Purchasing | Feature

BI Buy

Two universities apply the principles of business intelligence to procurement and purchasing, with significant results.

At a time when higher education is enduring stomach-churning budget cuts, institutions are under more pressure than ever to make each dollar count. While cuts in staff and services are often an unpleasant part of the solution, the drive toward greater efficiency also means getting smart about purchasing. And, increasingly, universities and colleges are turning to business intelligence tools to help them monitor spending and find economies of scale.

BI has long been used in higher education to tackle a range of campus issues, but spending is a different kettle of fish altogether: Typically, each university division or department handles its purchasing separately, and often uses different systems to manage contracts, purchase orders, and invoices. Despite the challenges, two institutions--Bowling Green State University (OH) and Cornell University (NY)--have shown that, with an e-procurement system in place and a lot of hard work, BI tools can lead to significant savings and increased control over how university dollars are spent. And, interestingly, the schools have taken radically different approaches to the problem.

The Macro Approach
When Bowling Green investigated e-procurement solutions as a way to centralize purchasing and increase contract compliance, it discovered that it was not alone in its search. "Three other state schools in Ohio were looking for a similar solution, and another three were already running SciQuest, an e-procurement tool," says Andrew Grant, director of business operations at Bowling Green. "We felt that trying to have a like system across our seven campuses would not only bring some uniformity but would also allow us to look at each other's purchasing data from a centralized point, and to be able to procure with larger volumes--and, therefore, better prices--than we'd have as individual schools."

As a result, in June 2010, Bowling Green adopted the SciQuest e-procurement tool, and became part of an Ohio-based purchasing consortium with Ohio University, Shawnee State University, Kent State University, Youngstown State University, Miami University, and Wright State University.

Although SciQuest is not specifically designed to be a business intelligence tool, the data mined from the shared purchasing histories of the seven schools have provided Bowling Green and its partners with plenty of savings. From an examination of the schools' spending history for maintenance, repair, and operations, for example, the consortium identified a range of identical items that the schools all purchased separately--at a higher price than they would have paid by buying together.

"We can now see that we buy 10,000 units of a specific brand of light bulbs, and another school in the consortium buys 5,000," explains Grant. "We can combine those purchases into a market basket to be purchased from a single vendor, and we can use our purchasing history data as leverage when getting bids from vendors for the lowest price."

In fact, initial data gathered on SciQuest showed a surprisingly high number of technology vendors serving the needs of departments within Bowling Green and the six other schools in the consortium. Grant wanted to deal with just a single tech vendor, so he worked with CDW-G to negotiate a deal for the consortium. The deal eventually grew into a tiered, discounted contract that applies to all 14 schools in the Ohio State University system, Ohio's community colleges, and all the private universities within the state of Ohio--87 schools in total. "We now have a relationship with a single vendor with volume discounting on every tech-related category that's better than any group-purchasing organization [GPO] contract in the market right now," notes Grant.

On Bowling Green's campus, the SciQuest e-procurement system has also reduced rogue and noncontract spending in non-tech areas by creating a virtual centralized purchasing department. Online catalogs of more than 40 preferred vendors, with which Bowling Green or a third-party GPO has negotiated favorable contracts, are available to university staff through the SciQuest tool. Purchase orders are automatically generated through the system, rather than being handwritten and processed into separate systems by each department.

"These automated processes mean that we have more contract compliance and more purchasing data than ever," says Grant.

By using SciQuest to consolidate the school's contracted vendors and make catalogs of preferred vendors available, Bowling Green has averaged savings of 15 percent. Plus, Grant can identify any purchases made from vendors with whom Bowling Green has not negotiated a contract, allowing him to follow up.

"SciQuest drives people toward the contracts," explains Grant. "It drives people toward the partners that we want them to use, with whom we've negotiated the best deals."

The Micro Approach
Like Bowling Green, Cornell University wanted to centralize its spending and reduce costs when it first began exploring the use of BI tools in purchasing. Instead of leveraging the power of a consortium, however, Cornell focused its efforts on creating a data system that could drill down to the stock-keeping unit (SKU) level, and had the flexibility to create reports on a variety of data points so sourcing managers could identify cost-cutting opportunities across the university's campuses. Back in 2007, the school had implemented a third-party system to do this, but found it too rigid for the higher ed market.

"We needed to be able to separate data into restricted and nonrestricted funds, federal dollars and state dollars," explains Thomas Romantic, senior director of supply channel management and business services. "We needed to have more control over how the data was classified, and to be able to modify how we classified the data as our knowledge grew."

In 2008, Cornell began work with Tonto Verde, a Phoenix-based software company, to create Spend Viz, a robust data-analysis and reporting tool. Spend Viz pulls purchasing information from Cornell's existing payment-requisition, procurement-card, and e-procurement systems to provide a complete view of enterprise spending, including what's being purchased, by whom, and from whom. Detailed levels of classification can be retroactively modified as reporting needs change.

When the university unveiled the tool in July 2009, it simultaneously launched a five-year procurement-savings initiative on Cornell campuses. On the table was $450 million, out of which the school aimed to cut $30 million to $40 million by 2014. "That's an 8 percent to 10 percent reduction that we need to identify by using data to consolidate vendors, consolidate spending, and explore different ways of attacking things," notes Romantic. To date, the university has achieved $6.5 million in reductions through its use of the Spend Viz system.

As a major research institution, Cornell spends a significant amount on lab and scientific supplies. By running purchasing data through the Spend Viz system, the university was able to determine how much money was being spent with each of its supply manufacturers. It then leveraged the relationship between the manufacturers and their four main distributors to reduce the costs of the most common lab and scientific supplies.

"We're trying to spend with a distributor through a manufacturer," explains Romantic. "The manufacturer now provides discounts to us directly because they're getting visibility and recognition on campus that they weren't getting before." This approach alone has garnered savings in excess of $1 million.

And by tracking purchasing data to the SKU level, including quantity and historical pricing information, Cornell has been able to hold reverse auctions for commodities (such as toner), where three or four suppliers are invited to an online bidding event. For 15 to 30 minutes, vendors anonymously bid against each other in an eBay-style auction on a list of SKU numbers and corresponding quantities.

Before Spend Viz performed a SKU-level analysis, this type of bidding event wasn't possible at Cornell. "It's one thing to know that you're spending x amount on a specific commodity, but you need to know the specific SKUs that are driving that spending," explains Romantic. "With Spend Viz, we can use the historical pricing data to set a baseline to calculate our savings." Cornell's reverse auctions typically result in prices 10 percent to 25 percent lower than those established after years of bidding and renegotiations.

Although Spend Viz was intended to be an internal tool for Cornell's procurement office and sourcing managers, significant interest on campus has seen its use expand to 85 to 100 users in various departments.

These users can create and view department-specific reports with the tool's dashboard, and request the inclusion of data specific to their departments' needs. For example, the university's community-relations team tracked spending by ZIP code so they could determine how much money the school was spending with local businesses. "Because we designed the classification, rules, and business logic that apply to our data, we can easily go back and run the data through a reclassification program," notes Romantic. "It's very powerful, and it's why we created our own tool. You need to have control of your data and understand exactly how your data is being classified."

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