When Vodafone, one of the largest telecommunications companies in the world, wanted to eliminate inefficiencies from its massive purchasing operations, it turned to big data process analytics.

Vodafone provides a range of services including voice, messaging, data and fixed communications. It runs mobile operations in 26 countries, has partnership with mobile networks in 49 more and fixed broadband operations in 17 markets. As of September 2016, Vodafone had 470 million mobile and 14 million fixed broadband customers.

To support these customers, Vodafone relies on an array of equipment and services from suppliers around the globe.

The source-to-pay process, responsible for managing the procurement activities in Vodafone, now relies heavily on big data technology to identify process gaps and deviations from the standard procedures.

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Vodafone last year set up a big data process analytics team within source-to-pay to focus on business excellence and creating the “perfect purchase order,” according to Israel Exposito, global process lead for the big data process mining initiative. The main goal was to quickly determine where inefficiencies and deviations are driving up costs or delivery times.

The company also wanted big data analytics conducted in real time with 100% transparency to all users, so there would be “one version of the truth.”

One of the factors that drove the company to leverage process analytics was the sheer volume of its purchasing operation. The global company annually manages more than 800,000 purchase orders, 5 million invoices and 40 million assets.

This all adds up to more than 10 terabytes of data that Vodafone houses in various storage systems and applications such as its enterprise resource planning (ERP) system, SharePoint document management system and other data stores. The company uses SAP’s HANA relational database management system as its main storage platform.

Vodafone’s big data team deployed Celonis Process Mining software from German software company Celonis. The vendor’s Process Mining software is a form of data mining that is able to analyze internal business operations based on event logs.

The Celonis software reconstructs what happens in a business activity, such as creating purchase orders, learns how the operation works and detects any hidden vulnerabilities, all of which allows managers to quickly determine the root cause of the issues and take immediately corrective actions.

By eliminating errors in its procurement activities, Vodafone can maximize catalogue buying and speed the release of a purchase order to a supplier.

“The basic idea is to extract in real time insights from event logs, recorded by systems such as ERP, SharePoint or workflow systems,” Exposito says.

The perfect purchase order (PO) initiative is one of more than 20 big data projects the department has launched in the source-to-pay area. Other initiatives focus on regulatory compliance and process automation.

“I like to use the Perfect PO initiative—right-first-time ordering—as the perfect use case on how big data by process mining enabled us to transform the business to perform on a world class level,” Exposito says.

The goal of the project was to have 80% of its purchase orders produced without errors. “When we kicked off this initiative our Perfect PO ratio was at 73%. Only six months later we over-achieved the 80% annual target by hitting the 85% level.” That means 85% of the purchase orders are created correctly the first time, without any mistakes or need for reworking. In addition to the increase in perfect purchase orders to 85%, time to market improved by 20%.

The Celonis technology enables this improvement by alerting the department of the need for fixing data at the source,” Exposito says. “Big data told us also where we had low automated transactions, so we could improve by using robotic process automation.” Low automated transactions are those in which a big level of manual human interactions is still needed. Robotics processes are designed to automatically replicate the same actions that humans would take, but without errors and at a higher speed.

“It means that business decisions are based on facts, and no longer on assumptions,” Exposito says. “We used to have many complex reports coming from different sources telling us that something went wrong. Now, with process mining, we get only one version of the truth and what’s more important is we can quickly answer the question of why did it go wrong? We now detect weaknesses and anomalies and have the ability to get to the root of identified problems.”

Prior to deploying the Celonis product running a root cause analysis was taking about two days. Now the company gets answers on the fly, Exposito says.

The big data analytics effort in PO has come with challenges, including convincing people in the company about the need for data process mining.

“We still see some people confusing big data process mining and business intelligence,” Exposito says. “I believe this is a normal symptom, as the big data world has just emerged. We have had to reinforce the fact to our employees that although they are related they aren’t the same. Big data analytics isn’t another BI initiative. It builds upon it.”

Big data analytics “is about extracting valuable insight from data and not only about showing KPIs in a dashboard,” Exposito says. “It is about empowering decision makers with analytics that will eradicate gut feel decision-making and enable the data-driven organization of the future.”

While the initial effort is aimed at the source to pay function, Vodafone is planning to extend it into other business functions. Exposito, however, says it’s too early to elaborate on these efforts.

“Big data analytics is crucial for leading companies to outperform its peers,” Exposito says. “Most industries will leverage data-driven strategies to innovate, compete and capture value. We felt the need to make data speak and bring the light to further process efficiencies as well as to control compliance.”

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