions, it is also important to understand that at the end of the day, the outcome of any data analytics process depends on the quality of the input data and the answers we can infer from it. What is most important is that we should have a good understanding of both the qualitative and the quantitative data sources to be utilized for our analysis, since we are going to get the quality insights based on how good the underlying data is.

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