Data as an asset
We all tend to assume that data is a great and glorious asset. How solid is this assumption?
- Yes, data is one of the most proprietary assets an enterprise can have. Any of the Goldman Sachs big three* — people, capital, and reputation — are easier to lose or imitate than data.
- In many cases, however, data’s value diminishes quickly.
- Determining the value derived from owning, analyzing and using data is often tricky — but not always. Examples where data’s value is pretty clear start with:
- Industries which long have had large data-gathering research budgets, in areas such as clinical trials or seismology.
- Industries that can calculate the return on mass marketing programs, such as internet advertising or its snail-mail predecessors.
*”Our assets are our people, capital and reputation. If any of these is ever diminished, the last is the most difficult to restore.” I love that motto, even if Goldman Sachs itself eventually stopped living up to it. If nothing else, my own business depends primarily on my reputation and information.
This all raises the idea — if you think data is so valuable, maybe you should get more of it. Areas in which enterprises have made significant and/or successful investments in data acquisition include:
- Actual scientific, clinical, seismic, or engineering research.
- Actual selling of (usually proprietary) data, with the straightforward economic proposition of “Get once, sell to multiple customers more cheaply than they could get it themselves.” Examples start:
- This is the essence of the stock quote business. And Michael Bloomberg started building his vast fortune by adding additional data to what the then-incumbents could offer, for example by getting fixed-income prices from Cantor Fitzgerald.*
- Multiple marketing-data businesses operate on this model.
- Back when there was a small but healthy independent paper newsletter and directory business, its essence was data.
- And now there are many online data selling efforts, in niches large and small.
- Internet ad-targeting businesses. Making money from your great ad-targeting technology usually involves access to lots of user-impression and de-anonymization data as well.
- Aggressive testing by internet businesses, of substantive offers and marketing-display choices alike. At the largest, such as eBay, you’ll rarely see a page that doesn’t have at least one experiment on it. Paper-based direct marketers take a similar approach. Call centers perhaps should follow suit more than they do.
- Surveys, focus groups, etc. These are commonly expensive and unreliable (and the cheap internet ones commonly irritate people who do business with you). But sometimes they are, or seem to be, the only kind of information available.
- Free-text data. On the whole I’ve been disappointed by the progress in text analytics. Still — and this overlaps with some previous points — there’s a lot of information in text or narrative form out there for the taking.
- Internally you might have customer emails, call center notes, warranty reports and a lot more.
- Externally there’s a lot of social media to mine.
*Sadly, Cantor Fitzgerald later became famous for being hit especially hard on 9/11/2001.
And then there’s my favorite example of all. Several decades ago, especially in the 1990s, supermarkets and mass merchants implemented point-of-sale (POS) systems to track every item sold, and then added loyalty cards through which they bribed their customers to associate their names with their purchases. Casinos followed suit. Airlines of course had loyalty/frequent-flyer programs too, which were heavily related to their marketing, although in that case I think loyalty/rewards were truly the core element, with targeted marketing just being an important secondary benefit. Overall, that’s an awesome example of aggressive data gathering. But here’s the thing, and it’s an example of why I’m confused about the value of data — I wouldn’t exactly say that grocers, mass merchants or airlines have been bastions of economic success. Good data will rarely save a bad business.
Related links
- I first wrote up this point in a 2005 Computerworld column, and added a text-analytics nuance a year later, but since then I seem to have talked about it much more than I’ve written it down.
- Please always keep in mind the risks to privacy in whatever you do.
Comments
9 Responses to “Data as an asset”
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“Big data can’t save a bad business”: Of late, the casinos haven’t been doing so well either!
— Jerry
I think data protection, both in the security sense and in the “backup and disaster recovery ” sense is a neglected area. Getting more without protecting it is irresponsible but common.
Data — assuming its quality and complete – has enormous value to the analytical organization. Of course, this means devoting the resources to build the skills needed to adequately complete the necessary tasks. In a recent IDG SAS survey it was quite obvious that most organizations are not at that point yet with under 20 percent ranking their organizations at highly capable of any of the key requirements.
Peter Fretty
Curt
“Determining the value derived from owning, analyzing and using data is often tricky — but not always. Examples where data’s value is pretty clear start with:
Industries which long have had large data-gathering research budgets, in areas such as clinical trials or seismology.
Industries that can calculate the return on mass marketing programs, such as internet advertising or its snail-mail predecessors.”
I’m somewhat surprised you havent mentioned Financial Services as the definitive proto-business for ‘data as an asset’ that predates internet advertising. Financial products are merely contracts of ownership or debt, i.e data, and profit is driven by identifying and reacting to data (news), and state is recorded/fabricated as data. Sure, you can buy and sell orange juice futures, texas sweet crude and pork bellies, but no-one in the industry makes anything from them other than money (data).
Venkat,
I think electronic-only products are different from data. Heck, for all practical purposes Linda’s books are electronic-only, but I don’t count them as data.
Bloomberg’s data acquisition includes tediously digitizing the terms and conditions of various financial instruments. If they’re the only vendor doing that, then in some sense they own proprietary data about the bond/derivative/whatever. But that’s a very different thing from owning the financial instrument itself.
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