Data Governance Interview - Thijs van der Feltz

Thijs van der Feltz, MBA, is an enterprise data management specialist and information architect and has been devoted to data management for over 30 years. He has hands-on experience in numerous facets of this field. With a long history in financial services, he is currently in the middle of implementing data governance at an insurance company in the Netherlands. He is one of the founding members of the recently established DAMA-Netherlands chapter.

How long have you been working in Data Governance?

If we define it loosely, I started doing Data Governance about 30 years ago, long before that name emerged. It was called data administration then and was taken very seriously at the company I worked for. Things were different at that time, of course. With the mainframe being king of the jungle, there was already some serious governance going on, except that IT was in charge instead of the business. Over the years the business gained more control of IT, and rightly so, but governance has lagged behind. The king is practically gone and what we have left is a rapidly expanding jungle of disparate data that is cultivated by innovation and savvy users. Hence the need for data governance is now greater than ever.

How did you start working in Data Governance?

In the 1980s I worked for a consultancy firm that specialised in information strategy, databases and data modelling. After 5 years, I joined a merchant bank to set up their data administration. In time, this field of work evolved into data governance, data architecture/modelling and metadata management, which I have all embraced during my career. In fact, in a recent article Robert Seiner suggests that data modelling is data governance; not literally of course, but in terms of discipline, rigor and effect, the analogy is a good one.

What were your initial thoughts when you first fully understood what you had got into?

When this ‘new’ field called data governance emerged, it did not come as a surprise to me because I had already been doing data governance stuff for years. It added some missing parts to data management as we knew it, and it had a nice ring to it that appealed to business people.

Data management and data governance are intrinsically connected, but are also distinctly different. One can argue that we have a chicken-and-egg discussion as to ‘who is on top’ but ultimately, data management is the task that needs to be done. Data governance is needed to make sure that this is properly embedded in terms of roles and responsibilities. Semantically, the term data governance is sort of a misnomer, because we cannot govern data (the inanimate ‘thing’) itself. But hey, what’s in a name; if it works, don’t fix it. What can and must be governed, however, is the behaviour of people, and data management processes. That’s what data governance is about.

Are there any particular resources that you found useful support when you were starting out?

There were very few resources back then, but I found several books that were particularly influential and supportive to my efforts: “Data administration” (William Durell, 1985), “Fourth Generation Data” (Dan Tasker, 1989) and “Case*Method – Entity Relationship Modelling” (Richard Barker, 1990).

At that time, I was consultant with a company that was a pioneer in data centric solutions, with data management as a core competence. I had the good fortune of having access to a wealth of expertise provided by all my colleagues.

What characteristics do you have that make you successful at Data Governance and why?

Data governance is a complex field, so my multi-disciplinary educational background (engineering, economics, MBA), which spans the business-IT gap, has given me an advantage in comprehending the big picture.

What also helps is that I’m passionate about data and relentless in seeking answers and finding ways to convince people of the importance of data governance. I have experienced first hand the advantages of mature data management and understand the root causes of data quality issues. I am very critical about superficial approaches to fixing data quality, which is not always appreciated by some of the people I work with. Diplomatic skills should not be underestimated when trying to achieve data governance success.

What is the biggest Data Governance challenge you have faced so far?

One challenge is the knowledge gap between the business and IT. While the business clearly wants high quality information and more and more uses for it, they generally don’t want to be bothered with the details of achieving data quality. They just want to plug their (information) appliance into an outlet in the wall, but don’t care what’s behind that wall. This leads to another challenge: obtaining management buy-in.

In the other corner is an IT organisation that is primarily focussed on technology and not so much on informational aspects such as semantics, purpose, and taxonomy. The result of this polarisation is often poorly defined business and data requirements. This is a root cause of cost overruns and mutual frustration between business and IT. Data governance plays an important role in bridging this gap, by ensuring that the business takes control and responsibility of its own data. Data governance sets the rules and policies, while IT is responsible for the data management execution that correctly implements them in a way that is transparent and verifiable by the business.

Data belongs to everyone, but nobody wants to own it. Business engagement, responsibility and accountability are key, but that is much easier said than done. Strong leadership and executive sponsorship are prerequisites but actually getting an organisation to embrace a ‘data as an asset’ culture is the ultimate challenge and very hard work.

What have you implemented or solved so far that you are particularly proud of?

