A global leader in petrochemical manufacturing and refining has a truly worldwide reach, with offices or operations on every inhabited continent, spanning more than 150 countries around the world. The company provides a wide range of products and services in the oil and gas arena, including exploration, refining, and developing new and improved technologies to help make petrochemical processing better and more efficient.
The large petrochemical company faced a challenge that was familiar to many of its companion companies listed on the Fortune 500. The company had increased in size over time through a mixture of organic growth and strategic mergers and acquisitions. As the business grew, its expansion not only brought in new revenue streams, it also increased the number and complexity of business applications and information systems within the enterprise.
To create better information that was both more reliable and more accessible across business or geographical units, the company began to implement global data warehouses, massive information repositories designed to store standardized and validated versions of all critical business information.
One of these data warehouses was a resource for product data, containing details, descriptions and sales of the company’s products. This data would allow the organization to make an accurate assessment of worldwide market needs and product availability.
Unfortunately, product data is notoriously difficult to standardize. Even within the same business, companies have different ways to describe products and brand names. The company’s worldwide presence made the problem even more difficult by adding language differences and other cultural variables, making the task of building a global product data warehouse significantly daunting.
The worldwide petrochemical provider selected DataFlux technology to help them assess the data that they had – and validate and verify information before loading it into a data warehouse. Through pre-built and customizable matching algorithms, the company could automatically standardize data as it was loaded into the data warehouse.
With DataFlux solutions, the company was able to integrate business rules and existing logic into the software. Prior to implementing DataFlux, business analysts had to look at the data to understand that HD meant “high density” while HDTO stood for “high density transmission oil.” DataFlux technology incorporated those definitions – and associated permutations of those words or phrases – to create matching rules that could identify similar data and standardize information across millions of product records.
Before implementing DataFlux, the oil and gas company had to manually browse through records on a monthly basis to standardize data across sites. This process typically took two weeks each month to finalize, meaning business analysts spent roughly one-half of their time on this mundane, laborious task.
With DataFlux technology, the oil company could capture the knowledge of the business analyst in the matching and standardization routines within the software. The monthly routine – which once took almost two weeks to complete – now takes only 10 seconds.
As an added benefit, the oil company receives better data on products. Now, it can make better evaluations of product performance and create more accurate, usable projections for successful product offerings in the future.