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Data value chain puts the focus on what matters most to a business

In his career running data management systems for consumer goods companies, Richard Beaver has found a formula for success: the data value chain.

Scot PetersenScot Petersen

Many things go well with beer: football, chips, burgers on the grill on a hot summer afternoon. How about data...

management? If you are Richard Beaver, a 20-year veteran of running data management systems at retail and consumer packaged goods (CPG) companies, then beer and data go together like pure Rocky Mountain spring water and the Cold Activated Can.

Beaver came to this conclusion while working at MillerCoors about four years ago. "I had a kind of a mantra," he said in an interview. "I visualized it for a group of people, and I drew a value chain for beer, from the acquisition of raw materials to the manufacturing process, transportation, marketing, sales and, ultimately, consumption. And then I overlaid the value proposition for data. From the creation of data, from source systems to the translation to master data, through the storage in a data warehouse, to the presentation layer in a business intelligence tool, to the business people making decisions off of it. It's the same model. There's a value chain of information."

The more you think about it, the more Beaver's data value chain analogy should make perfect sense to businesses that are customer-focused. According to the theory set forth by Harvard business professor Michael Porter back in the 1980s, the value chain is exactly that: a chain. Each link in the chain is important to every other link in the chain. If the production quality or transportation link gets broken, at the end of the chain you end up with a poor product and a dissatisfied customer. Bad link, skunky beer.

The same goes with data, only the "customer" at the end of the chain isn't a beer drinker; it's your CEO, or a business analyst, or another internal data user. Data has to be properly cared for, extracted from reliable sources, cleansed and presented in a way that makes sense to the data consumer, who then can use it to make sound business decisions. Good data, happy customer; skunky data, unhappy customer.

Give your data the respect it deserves

Richard BeaverRichard Beaver

"We treat our products with reverence," Beaver said. "We would never change the quality of the water that went into the beer. We would never change the type of yeast that went into the beer. But we don't treat our data the same way. We don't treat the information that we create about our business the same way we treat the thing we make in our business."

Beaver, who spoke in April at the SAS Global Forum in San Francisco as part of a panel on managing data as a strategic asset, told me that it's hard to actually put a value on data like you would on a balance sheet. But you can measure the risk to your company if your data isn't high quality.

The leaders in the retail industry, for instance, "have separated themselves from the pack of most of the other competitors in the space, because they have better control of their information," he said. "And by control, I don't just mean in a data warehouse. I mean their ability to analyze and act on the information, as opposed to being reactive."

Ultimately, it's the steps data managers take in setting up a data value chain that will make the difference in creating high-quality data. The technology comes second. Beaver recounted his post-MillerCoors experience at United Natural Foods Inc., a food distributor that he left recently to form a technology startup.

"Most companies' mistakes are when they start with the technology, right? 'Let's buy a BI tool, let's buy a data warehouse, let's buy something to facilitate change,'" Beaver said. "What we said was information governance and structure is paramount to success. Before we had tools we wanted to put in place an information governance structure run by the business, then start defining what the future will look like. And then we can go use that as the requirements for the new tools that we'll ultimately buy."

Mind the data gaps

Beaver's new venture is an extension of the experience he's gained over the years. GapNsnap is a mobile, cloud-based data collection app that enables consumers to identify and communicate out-of-stock items -- the "gaps" on store shelves. According to Beaver, retailers lose 7% to 10% of sales to out-of-stock items, which can add up to billions of dollars annually. For consumers, an out-of-stock item can lead to frustration, and possibly drive them to competitors. For the business, it's all about data -- or a lack of data when it's most needed.

"We are collecting information on the out of stocks, and the reason that's important is you can't see an out of stock today," Beaver said. "The reason we could never solve it in CPG is because you couldn't see it. You could infer it, with data, but you could never actually see it and know it had happened. And then the other piece was you couldn't do anything about it until a week later, when you inferred from the data that it did happen."

Beaver's plan is to create an out-of-stock data and analytics service for retailers and also reward consumers who are uploading the out-of-stock data with coupons or points toward purchases of products. It's a win-win for the companies and the customers, all through a strengthening of the data value chain. And that's a good value proposition for businesses in all industries.

Scot Petersen is the editorial director of TechTarget's Business Applications and Architecture Media Group. Email him at

Follow SearchContentManagement on Twitter: @sContentMgmt.

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