Determining the value of enterprise data

Volumes have been written about the return on investment (ROI) and total cost of ownership (TCO) of enterprise data deployments. Virtually every vendor has an analytical tool or calculator that spits out attractive PowerPoint charts about how much savings or efficiency a data initiative will bring to a company.

But I’m constantly shocked, in my dealings with corporate leadership, that so little attention is placed on the lifetime value of the data within the repository. As with social media, many corporate leaders are obsessed with “vanity metrics” related to the size of the database with no mention of data hygiene.

Added to this is the tendency for enterprise IT (and corporate management for that matter) to disproportionately focus on the investment in “containers” as opposed to deriving asset value from the “contents.”

Now it goes without saying that e-commerce-only enterprises like Amazon survives on their ability to develop predictive behavior metrics related to the value of customer profiles. They know the probability of a purchase — that “people who bought A also bought B & C” — using algorithms, and they know the incremental revenue derived from each product recommendation.

At the other end of the spectrum, many enterprises are just starting to transform from a traditional to data-driven business. In these cases, just getting through the data storage process is considered a victory.

Since many of these companies are not using databases for transactional purposes, there is the misperception that the asset value directly relates to how much money a user spends. But in a data-driven enterprise, the more critical data-point is much that data file contributes.

For example, many media companies are going through an evolution from print to Web to data. The reduction in print advertising revenues and the decreased margins on digital ad units has forced publishers to transition to a data or performance-based business. The “performance” is related to the ability to provide data insight on readers to third parties.

In the past the “circulation file” was used to mail magazines or newspapers to qualified subscribers and to encourage them to renew their subscriptions. The key metric in this use was the subscription renewal rate. In many media firms, this metric was confidential.

As a result of the shift to performance-based advertising, though, the “subscriber” database must be deeper and richer than ever before. Every “subscriber” is now a potential source of revenue, not just from the act of charging a subscription to his or her credit card. In the performance-based model, media companies may entice a qualified subscriber to click on a vendor’s white paper or webcast, resulting in a sales lead that can generate revenue for the publisher.

The convergence of IT, Marketing and Data Science occurs at this point. Technology must provide the platform that allows this engagement, to move customers through a series of revenue-producing clicks and provide insight on the user’s behavior.

Any B2B or B2C company that uses the company or divisional database to convert leads to sales needs to be looking at this same metric when determining ROI or TCO on the deployment. In fact the content of the database can become a revenue stream that increases ROI or reduces TCO, given the degree of contribution.

In my past, I would evaluate the asset value of a company like a publishing company on such metrics as subscriber renewal and advertising revenues. However in the 21st century data-driven enterprise, the key determinant becomes data hygiene and the value of user engagement, which results in insight that vendors are willing to pay high prices for.

This reinforces the importance of enterprise IT to work closely with the lines of business that generate structured and unstructured (social media interactions, conversational) data. And it behooves CIOs to incorporate increases in data asset value into ROI and TCO calculations.

To do this, deeper questions must be asked that go far beyond the qualitative aspects of data and zero in on more quantitative contributions to the P&L.

Does your company have a means or process of valuing the contents of your database…especially if you’re not an e-commerce play?

RELATED LINKS

Leveraging the value of big data with automated decision making

Big data is useless (and even dangerous) without this key ingredient

How to avoid drowning in a data lake

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