Master Data: The Frontier of Infonomics

Still, the term infonomics does not run unmarked through my English spellchecker. But I think one day it will.

Infonomics BookInfonomics is first and foremost connected to Gartner analyst Doug Laney, who recently told a bit about his upcoming book on the subject in the post Why a Book on Infonomics?

In his preview Doug Laney writes: “Perhaps the book brings about a revolution of sorts, leading to the recognition of information as an accounting asset, and subject to the same legal treatment as other forms of property.

This resonates very well with me, as I think Master Data Management (MDM) is the new bookkeeping. One example of why it should be so, is examined in a nearly 10-year-old post about a financial scandal in Denmark, that would have been avoided if the auditors had spent 10 minutes on the company’s master data. Read more in Master Data Audit.

Master data is only one form of information. However, in my eyes it is the one with the best chance of making sense as an accounting asset.

As business ecosystems and related digital ecosystems are becoming increasingly important in information management I also think that exchange of master data will be worth accounting for as pondered in the post Infonomics and Second Party Data.

2 thoughts on “Master Data: The Frontier of Infonomics

  1. Axel Troike (@AxelTroike) 27th August 2017 / 16:56

    Henrik,

    I agree that Master Data – particularly the domains Party and Product (beside the already traditional balance sheet contributor Asset) – can indicate the potential economic value for an organization. However, I rather like to assign value to their roles (expressed as relationships in the data model). For the domain Party, I consider data describing their role of being Customer or Employee as balance sheet candidates, for the domain Product, data about their role of being part of an Order.

    Your thoughts?

    Rg, Axel

    • Henrik Liliendahl 27th August 2017 / 17:47

      Thanks for adding in Axel. These thoughts apply very well to the realized value of information. When it comes to the potential value of information I believe the value increases with the data quality (or information quality if you like) we can measure on the information we hold or have access to. An example close to me right now is that the infonomic value of product master data is related to the completeness (in conjunction with other data quality dimensions) of the product information we have on the product model. This again is a parameter guiding the information value attached to each physical instance of the product = asset or thing as in Internet of Things.

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