In this digital age, we’re all flooded with excessive amounts of data, but it can be put to good use too! Here are some truly beneficial ways data is helping buyers work more effectively and efficiently in today’s competitive business environment.
Big Data. Data Analytics. Key performance metrics. Predictive Data Analytics. Structured and Unstructured Data.
The number of terms for the massive quantities of information being generated by companies — and the methods for using that data — seems to be increasing as rapidly as the data itself. Figuring out what to do with all of this information can seem daunting, but on the bright side, procurement is in a prime position to use data to develop reports, perform spend analytics, assess suppliers and ensure compliance.
In ‘Big Data = Big Opportunity for Procurement’, Corrina Owens writes, “While more sourcing and procurement teams have adopted and are employing modern sourcing and procurement tools that facilitate data collection, management, and analysis, many teams continue to wrangle their data the old-fashioned way. Put another way, many sourcing and procurement teams continue to struggle against the rising tide of big data, which will continue to swell in the years ahead.”
Thanks to developments in automation, a data-centric approach can often replace the laborious information compilation, organization and dissemination processes that used to take months to complete.
Here are five ways procurement departments can use data analytics to develop more efficient buying processes
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Obtaining more value from the sourcing process: Procurement can adopt a data-driven approach to awarding contracts to suppliers by collecting and analysing suppliers’ past performance data, as well as current market pricing and risk assessments, rather than awarding them based on the lowest price, an existing relationship, or just taking a risk. Owens further mentions, “Sourcing teams can also examine shipping and carrier data to help them optimize sourcing routes and freight transporters, and help them extract more value from the logistics side of the process.”
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Determining evolving customer demands: Data Analytics can be used to identify the evolving requirements of customers and predict changes in supply and demand. It can also be used to enhance customer service and loyalty programs, make logistics and planning more efficient and eliminate errors and duplicated efforts throughout a company. By using data analytics to build a predictive model, an organisation can anticipate fluctuations in demand and regulate available supply accordingly.
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Receiving the best quality products at the best possible price: The supply chain is constantly pushed to become more cost-effective, especially in a competitive environment. Using Data Analytics, procurement can continually compare real-time availability and pricing from suppliers, incorporating the history of order accuracy, logistics costs, transportation and many other variables.
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Obtaining both internal & external views on spend: In the era of big data, many procurement companies still rely only on internal views of spend. Not realising its true potential, they are still getting to grips with past-spend visibility, only using their own taxonomies, supplier information and transactional data. For procurement, the opportunity lies in combining internal procurement data assets with relevant external data assets to benchmark performance against peer groups based on real data and in real time.
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Extracting unstructured data: Comprising everything from text files to email to social media, unstructured data is an unexplored treasure for procurement departments. Text analytics helps in understanding supplier information on social media. Visualising social media data related to a supplier, for example, can give buyers opportune insights into their purchase decisions. Real-time data allows you to monitor strategy implementation and modify plans to increase the success rate.