Having designed and built a custom built enterprise metadata repository system for data modelling at the previously mentioned merchant bank has given me great satisfaction and pride. While there are many good tools on the market, none offered a complete solution that we were looking for, so rather than trying to synchronise multiple overlapping tools, we decided to build an integrated solution ourselves. It was used from 1990 to 2010 to serve the needs of hundreds of application developers and database designers and it was our metadata integration hub. We incrementally developed an enterprise data model (ca. 4000 entities) that was mapped to our relational databases across some 250 systems. The data modelling process was incorporated in the application development life cycle, and certified data models helped to create accurate business requirements. The system provided us with considerable control of our (master) data, as well as reliable impact analysis that enabled exceptional agility. Eventually this system faded into obscurity, after a takeover that resulted in our systems succumbing to the new organisation. Nonetheless, it has been very inspirational to have worked in such a mature data management environment, with highly capable team members and supportive management. It has opened my eyes to the potential of data management done right.

I am also proud of my recent progress in establishing and promoting a corporate business glossary. A seemingly simple list of words and definitions can be an endless source of discussion, so it’s important to be firm at times and to keep moving. Two factors have proven to be successful: (1) a comprehensive set of guidelines & standards to improve the quality and overall consistency and (2) embedding the glossary in existing policies and procedures, to encourage its use, to enforce consistent use of terminology, and to leverage reusability by averting the need to redefine terms in multiple documents.

What single piece of advice would you give someone just starting out in Data Governance?

Get involved in teams of like-minded and experienced people and start doing it. There is no shortage of good books and blogs in the internet to help learn the trade, but compare sources to separate truth from fantasy and hypes. Some of my favourite sources of knowledge are the TDAN, B-Eye-Network and DataVersity. Also, the recent Data Governance books by John Ladley and Robert Seiner are very good. To get a broader overview, become familiar with some general management and quality assurance books such as those by W. Edwards Deming, Peter Drucker and Danette McGilvray.

Data governance is business responsibility, but it is important to realise that the success of data governance strongly depends on the maturity of the data management function. To this effect and in the spirit of the old adage “you can’t manage what you can’t measure (or define)” I would to add “you can’t govern what you can’t manage”. One should therefore understand the essentials of data management and business-IT interaction. Data governance is a multi-disciplinary function and requires a certain level of seniority to get things done, so prior experience in different data-related fields is highly recommended before seriously getting involved in data governance.

The rewards of data governance success are considerable, but passion, patience and perseverance are indispensable while pursuing this goal.

Finally, what do you wish you had known or done differently when you were just starting out in Data Governance?

For a long time, I believed that it was sufficient to enforce a solid data management discipline using advanced tooling for data modelling and metadata management. This idea was further reinforced by, as mentioned earlier, positive experiences with a mature data management environment. In recent years, it has become very obvious to me that the biggest challenge is people, culture and change. No surprise here, just confirming the findings of Nicola’s previous interviews. While I have no regrets about my career path, I do wish I had become aware of this earlier, to have gained more experience in tackling the ‘sociological’ aspects of data governance.

I wondered if you could share a memorable data governance experience?

During my years at the bank, we were involved in several successive mergers and acquisitions. Part of the process was systems integration. During these sessions, our new colleagues were surprised that we had only a single customer database, while to us, this seemed like such an obvious design choice.  To make a long story short, our IT system was chosen several times to be the leading environment for the new organisation. In time, I also witnessed that such decisions are more often politically motivated, with data being of lesser concern.  Could this be a reason why the anticipated benefits of mergers often fall short of expectations?

What are your final thoughts?

I would like to thank you, Nicola, for giving me the opportunity to share my views and join the ranks of data governance experts that you have interviewed over the years. Their views and public contributions have been a valuable source of knowledge and inspiration for me in my daily work.

Having read my interview with Thijs you can also read my free report which reveals why companies struggle to successfully implement data governance.  

Discover how to quickly get you data governance initiative on track by downloading this free report

Data Governance Interview - Sue Geuens

The lastest Data Governance Interview is with Sue Geuens.  Many of you will know Sue through the tremendous amount of work she puts in as the current President of DAMA International.  I am so pleased that she found time in her hectic schedule to answer some questions and shared some valuable insights into her views on Data Governance.

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How long have you been working in Data Governance?

Officially for about 18 years, but I think effectively and sub-consciously most of my business life!

