Published

3

May

2021

Project Scope

Data Diabetes

Why Organizations Fail to Effectively Metabolize Information Assets, and What to Do About It?

Many organizations collect, curate and process enormous amounts of data. They stockpile this data in data warehouses, data lakes, and other repositories, in the misshaped belief that data, like capital, has value via mere possession. Unfortunately, this simply isn’t the case. Data is only valuable once it’s converted first into information, then into insight, and finally into action. Indeed, until it is “metabolized” in this fashion, data represents nothing but cost and risk.

Data Diabetes

Photo by Lance Asper on Unsplash

Many organizations cannot effectively perform this data metabolism, and hence cannot properly enter the context economy; the world that organizations like Uber, Amazon, Apple and Google both created and now dominate. In effect, these organizations suffer from “Data Diabetes.” They are unable to properly metabolize data, fast enough and effective enough to follow the data-information-insight-action chain. And, until they develop the ability to do so, they will not only not fully monetize their data assets, they will continue to take significant losses from the piles of data that remains untapped. In this working group, LEF seeks to define both the characteristics of this ailment and the most effective treatment(s) to correct it. We are looking for 6-8 client executives to contribute to this discussion. We will look for two, one-hour online discussions to shape this analysis and create the recommended courses of treatment. These discussions will take place during May 2021, with the delivery of the results in June 2021.

What topics will be addressed?

Data diabetes is the term we have coined for the all-too-common situation where organizations possess enormous quantities of data yet are unable to properly leverage that data to improve their operations. Diabetes is a disease in which your blood glucose, or blood sugar, levels are too high. Insulin is a hormone that helps the glucose get into your cells to give them energy. Similarly, many organizations have data, but are unable to properly utilize it, or metabolize it, to energize their business. This research will seek to ask and answer all six of the basic interrogatives: Where and What, Who, When, How and Why as they pertain to this question of “data metabolism.”

WHY be Data-Driven: Information is Not Capital: The Need to Operate Differently

Why is this a relevant discussion and what drives the need for it to be addressed?

  • Capital increases in value over time. Data typically loses value over time.
  • Capital grows in value from mere possession. Data grows in cost and risk from mere possession.
  • Capital rewards inaction, data rewards action.

There is a continuum of data stewardship: Data, Information, Insight, Knowledge, Foresight. Organizations must progress through this continuum to remain relevant.

WHEN: Analytic Foci: Past, Present or Future?

What “when” are you focused upon? Each requires a completely different level of data metabolism to reach and maintain.

  • Rationalize: Focus on explaining the past.
  • Respond: Focus on responding to the here and now.
  • Resolve: Choose to set the course of the future.

WHAT: What are the characteristics of being Data Diabetic?

Recognizing what you are suffering from; too much information, or not enough.

  • Hyposcientia (Too little knowledge): Irritable, Anxious, “Hangry”
  • Hyperscientia (Too much knowledge): Confused, hungry, drowsy, blurred, thirsty
  • Cerritus Narratus (Frenzied Reporting): An over-abundance of reporting and reports
  • Certior Claudico (Halted by Information): Inability to act due to too much information
  • Data Composting: Making ever-deeper piles of data that is not converting into information nor knowledge

WHO: Who is most impacted by this issue, and how do you find them?

Many organizations have hired Chief Data Officers (CDOs) in a tacit, if not explicit, acknowledgement that they are struggling with data issues. Other examples are Chief Analytics Officers (CAOs), Lead Data Architects, Chief Transformation Officers (CTOs) and sometimes Chief Digital Officers (CDOs). What are these people being asked to deal with and work on, and what organizational struggle does their new role reveal?

WHERE: Where in the organization does this problem present itself?

  • Finance, Operations, Logistics, Customer Service, Human Resources, etc.

HOW: Dealing with Data Metabolism challenges

  • Cataloguing existing and potential sources of data throughout the organization
  • Identifying sources of contextual data, and their relationship to current value propositions
  • Identifying potentially new value propositions, if these sources were properly utilized
  • Identifying activities that slow down information metabolism, rather than speed it up
  • Data Triage: Identify data that cannot mature into information, etc., and ruthlessly cull it from the stockpile

Research Interviews & Benefits of Participation

In this project we will interview COO's, CIO's and other IT Executives from large multinational organizations and government bodies. In exchange for their views and insights we will provide early access to our findings and executives will be invited to participate in an exclusive focus group to discuss paths forward. If you would like to participate in this project, please contact svanderburg@dxc.com With these participants we will present and peer review challenges each business has faced in accelerating their data metabolism in order to meet the changing needs of their business. The outcomes of these discussions will evolve the practical roadmap-style guidance for implementing LEF’s frameworks. We will also share interim research assets in formats that each group will decide upon. In addition to peer expertise throughout the working groups, participants will gain early access to the final research report.

If you would like to participate in this project, please contact us.

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