How to Justify Investing in Data Management

Loraine Lawson
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Five Ways to Know if Your Challenge Is Big Data or Lots of Data

The trend now is to view data as a business asset. This means the business should “own” aspects of data, such as data governance, data quality and data exploration.

What I don’t hear a lot about though, is who pays for data. A recent Forbes column by Gartner Research Vice President Doug Laney makes me suspect maybe not — especially when it comes to Big Data.

Infonomics: The Practice of Information Economics” is a mini-thesis on how organizations can start to assess the value of their information assets. Your CFO should love it, since it talks about things like trading data to avoid taxes and how data can translate into “found money” during acquisitions.

But for CIOs and other IT leaders, what’s relevant here is how “infonomics” — the economic impact of data and information — can be used to shape IT priorities and your budget.

“… organizations spend significant slices of their IT budget on information management,” he writes. “Only by measuring the comparative value that information delivers before and after this investment can they determine the ROI on information management initiatives. Otherwise these investments are perceived and recorded only as a sunk cost.”

One specific example: When it comes to IT security, organizations don’t quantify the value of the data being secured. Instead there’s a “broad assumption that information security solutions merely cost less than the probable economic loss over their lifespan,” he writes.

That can translate into both overspending to protect data with little value, while underspending on security to protect very valuable data. It’s the physical equivalent of using a padlock (or a bank vault) for protecting both the Hope diamond and a gum machine ring.


Central to his argument is the idea that data has a monetary value regardless of whether or not you’re using it. Generally, business leaders see data only as valuable in the context of decision-making.

Laney contends it should be viewed more like a brand name, copyright or patents. Its value isn’t just in how it’s realized, but in its potential value, he writes:

“Copyright, patents and brand are reported in financial statements - but not data. Case-in-point is the yawning gap between Facebook’s near $100B market valuation versus its book value of under $7 billion. As a pure information-based business, this suggests that Facebook’s off-balance sheet information assets generated by nearly a billion unassuming, unpaid information workers ostensibly are worth more than $90 billion.”

He also draws a comparison between data and physical inventory, which has value even when it’s sitting in a warehouse.

This idea is a long way from being broadly embraced, of course. Just as some financial experts see Facebook as overvalued, the courts have run hot and cold with this idea that data is an asset, he explains.

But even if the courts, insurers or accountants do not universally agree on the value of data, Laney’s list provides good fodder for CIOs hoping to justify data-related investments.

That said, the most reliable justification for data spending remains the fact that data supports better business decisions, according to IBM Big Data Evangelist James Kobielus.

“I think it’s better to focus on data’s instrumental value in decision support, which is, after all, the core function of traditional business intelligence and of a lot of big data, advanced analytics and data science applications as well,” Kobielus writes in a recent post. “If we tie data’s value to its potential in supporting decisions that lead to positive business outcomes, we have a sounder basis for valuation.”

But when you use that approach for an ROI, you can’t just base your calculations on any old data, he warns. For data to be valuable for business, it needs to be high-quality data.

“Clearly, what we’re valuing with such a framework is not just the customer data, but also the entire set of customer data management, governance and analytics practices,” he writes. “In fact, it’s pointless to put an economic value on the data itself if you fail to sustain this entire body of best practices. … Data’s quality and potential business benefit degrades to the extent that you slack off on governance.”



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