Some people view Data Governance as an unusual career choice, would you mind sharing how you got into this area of work?

This is a really funny story. I started work at the National Home Builders Registration Council here in SA on 7th February 1996. My boss handed me a disk with a list of registered builders and told me this was now my responsibility. I had a look and told him I needed a database to do this. He gave me his credit card to go and buy one. I chose MS Access since it was the only one I knew and then went on to copy the list and paste into Access – creating a table with the paste. I then spent about 3 weeks typing into this table – directly in Access before it occurred to me that there were patterns to the data and that there had to be a better way. The rest, so they say is history!

What characteristics do you have that make you successful at Data Governance and why?

I believe that a strong knowledge of business in general is very important. I have been in a number of jobs since I started work at 19 and in each instance left the job knowing much more than when I started. It has given me a very good enterprise view. Funnily enough, I think my ability to see the patterns and flow in data is also a good characteristic to have – allows me to think out the box – and that is a complete necessity when “doing” Data Governance. Finally, I get along with people and can be quite objective – surprising my friends will tell you as they all think I am quite scary and stand offish, but DG is all about people, isn’t it?

Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?

I was very lucky in that I got involved with DAMA in 2006 and ended up having many contacts who are considered as Data Governance gurus. I tap their knowledge and expertise when needed. I do have a few favourite books though although they are not specifically DG based. Danette’s book on DQ and Graeme’s books on data modelling – both personally signed and well used. And of course, I do have the DMBOK. Before that I was pretty much seat of the pants and I am surprised at how well I managed!

What is the biggest challenge you have ever faced in a Data Governance implementation?

Holding my tongue! I am quite strong and sometimes it drives me nuts when I see something happening that is just wrong – but I have learnt that I have to let the client make the decisions, even when I know it is not right – my job is to guide and advise.

Is there a company or industry you would particularly like to help implement Data Governance for and why?

I do a lot of work in the very big companies, but I do feel the smaller organisations are just as needy for DG. I would love to be able to create a DG implementation program for small companies – that wouldn’t cost the traditional arm and a leg and that doesn’t need a huge team (internal and external) to implement

What single piece of advice would you give someone just starting out in Data Governance?

Patience, patience, patience. Is that a single piece? DG is slow, its frustrating and its likely to fail at least once – so being patient and getting back up each time you stumble is the only way to go!

Finally I wondered if you could share a memorable data governance experience?

I have so many stories it’s hard to decide on one only. However the one that I think is the most impactful is this. At one of my clients, there were a number of very difficult personalities on the DG Council. This made our meetings fraught with interesting possibilities. One of the meetings was particularly difficult and there was a real battle going on between two of the attendees and it got really personal from one side. Which was not acceptable or productive. I was struggling to stop this from happening since I was chairing the meeting - face to face and via video conferencing. Suddenly the person who was being really abusive stopped in the middle of a sentence, jumped about a foot out of his chair and then just sat there completely quiet. The rest of the group looked on puzzled, but he stopped dead – so we eventually gather ourselves and carried on. I found out just after the meeting that my boss at the time, who was sitting next to the abuser had actually kicked him under the table – HARD. Talk about Data Governance being a contact sport!

If you want more advice on data governance My free report reveals why companies struggle to successfully implement data governance. Discover how to quickly get you data governance initiative on track by downloading this free report

Data Governance Interview – John Ladley

I was lucky enough to have the opportunity to interview John over breakfast when he was in London in May.  It's taken a while to get the interview transcribed, edited and published but I hope you'll agree that's it was worth the wait!

How long have you been working in data governance?

If you define data governance as the rules of engagement, simply I’ve been doing it for at least 20 years.

We used to call it “enforcing standards”. The most common question I got at conferences in the 1980s was, “How do you enforce standards for development or for manipulation of data?” and the answer then was creative process of people knowing the rules and understanding the rules and adhering to the rules and then have someone with a large stick walk around, making sure they’re enforced. Back in those days, we were not very sensitive to personal human capital issues. So some people view data governance as an unusual choice of a career.

Would you mind sharing how you got into that area?

Just for the money. It’s just for the money :-).  But seriously, If you read my books, there has to be a control side to managing the information asset. There has to be data governance. So it can’t be something that you choose instead of data management or you don’t choose data management instead of governance. You embrace both or you embrace none.

What characteristics or traits do you think you have that make you so successful at data governance?

