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5 Innovative Ways Procurement Can Use Data Analytics

We’re all inundated with data in this digital age, but here are some truly useful ways it’s helping buyers work more efficiently and effectively in this competitive business environment.

Big data. Key performance metrics. Predictive data analytics. Structured and unstructured data. The list of terms used to describe the vast quantities of information being generated by organizations—and the methods for using that data—seems to be proliferating as quickly as the data itself. Figuring out what to do with all of this information can be downright daunting, but the good news is that procurement is in a prime position to use data to develop reports, perform spend analysis, assess suppliers, and do compliance checks.

“While more sourcing and procurement teams have adopted and are employing modern sourcing and procurement tools that facilitate data collection, management, and analysis,” Corrina Owens writes in “Big Data = Big Opportunity for Procurement,”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 advances in automation, a data-centric approach can often replace the laborious information compilation, organization, and dissemination processes that used to take weeks or even months to complete. Here are five innovative ways procurement departments can get in on the game and use data analytics to develop more streamlined, efficient buying processes:

1. Extracting more value from the sourcing process. By collecting and analyzing suppliers’ past performance data, as well as current market pricing and risk assessments, procurement can adopt a data-driven approach to awarding contracts to suppliers, rather than awarding them based on lowest price, an existing relationship, or “gut feel.” “Sourcing teams can also examine shipping and carrier data to help them optimize sourcing routes and freight transporters,” Owens writes, “and help them extract more value from the logistics side of the process.

2. Pinpointing changing customer demands. Data analysis can be used to identify changing customer requirements and predict changes in supply and demand for electronic component purchasing, sales automation platform maker Orbweaver writes in “5 Ways Data Analytics Improve the Electronic Component Supply Chain.” “It can also be used to improve customer service and loyalty programs, to make planning and logistics more efficient, and to eliminate waste, error, and duplicated effort throughout an organization,” Orbweaver adds, noting that data analytics can also help bring in and connect many disparate elements to make prediction possible in a way that it wasn’t previously. “In using data analytics to build a predictive model, a company can anticipate fluctuations in demand and adjust available supply accordingly.”

3. Getting the best quality products at the best possible price. In a competitive environment, the supply chain is constantly pressed to become more cost-effective. Using data analytics, procurement can continually compare real-time pricing and availability from suppliers—incorporating the history of order accuracy, transportation and logistics costs, and many additional variables. “Utilizing analytical insights,” Orbweaver points out, “electronic component purchasing officers can be confident that they are always receiving the highest-quality product available at the best price.”

4. Obtaining both internal and external views on spend. We live in the era of big data, but many procurement organizations rely on internal views of spend. “Too many are still getting to grips with past spend visibility, only using their own taxonomies, supplier information, and transactional data,” Spend Matters points out in its “Procurement Benchmarking in the Era of Big Data” report. “This is a shame, because data offers much more potential.” 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. “This paradigm shift may be difficult to master,” Spend Matters notes, “but its consequences are nothing less than revolutionary.”

5. Tapping unstructured data. Encompassing everything from text files (e.g., word processing, spreadsheets, and presentations) to e-mail to social media (data from Facebook, LinkedIn, and Twitter), unstructured data is an untapped goldmine for today’s procurement departments. “Text analytics can give insight into supplier information on social media,” CIPS points out in “Five tips: How procurement can use big data effectively.” Visualizing social media data related to a supplier, for example, can give buyers timely insights into their purchase decisions. “Real-time data will allow you to monitor strategy implementations and allow the tweaking of plans to increase success,” CIPS adds. “For example, monitoring maverick spend on a new contract can be quickly identified and reduced.”

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