Data Monetization: Pie in the Sky?

Over the course of the last year increasingly more clients have been inquiring with us about the topic of “Data Monetization”. In other words, they wanted to learn more about how Informatica enables their ability to “sell” their existing data from operations instead of just archiving them away or deleting them. As you can imagine, this is especially difficult for industrial B2B firms, which do not consider themselves peers of firms like Amazon. Just like Digital Transformation, Data Monetization is a tremendously gooey subject. It can mean so many different things and almost everybody has a different twist on it. Moreover, there is no good reading available on it besides some high flying marketing fluff.

Today, I will remedy this situation by starting a couple of posts about how we at Informatica view Data Monetization. The goal is to go a few levels deeper than you may traditionally find in your Google searches.

First, what is it? Monetizing an organization’s data is already happening all over today. The good news of today is that by investing in your data management infrastructure, you are effectively monetizing your data. If you are not in the business of (digitally) transforming your internal operations with data already, get started with it first.

How, do you ask? De-duplicating, standardizing, linking, keeping lineage, transforming, moving and securing your data with a software tool enables your organization to be more productive by decoupling yourself from the legacy hand coding effort. It also ensures transactional integrity when it comes to order and service management, billing and other operational processes by ensuring missing, conflicting or incorrect data elements are minimized, thereby reducing process failure and rework. A secondary effect of this lack of errors is revenue assurance from process integrity, i.e. orders don’t linger, equipment does not fail, bills get mailed, etc. Third, by eliminating errors and legacy systems responsible for some of these, you are reducing cost; cost of service, cost of operations, cost of acquisition and so on. The question now is how your data can help your clients (B2B or B2C) achieve the same? What is the secret sauce you have within your data repositories? After all, research has shown; there is money in data.

The new currency is how quickly and effectively a hedge fund can develop new uses of existing data sets when combining it with massive amounts of historical data.

Realizing that you are likely not a hedge fund manager, when would it be prudent to execute on this approach?

There are 6 major factors you should evaluate:

  1. Market Share: Is your organization managing at least 20% of your core market’s transactions?
  2. First Mover: Are you the first, second or at least in the top 50% of your market competitors introducing such a product because if you are 80% of the available profit pool with go to you?
  3. Usage Rights: Do you have legal rights to re-use your client’s (B2B and consumer) data?
  4. Privacy: Do you have a deep understanding of required privacy regulations governing this data?
  5. Readiness: Is your organization ready to operate the required IT, sales and service infrastructure?
  6. Value Proposition: Do you fully understand how the consumers of your product/service value it in terms of net-new benefit to them to price it accurately?

If you have these covered, you should be in good shape to start a more formal, meaning budgeted evaluation of your go forward. You may have also noticed that I spoke about a “product” in this list. The reason: what you are ultimately providing your customers is precisely that – a new Digital Product.

Yes, data becomes a product.

Companies like Nielsen, Acxiom, D&B, TransUnion, Equifax, Bloomberg and IMS run their business on licensing their data in raw format or as part of an application infrastructure. Your goal should be to become like them.

What will your new digital product do for your clients? It will likely fall into one or more of this six – yes, six again – digitization categories.

  1. Automation
  2. Supply Extension
  3. Distribution
  4. Digital Feature
  5. Repackaging/Customization
  6. Platform

Source: [Informatica] Article: Stephan Zoder
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