I’m practical. We all have our success factors. We have our methods for doing artifacts that. But an organisation in the throes of a bitterly competitive market or brand new crushing regulations has a lot more problems than just data. So you have to make sure that what you do enhances their ability to thrive in whatever marketplace they’re in, whether it’s government or business or anything. That’s the key.

There not many books on data governance in the market and I always recommend to my clients that they read yours because I think that’s really comprehensive. But are there any other particular books or resources that you recommend reading if you are trying to learn about data governance?

Yes, and they don’t have anything to do with data governance. But I recommend people read any basic good book on financial accounting. Now a lot of us had accounting basics in our college level education. But if you didn’t, I would go back to that and understand about auditing and accounting principles because that transfers directly to data governance. It is a one-for-one conceptual transfer. 

Or try reading a book on any other type of governance, such as corporate governance, I really do burst bubbles of our peers and our industry sometimes but we are not the inventors of governance. We do not have a monopoly on governance and we’re actually latecomers and we actually look pretty silly when we realise that the data and information field is only just now talking about this.  Any books by Dr Edwards Deming will be useful as well. .

What has been your biggest challenge in data governance so far?

I think others have said this too, it’s the culture. It’s always the culture. Data people as a rule tend to promote what we do as a wonderful attractive abstraction but data people make up, in terms of the way our brains work, only 20 percent of the population. The other 80 percent, want to be told why they should be doing it, . “What’s in it for me?” then be told exactly what to do to pull it off.

We (information management people)  are terrible at that type of engagement with other people. So it’s the culture. It’s making sure that the organisation understands that there’s value to be gained, that there’s a compelling reason. I don’t know if there’s another question along this line coming up. But data governance is becoming in my eyes as transformational for most organisations business reengineering or a merger and an acquisition or Sarbanes-Oxley. It requires a good depth of attention to the organisation.

Are there any industries left that you haven’t worked in that you would like to do data governance for?

Well, that is a good question. What I find, the type of governance we do which is very much based on business alignment and supportive of business strategy;  as reflected in my earlier answer about being practical within their environment. We do an awful lot of reverse engineering of business strategies. We get many, many clients where I ask, “Well, tell me your business strategy,” and you get this image of Mr. Bean rummaging around the office and lifting up plants and such to find this mysterious document.

So we’ve ended up doing a lot of those. What I would really love to do is participate in the actual business strategy itself, to not react to what the strategy is, but how to drive the strategy with an information viewpoint. A lot of organisations are looking at how you can monetise their data. How can we get more revenues from the amount of our data? It’s in all industries. That would be very, very much fun to be part of that.

If there was just one piece of advice you could give somebody just starting out in data governance, what would it be?

I would ask them "why?". I know that sounds glib and you’re laughing but I would ask them why. Why do they think it’s important? And if they say, “Well, I’m in it for the money,” I would say learn something from it, but don’t plan on doing it forever. I would say being passionate about it is key. The second thing I have to say, you have to be resilient.

My free report reveals why companies struggle to successfully implement data governance. Discover how to quickly get you data governance initiative on track by downloading this free report

Make Sure you Follow These Practical Steps for Creating a Business Glossary

I’ve recently launched a new course: An Introduction to Data Governance Using Collibra and in order to ensure that attendees on this course have access to the best combination of both business (my focus) and technical skills, I have teamed up with a leading Collibra expert and Implementation Partner Carl White. As you know I like to use this blog to share practical advice to help you with your Data Governance initiatives and I thought that this new collaboration gave me an opportunity to ask Carl for his views on the best way to approach a typical activity for organisations embracing data governance - creating a Business Glossary.

Firstly, what is a business glossary?

In a nutshell, it’s the place where important business terms are clearly owned, articulated, contextualised and linked to other information assets (e.g. reports).  For example you will have a list of terms, what that means in business terms, who owns that data and then information such as which systems and processes it is used in.

A Business Glossary seems a fairly straightforward deliverable, surely it’s very easy to create one?

It seems straightforward but there will inevitably be many stakeholders, all of whom differ in their understanding, expectations, requirements and commitment. Enthusiastic stakeholders will expect the Business Glossary to store everything and solve all problems related to business semantics. Uncommitted stakeholders might see it as a valueless exercise. If it is not carefully positioned, the glossary can quickly become an unstructured dumping ground, ironically reflecting the reason the organisation needed one in the first place.

