Exploding the Myth of “Data is an Asset”
by Patrick Dewald, Diaku
“Data is an Asset” is one of those terms that frequently gets bandied around within management circles but is there a reality gap between intent and execution?
In this guest post from expert panellist and director of Diaku, Patrick Dewald, we get an insiders view on some of the myths and paradoxes of data strategy. Patrick also shares insights on where organisations possibly need to refocus their efforts.
NEWS: Patrick Dewald presents Diaku Axon, their flagship Data Governance software solution via webinar on 17th July 2013 – find out more…
Rise of the Chief Data Officer
The modern firm relies heavily on data. It provides insight into business performance as well as strategic direction. If utilised properly it plays an integral role in running the firm.
Many large scale firms have recognised the strategic importance of data and have created an executive position of Chief Data Officer, dedicated to overseeing and developing what has become known as the ‘Data Asset’.
The Knowledge Management Paradox
Despite this investment, is data really treated as an asset?
All large firms hold comprehensive registers of other more tangible assets such as human capital, financial resources and facilities etc.
If data is indeed considered a strategic asset to a firm, one would expect there to at least be a register of what data is held and where, for which purpose and who is involved.
Both data and data knowledge are valuable assets in themselves and need to be managed accordingly.
After all Knowledge Management has been an established practice for many years now, so why is knowledge management about data not an active focus of the enterprise data management professionals?
How Effective is Your Corporate Memory for Data?
It is assumed by many that data is a billion dollar asset for most global firms, yet collective understanding of that asset is partial at best. It is also not readily available in language used outside data-specific teams. In most large firms collating existing understanding of a given data type occurs in an ad hoc manner, requiring a mad scramble of people quizzing one another. The data is all there, but where is the corporate memory when it comes to locating and using it?
Such a question may sound brash. After all, technology and information experts are working hard at building their understanding of the data landscape. They have system, server, interface & architecture diagrams, data models and dictionaries.
So what other understanding is required? What is lacking?
Data-Centricity – Business Context Required
The existing technical and data-centric views lack the business context in which the data operates. What is the data used for?
Firms must be able to answer the most pertinent questions one has of any corporate asset: is the asset fit for purpose and is it compatible with the firm’s overarching strategic objectives?
Wherever a firm’s business functions rely on data, it is crucial to know whether or not the data concerned is:
Performing as a trusted asset
Containing relevant information and
Delivering great value
Given the reliance on data in the modern firm, not being able to assess whether or not the asset meets current and future business requirements is a major shortcoming. Ten years ago applying roles and responsibilities to data was a revelation to most and the start of data governance as we now know it. However little focus was given to there being a shared understanding of what was being governed.
Part of the problem is that discussions around data are not currently being conducted in business terms. This prevents the business community from taking an active role in ensuring its business requirements are being met.
Data and the broad business context in which it operates needs to be captured and managed as a core body of knowledge in a way that is accessible and understandable to a business audience.
A deliberate and active management of data knowledge by and for the business is imperative in order for the modern firm to manage the data asset in line with business needs and priorities. This approach will help bring data governance out of the committee dark rooms and into the workplace.
We strongly believe it will prove to be the next evolution in enterprise data management.
If you are responsible for maturing the governance, quality or compliance of your data here are some important questions to ask within your organisation to help you gauge potential areas for improvement:
Does a data register exist and how widely is it used?
Is there a go-to point to find out about data sourcing, usage, quality etc.?
Does every project start from scratch in clarifying and confirming its data requirements and the as-is data landscape?
Does the business have an integrated view on its critical data elements and where these are used?
- Who is tracking the level of data duplication and fragmentation across the firm?
Image rights: CC – Flickr RLJ Photography NYC
Patrick Dewald is a Data Governance Architect and founding partner in Diaku.
Patrick has a wealth of experience designing Master Data Management and Data Governance solutions for financial institutions.
He has been heading up Data Governance initiatives, designing and implementing group-wide data services from the ground up for the best part of 15 years.
Patrick is recognised by his peers as a thought leader in the field of data governance.