Introduction
In my recent blog series on MDM I brought up the topic of “Data Governance at the Front Line”. It is an important topic for me and with data governance currently high on the agenda, if the recent blogs and media publications are anything to go by, at the risk of a bit of repetition I thought it needed further attention.
Pushing data governance to front line business processes and applications must be the ultimate goal in any Data Quality / Governance initiative. In this post I will detail my thoughts on what it is to have data governance at the front line.
What is Data Governance?
There are a vast number of resources out there that cover this topic. Jim Harris’ OCDQ Blog post regarding Steve Sarsfield’s book ‘The Data Governance Imperative’ provides a great insight into data governance, I really like this definition that Jim extracts from the book:
“Data governance is about changing the hearts and minds of your company to see the value of information quality…data governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise…at the root of the problems with managing your data are data quality problems…data governance guarantees that data can be trusted…putting people in charge of fixing and preventing issues with data…to have fewer negative events as a result of poor data.”
I’ve always seen data governance as the overarching control methodology and processes that encompass the world of data management, in this I include:
- Data Quality
- MDM
- CDI
- Linear Data Processing
- Data Architecture
- Data Modelling
- Meta Data Management
- Data Security
The controls that data governance ensures are an essential part of each of the above domains. Data governance provides the standards, procedures, controls and monitoring principles by which an enterprise governs it’s most important asset, Data!
So what does that mean for the business?
For data governance to be successful you need to align business, process and technology. My MDM series covered these three areas of data governance from an MDM viewpoint, however, the same strategies should be applied to data governance, each aspect needs specific focus, they are not mutually exclusive.
The fundamental approach to successful data management is through understanding our business and process gaps in data governance, and ensuring that we select the appropriate technology.
Driving data governance to front line ensures that we close as many of those gaps in our process and organizational practices (people attitudes and actions) at source, guaranteeing that there is less reactive remedial data cleansing and technology capabilities required at the back end.
Front line data governance reduces the cost of data management, increases efficiency in business processes and improves operational performance and financial accuracy. However I feel that the most important benefit from data governance is an intangible one – the increased user trust in data as an enterprise asset.
What is data governance at the front line?
Front line Data Governance is about driving data ownership back into the business, getting every resource at every data touch-point to ‘own’ the data. Get the people involved!
These resources can be categorized into five types defined across the data life-cycle, viz. Authors, Consumers, Enrichers , Publishers and Custodians. I have been using these definitions for a while and they evolved from an MDM white-paper by Andrew White from Gartner entitled “Governance of Master Data Starts with the Master Data Life Cycle.
The five data governance front line resource categories
You can say that not all resources at these touch-points create data, therefore how can they be involved in the goal of pushing data governance to sharp end of the business?
To answer that question, let’s look at the roles and their activity within the data life-cycle and data governance in more detail.
Authors – As the creators of data, Authors are one of the focus points in data governance. Their role within the data life-cycle is to create new records of source, e.g. new customer records at point of sale, new product definitions and detail or new cost centre creation and definition. These authors are often working within a process in which they feel they do not own the data, they don’t do anything with it post their immediate responsibilities, why would they care if the data is correct or not.
The majority of data quality issues start with Authors. To be successful at front line data governance, it is imperative that you have the buy-in from the Authors, you need them on your side.
Consumers – Consumers use data. Probably the most common component in data delivery. Their role in Data Governance is to have a watching brief. Get the consumers to have ownership in highlighting data issues that have not been captured at source. Therefore ensuring that the issues are not propagated any further.
Enrichers – Users who augment or change data. Data is amended and added to all thorough its life-cycle, data Enrichers (is that a word?) need to be given the same ownership and responsibility as Authors. They need to understand that if they create data issues at their touch-point they can break the data life-cycle chain. Get them on side.
Publishers – People and systems who publish data to the world. A key part in BI, e-commerce and B2B divisions, who’s role it is to publish quality data to Consumers, Enrichers and Authors. Data Publishers need to be perfectionist when it comes to data. They are often seen as the face of data. Ensuring that the data assets that they share with the business and their relevant derivations are accurate, and subscribe to the data governance standards, is an essential part of their role.
Data Custodians – People who ‘look’ after the data. Typically IT people who are responsible for data e.g. DBA’s, Data Architects, Data Stewards and Data Warehouse developers. Traditionally the custodians are the people who clean the data, ensure that it is of quality and that it adheres to all relevant standards. This view of custodians needs to change.
The custodians role is one of stewardship, defining the data governance strategy with the business, managing the deployment and support of that strategy, developing the business data model and supporting the IT architecture within the data governance domain.
Wrapping it all up
I’ve said this before, but it is worth repeating:
By understanding each of the categorized resource types with their relevant data touch-points, and where they sit in your business processes, you can start to build a data governance strategy that empowers your people to own your data.
Data ownership needs to be part of the psyche of every employee, make it part of their incentives, set it as a key KPI in the performance management of the organization. Drive it from every angle, entrench it in the DNA of the organization. Measure it, evangelize it, talk about it in your company report, and make data a unique selling point for your business, the ultimate strategic asset.
Take data governance to the Front Line and reap the benefits today!
Another great post Charles,
I agree with you that “the most important benefit from data governance is an intangible one – the increased user trust in data as an enterprise asset.”
Lack of trust prevents viewing enterprise data as an asset and reinforces the view that each business unit can only rely on its own data silo for daily business operations.
This mindset encourages consumers to author, enrich, and act as custodians of their own private data.
This is why during the planning stages of data governance programs, you will often hear key stakeholders tell you that they are already doing what you describe in this post – and yes, they are – however that’s because they are practicing “Data Silo Governance.”
The key word for viewing data as an enterprise asset is – Enterprise.
Best Regards,
Jim
Jim,
Thanks for providing this additional insight Jim. As always, you are spot, the enterprise view for data governance is imperative to success in any data governance initiative.
There is a continuum story in there somewhere …
Cheers
Charles
Nicely said. It’s true that there are different views of what data governance is, depending upon your perspective and vision. Authors, Consumers, Enrichers, Publishers and Data Custodians all have jobs to do, and as data governance champions, we must help them do it.
Thanks for your comments Steve, apologies for my late reply.
I agree, our role as change managers in data governance is an every present responsibility, one that I relish with passion though …
PS: Your book goes a long way in helping me do this!
Charles,
I’m a big believer in getting more folks actively involved in the data governance process. I wrote about it a few months ago:
http://www.itbusinessedge.com/cm/blogs/all/giving-everyone-a-stake-in-data-integrity/?cs=35678
Your explanations of the five roles gives added dimension to the idea. Do you think ‘carrots’ are more effective than ’sticks’ in getting folks to take data quality more seriously?
Ann
Hi Ann,
Thanks for your comment. I am a big fan of the ‘carrots’ approach, however, these should be set as enterprise KPI’s cascaded down to divisions and individuals as both KPI’s and roll responsibilities, your therefore end up with both the carrot and the stick, if the resources adhere to their responsibilities they get awarded for the scale of the achievement, if not and they ignore their responsibilities they get the stick (with support …). It’s kind of a meritocratic approach.
Cheers
Charles