So what do you recommend that anyone creating a Business Glossary does first?

It’s critical to identify a focus area within the organisation where sponsorship is strong but a lack of clarity has caused problems. Canny sponsors will usually be aware of a particular domain or business area where terms are problematic, for instance, a certain set of management reports where Finance and Sales teams don’t even realise they define terms differently.

Once you have agreed a focus for your pilot what should you do next?

Starting with the sponsor, engage key stakeholders within the focus area to define a limited scope with clear and measurable outcomes that all stakeholders see as valuable to them.

Who do you consider ‘key stakeholder’ do you mean the really senior people in that area or the more junior people that really do the work?

Both senior and junior people have a part to play. Senior people will be accountable for terms and will want to review and approve definitions. Junior people will tend be more involved on a day to day basis so they often know more about the issues. There’s a collaboration to set up through the glossary in which the junior people begin articulating terms and the senior people review and approve. The collaboration is as important as the final definitions, in my opinion, as it leads onto generally better practice like clear accountability with data.

Once you have your area for your pilot identified and stakeholders engaged, what’s next?

Collect a small volume of the most problematic terms, perhaps in an Excel workbook. Identify stakeholders who are willing to act as owners of the term and others who are willing to articulate the term. Encourage stakeholders to be rigorous with their definitions and the information they keep on the terms. I’ve seen so many definitions along the lines of Customer Type - the type of customer’ but this tells me nothing about the possible values, who uses the term, why it matters, who wrote the definition, who approved the definition, when it might no longer apply and so on.

And once you’ve got them working, you move onto another area? 

Not quite, creating data glossaries is very much an iterative process. Once your stakeholders become involved they are likely to think of more information that they would like to add to the glossary. So after the pilot stage it is important that you review the pilot to determine whether all the required information has been collected whether changes are required before rolling the process out across the rest of your organisation.

And can all of this can be done in Microsoft Excel?

You can get a fair way along the journey with Microsoft Excel but the collaboration we talked about earlier includes an element of workflow, terms need to be very easily accessible to all users and changes to the glossary need to be tracked and understood. However, an organisation can start the process using Excel in order to begin their journey and really understand what they need. I would recommend starting small to understand the benefits. Once these are clear and there’s a head of steam, I’d strongly recommend making an investment in a tool.

I hope you have found this advice from Carl useful, if you want to learn where a Business Glossary fits in a data governance framework and even have an attempt at creating your own one in Collibra, why not come along and join us both on An Introduction to Data Governance Using Collibra on 7 September in Central London.

My free report reveals why companies struggle to successfully implement data governance. Discover how to quickly get you data governance initiative on track by downloading this free report

Data Governance Interview - Michael Nicosia

This Data Governance interview is with Michael Nicosia who I met at DGIQ this year in San Diego.  His presentation was full both of humour and also his enthusiasm for Data Governance, so I knew that I had to ask him to do an interview and share that enthusiasm with you all...

Mr. Nicosia joined TIAA-CREF in November 2004 and is currently responsible for developing and deploying business-led data and process governance practices and capabilities, as well as leading the development of Finance & Actuarial (F&A) multi-dimensional, multi-year vision, strategy, and roadmap.  He is also an active member of the company’s Enterprise Data Governance council.   

Prior to joining TIAA-CREF, Mr. Nicosia worked as a Managing Consultant for The Amherst Group Limited, a consulting firm that provides advisory services to Shared Services organizations around the world.  During this time, he provided strategic advice and counsel to Fortune 100 companies on organizational design, implementation of shared services management practices, and the re-design of standard service delivery processes across multiple functional areas and industries.

How long have you been working in Data Governance?

In late 2010, I assumed the responsibility for defining and implementing sustainable governance practices within F&A and building a permanent data governance function that will provide on-going advice, counsel and support for data governance initiatives

How did you start working in Data Governance?

Now that is an interesting story.  When I joined F&A in 2007, I was part of a new Finance Transformation Team that was responsible for changing the way F&A operates (i.e. process improvements, organization re-design, etc.).  As part of this initial role, I was selected to lead a very large multi-year transformation program that was focused on strengthening and automating our critical F&A business processes, improving our overall data quality, re-designing our data integration, implementing new analytical tools and solidifying the underlying infrastructure.  This program opened my eyes to the importance of data within an organization as well as the importance of having both efficient processes and high-quality data. 

