big dataIf there is an oft-cited and “classic” example of big data use, it’s the story of an enterprise that capitalizes on parsing and analyzing unstructured and semi-structured data about its customers from the Internet and other data sources that formerly went unnoticed. But the other part of big data that is “big” is effective use of structured data that comes in from systems of record like customer master files, order and shipping files, and even financial charts of accounts. If you look at the historical accumulation of this system of record data, it is “big” in the sense of the volume it presents. It remains a largely untapped data resource that traditional corporate reporting only scratches the surface of.

System of record

The other element of big data that doesn’t get talked about as much as breakthrough information producing competitive advantage, is the operational agility that effective big data analytics can produce. It is the structured, system of record, data that contributes the most to this agility – and its contribution is vested in the reformation of business processes that can be tuned for better performance.

Here are some current business process headaches that poor system of record data in companies creates:

Part descriptions initially entered by the company’s engineering department do not reflect the nomenclature that is used in the field, so someone has to manually go in and change them. Meanwhile, service reps have a hard time determining the correct parts to use in their daily work.

Part and assembly revision levels are difficult to synchronize for an aerospace company that must maintain three different sets of part and assembly levels – one that is internal, one that reflects the original part numbers from OEMs, and one that reflects part and assembly numbers that military customers want assigned.

Corporate charts of accounts become so complicated that it’s difficult to meet month-end close dates.

These situations have been “accepted” by companies. For years, they have put their shoulders to the wheel – correcting data “on the go” and as needed in the course of a business day. But now that the rise of big data has suddenly made dealing with data fashionable, they are beginning to look at the cost of poor and replicated data that manifests itself in inefficient business processes that take too long and limit corporate agility.

Relevance from data

“Companies want to see business relevance from their data,” said Rex Ahlstrom, Chief Strategy Officer at BackOffice Associates, which focuses on the quality of ERP (enterprise resource planning) data and has “Expect More from Your Data” as its company motto.” In the past, data quality has been a focus of IT, but now more companies want to see an alignment of the business with IT so they can improve the quality of the data that support their business processes.”

Ahlstrom explained how automated tools could analyze data from systems of record, determining which data really were necessarily to support a business process, and which were extraneous.

By Mary Shacklett read more

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