How To Measure, Manage, and Monetize Information As An Asset

Data Transformers Podcast
How To Measure, Manage, and Monetize Information As An Asset
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Episode Title : How To Measure, Manage, and Monetize Information As An Asset

Episode Summary: It has become a cliche to say data is an asset. If an organization is not making an attempt to measure, manage, and monetize, information can’t be an asset. Doug Laney is one of the foremost thought leaders who has been espousing Infonomics and the need for organizations to monetize their data. Doug was also the leader who came up with 3 Vs to describe Big Data and the one who came up with 4 types of analytics namely Descriptive, Diagnostic, Predictive, and Prescriptive. Doug’s assertion is that leading organizations focus on reaping the benefits by implementing the last 3 types of analytics. To enable any type of analytics though, leaders in organizations have to ensure that data literacy and data culture are pervasive.

Topics discussed in this episode:

01:30: Origin of Infonomics. Coincided with the 2001 terror attack and how companies lost their data.

03:00: Insurance companies excluded data and accounting bodies didn’t allow data to be recorded as an asset.

05:00: Monetize, Managing, Measuring the data. Reason for re-ordering the book to start with Monetizing as an inspiration.

06:00: You can’t manage anything that you can’t measure. So organizations should start with measuring their data.

08:00: Monetization has been the big impact of the book. There has been concerted efforts by companies and government

09:00: Usually CDOs responsibility is to manage

10:30: Data initiatives failures. Probably not measuring the value of the project. If analytics are not being used, it is considered a failure

11:00: Data literacy and data culture are also key. Data science and analytics projects are research projects and often fail.

13:30: Relevance of 3Vs today.

15:45: Self-organizing data. Application of AI and ML to facilitate self-organizing data.

17:30: How organizations could move up higher levels of analytics.

18:00 to 19:55 (Headliner)  500+ ways organizations are high value; 95% of high-value analytics are diagnostic, predictive and prescriptive types of analytics.

20:15 : Looking at data holistically. Advocating separating managing data analytics from data itself.

Resources mentioned in this episode:

Podcast website: https://DataTransformersPodcast.Com

Data Transformers Podcast

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