Towards the end of the transformation program, Our Corporate IT area launched a data transformation program that included a work stream focused on establishing Enterprise Data Governance.  I was asked to attend a governance meeting in place of my boss – it was this meeting that I really started working in the Data Governance space – that was the summer of 2010.  However, to be honest, at that time establishing a data governance function within F&A was not even remotely on my radar.  It was not until I was approach by my boss and no less than four other people (business and IT) about a new role around data governance that we were creating in F&A – I turned it down initially, because I did not see myself doing this type of work.  As the months went by, I did a little research and analysis of the opportunity and found that very few companies were approaching data governance from a purely “business perspective” – so I could be on the leading edge.  Based on this and other factors, I accepted the roll and have never looked back.

What where your initial thoughts when you first fully understood what you had got into?

Honestly?  My first real exposure was attending the IBM Information on Demand conference in October of 2010.  My take away from that conference (as well as prior research) was that “this was not rocket science” and that I could definitely take my prior experience and acumen and apply it in this space.

Are there any particular resources that you found useful support when you were starting out?

I would like to think that I was really smart in this space, but the reality was that I had zero direct experience – what I had was very relatable experience.  However, I was smart enough to know what I did not know, so I hired an external advisor to help educate and coach me through the initial planning.  I did not go the route of big consulting firm, multiple resources because I felt that was not necessary.  This advisor was with me for about 3-months at the start back in early 2011and as he would tell you – he started out as an advisor and we migrated very quickly to more collaboration as I was able to bring my prior consulting experience to bear in thinking through the strategy, approach and plan.

What is the biggest Data Governance challenge you have faced so far?

Adoption of good data governance practices!  As most of the companies that I have come into contact with over the last several years will attest.  The hardest part is getting staff to see the value in managing their data and making that structured management part of their normal operations.  We have addressed this in a number of different ways, most importantly is our focused approach on change management.  The reality is, that the level of success an organization achieves with their Data Governance efforts will be in direct proportion to the amount of effort they put forth on building awareness, educating and training staff.  I think that if you polled other data governance practitioners, you would find that they all would agree that change in any form, is the hardest thing for an organization and individual to accept! 

Whether it is changing jobs, homes, applications, processes, staff, etc., each change comes with a unique set of challenges – and stakeholders, and most people if given a choice would not change – why? Because we are “creatures of habit” and prefer routine and repetition – and change is HARD!  So, based on my experience focusing on Change Management as part of your governance initiative could be the difference between achieving “just compliance” or “full adoption” of good governance practices.

What have you implemented or solved so far that you are particularly proud of?

I would say that I am most proud of a couple of things.  The first is building a sustainable data governance function within F&A.  The second would be the level of engagement and awareness we have built over the last few years.

 My team and I have worked hard over to broaden the understanding of data governance and implement standard governance practices across our most critical data assets.  While we are far from done in this effort, we have been able to cover off some important areas within F&A – such as investment accounting, treasury and accounts payable.  The holistic approach we have taken - addressing multiple governance components from Meta data to data quality to business architecture to change management – has enabled us to bring broad awareness of why data governance is important and has resulted in a high-level of engagement across different levels F&A staff.  For example, the attendance rate for our Stewardship Committee meetings has averaged north of 70% over the last three plus years – and we have seen roughly a 30-point increase in overall data governance awareness during this time as well.

How has changing roles impacted your ability to improve Data Governance within Finance & Actuarial?

From the start, we have taken a “plug-n-play” approach to data governance that allows us to shift focus and change our approach based on changes to roles, organizational structures, etc.  We spend dedicated time each fall reviewing and refreshing our data governance goals, strategies and measures to ensure that they are aligned with where F&A is heading in the coming years.  And, periodically throughout the year we make minor “course corrections” to address changes in data domains, Stewardship, methodology and priorities.  So, we are constantly re-evaluating the effectiveness of our data governance efforts so as to minimize the impacts of broader changes.   

What single piece of advice would you give someone just starting out in Data Governance?

The most important piece of advice I would give to anyone just starting out is spend a good amount of time thinking and planning how best to roll-out data governance within your organization. 

The reality is that we (practioners) tend to over-complicate the roll out of data governance by trying to “eat the elephant” all at once or, worse, we focus too much time and effort at the start on tactical solutions so we can show some “quick wins”.  But we tend forget that doing the simple things first like figuring out where you are going before you start your journey (have a plan) and will tend to yield the best results. 

