doug laney customer accelerator podcast

Podcast: Customer Data as an Asset With Doug Laney

Caserta Principal of Data and Analytics Strategy, Doug Laney, appeared on The Customer Equity Accelerator podcast with Allison Hartsoe. Listen below to hear his thoughts on data strategy, data governance, and treating information as an asset.

View the full transcript of the podcast >

When 9/11 happened it kicked off an unexpected crisis as companies who lost all their data discovered that insurance firms believed it had no value. Although data meets the definition of an asset on many levels, traditional accounting and insurance firms do not see it this way. What can a corporation do to recognize and protect this truly valuable asset? Doug Laney has the answers.

Listen to the podcast:

Highlights from the podcast:

On treating (and defining) information as an asset:

“It’s imperative today for organizations to manage their information as an actual asset to treat it as an actual asset. The components of infonomics are really the three main aspects to it. One is to measure your information assets. The second is to manage them, and the third is to monetize them.”

“There are a lot of people who talk about data as the new oil, and while that certainly represents that the recognized data has value and importance, it misses the point that data has these unique characteristics. You can only consume a drop of oil once and then it’s gone, right? You can use data over and over again, and you can use it simultaneously for multiple purposes. It’s what economists would call a non-rivalrous non-depleting asset. I think it’s important to be able to consider the variety of ways to use information simultaneously for different business purposes and to use that same data again and again to drive business value.”

On data governance:

“Data governance is very important, especially with customer data. With all the regulations out there now, companies really need to be circumspect and buttoned-up when it comes to understanding all of the regulatory issues, whether they are national issues, international compliance issues like GDPR or industry-specific issues. The mistake companies make with data governance is they start with policies? And all these compliance regulations kind of compel you to do so.

I think it’s really important to think about the principles. What is the vision for data in the organization and what are the principles for the way that you’re going to collect and use and manage and store and share information? And to develop those principles in concert with not only your chief privacy officer and your chief information security officer but also the business because it is a bit of a push and pull and once you have those principles established. Then you’re in a position to establish guidelines and policies from that.”

On data strategy:

“The opportunities for leveraging data broadly within the organization and sometimes even externally, although there are of course are restrictions with customer data, and organizations shouldn’t get pigeonholed into just thinking about using data a single way and then reporting on it. There’s a lot more you can do with it.”

“There’s incredible value in external data assets. There are 10 million data sets published by government organizations worldwide open data. There are at least 5,000 data brokers out there selling data. There are a trillion websites with data that can be harvested. There’s data you can gather from partners, from suppliers, from customers.”

“I think there’s a step before that in understanding what data you have, creating an inventory directory, a metadata directory or a data catalog of your data. And that’s part of a data governance process. So I would start with that with understanding what you have before trying to architect an integrated data solution, and whether it’s a data lake or a data warehouse in series of data marts or a more of a hybrid, we call a logical data warehouse or a virtual data warehouse where data is virtually integrated. There’s a variety of architectural considerations that will be dependent upon what data you have, where it is, and what your vision for monetizing it or generating economic benefits from it is.”

View the full transcript of the podcast >