President Dwight Eisenhower was often quoted as saying “Plans are worthless, but planning is everything.”  If you think about it, there is definitely some truth to this quote, but what he is really saying is that the process of planning is the single most important action you can take to set a strong foundation for success.

Why you are going there [your goal/destination] is more a function of how you want to operate in the future than any single problem you are trying to solve. It’s all about having a clear view of how you will operate and what your teams will need from the start.

Finally, what do you wish you had known or done differently when you were just starting out in Data Governance?

At this stage in our data governance journey there is one particular thing that looking back, we should have done sooner – that is to develop a formal, cohesive data strategy.

Over the last 3-4 years we have been executing against a clear data governance vision and, as it turns out, all the right components (i.e. data governance, data management, data architecture, etc.) we would have include in a data strategy had we formalized this at the beginning of our journey.  A cohesive data strategy provides a foundation that you can use to “rally” your organization into action.  And if complete can provide a clear vision and pathway to what we see as the ultimate goal of all your efforts – adoption of good data governance and data management practices across the organization.

Michael Nicosia is the VP of Strategy & Data Governance at TIAA-CREF, a national financial services organization with over $860 billion in assets under management (as of 3/31/2015) and the leading provider of retirement services in the academic, research, medical and cultural fields.  He has been guiding the Finance & Actuarial area of TIAA-CREF on its data governance journey since 2010-2011. The views expressed herein are solely those of the author and do not necessarily reflect the views of TIAA-CREF.

My free report reveals why companies struggle to successfully implement data governance. Discover how to quickly get you data governance initiative on track by downloading this free report

Data Governance Interview - Andrew Davies

This data governance interview is with Andrew Davies, who I came across online as he enthusiastically contributes to online data related discussions. Andrew has been in the IT industry for 21 years coming from the background of a degree in applied mathematics. He started out his IT career as a database developer and having gained a good grounding in software development he went on to look at the more theoretical aspects of databases, starting with E.F. Codd’s seminal paper on The Relational Model of Data.  He firmly believe that if you don’t know the principles on which a discipline is based you can’t know how far those principles can be safely bent or when they can be broken.  After several years as a relational database designer he moved into data architecture and have recently moved into his current Information Architecture Management role in the Enterprise Architecture team for the BAE Systems Naval Ships business.

How long have you been working in Data Governance?

Data Governance has been a part of my role for about 12 years.  As the senior database designer in a software house where the product was data-driven getting the data right and controlling it through its lifecycle was critical to the credibility and success of the product.  We had to be disciplined about it because being data-driven was a key selling point of the software and we had to demonstrate that not only was our own house in order but that we could help customers who weren’t in such a good place with their data.

 How did you start working in Data Governance?

It wasn’t a conscious decision to work in that area and I’ve never really worn that badge overtly.  It became part of my role because it was naturally a part of what my day job was.  In fact I didn’t recognise that I was doing it as a specific part of my role at first.  It was only when I started to make use of the DAMA framework that I began to realise exactly how my role was spread across the range of data management activity and that a substantial part of what I did fell under the Data Governance banner.

What where your initial thoughts when you first fully understood what you had got into?

Because I had been doing what I had been doing for a number of years there was no sudden epiphany-like moment.  I managed everything in my remit that I needed to and we had robust processes that meant everything was controlled.  That meant the governance aspects were more about ensuring people knew what the established processes were and what they had to do in order to keep the development machine working smoothly. 

Are there any particular resources that you found useful support when you were starting out?

Common sense!  When I first started in this area I wasn’t aware of any specific formal frameworks so I relied on my mathematical training and logic, thinking things through and also tapping the experience of my manager.  He had been working with data for a long time and brought a wealth of experience from a number of large and small organisations.  When I discovered the DAMA framework and started to dig into that I found that we aligned nicely with what DAMA talked about.  Since then I have looked at other frameworks and am never afraid to pick the best elements of each.  I do ensure that those elements can neatly fit with what we already have, though.  That must be done up front otherwise you can find yourself in a situation where you have a random collection of non-integrated tools and techniques which promote conflict and confusion. 

What is the biggest Data Governance challenge you have faced so far?

Data Stewardship is a thorny problem.  It is challenging getting people in a business to take responsibility for their own data and make them realise that IT is not the owner of the data.  IT departments may provide the services, facilities and expertise that support the data but they don’t own the data and getting that message across isn’t something that happens in just one conversation.  It takes repeated discussion and putting the message across consistently but in as many different ways as you can.  Sooner or later people will begin to understand.

What have you implemented or solved so far that you are particularly proud of?

One thing I still consider very successful is the analysis and design work I did for a database to support head office and Point of Sale software.  The application suite was data driven and the database to support the head office functionality was designed from scratch.  Some very detailed analysis and innovative design work by the whole team resulted in a system that was capable of supporting the requirements in a way that wasn’t customer specific.  This made the product very flexible but still relatively straightforward to configure because the majority of the documentation was produced at the time of the design and development.

How has changing roles impacted on your ability to improve Data Governance at BAE Systems?

Interestingly I don’t think the move to a more senior position will, in itself, change things.  Instead I think the fact that I am now working in the core Enterprise Architecture team will result in me being able to more directly influence strategy and help the business shape and mature its EA capability.   

What single piece of advice would you give someone just starting out in Data Governance?

Be collaborative.  Your core business teams have to be able to work with what you do.  You can produce perfect data strategies and governance frameworks, but you have to provide the support that allows the business to transition from where they are to where they need to be to comply with them.  To do that they need your help, they can’t do it alone as they probably won’t understand what has been put in place, why it is there or how it benefits them and the wider business.  There is a big communications and support job you have to do.  Taking a three line whip approach is not a recipe for success. 

Finally, what do you wish you had known or done differently when you were just starting out in Data Governance?

Hindsight is a marvellous thing and it is difficult to single any one thing out.  My career route has taken me from hands-on development through architecture to management and I have grown into and then out of each role into the next one.  If I had known at the start what I know now I may not have been in a place to make best use of that knowledge!

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MDM & DG

This blog post at an initial glance looks to be about a jumble of letters.  One thing that perhaps all data management professionals are guilty of is using too many acronyms!  Now I hope if you are previous readers of my blog that you immediately realise that the DG stands for data governance (after all in a blog from me what else would you be expecting?)  And the MDM stands of course for master data management.  Now I say “of course” because I have been involved in a number of MDM initiatives over the years, however, several recent experiences and conversations have made it clear to me that this term is still not well understood. 

So let's start with the basics; according to the DAMA Dictionary of Data Management MDM means:

 Processes that control management of master data values to enable consistent, shared, contextual use across systems, of the most accurate, timely and relevant version of truth about essential business entities.

So if MDM is about the management of our master data, we need to be clear what our master data is.  At its simplest it is a single source of data that is critical for a business to operate and designed to be used across processes and systems. For example: product, customer, employees, suppliers etc.  Some people call this a golden record and if you're talking about mastering customer data, you often hear it referred to as a single customer view.

Now that we all understand what MDM is, I can share that my biggest concern is not the lack of understanding of what it is, but more worryingly that a significant proportion of people do not understand how critical implementing data governance is to the success of your MDM project.  Indeed this message was mentioned in several presentations I attended last week at the excellent Master Data Management and Data Governance Conference in London (there is a clue in their relationship in the fact that the two conferences are run jointly).

A few weeks ago I was asked if I could use an analogy to explain this relationship between MDM and DG.  I've never used one before and couldn't immediately think of one I felt entirely happy with.  Being a strong believer in the wisdom of crowds, I posed the question on LinkedIn and got a great response (including the usual warnings about the dangers of using analogies!) 

The best analogy we came up with is to imagine that your MDM system is the equivalent to the human body, that the data on that system is the equivalent of food/fuel for the body and data governance is the rules/commonsense applied to what food you do or do not consume.  As we all know if we consume good wholesome food, we feel healthier, have more energy and tend to make the right decisions.  If we have abandoned healthy habits for a period of time and consumed lots of junk food, then our bodies fail to work properly, we feel sluggish, tired and we start to experience problems with our health. 

If we translate this into the data world, it is often the case that organisations implement an MDM solution and migrate data into it with little attention to the quality of that data. It is fairly common for an MDM solution to be implemented without data governance.  This inevitably means that over time as poor quality data is consumed by the system, that it in turn causes problems with the processes that are using that data. 

But what does that mean in practice?  Well let's say, for example, you are implementing PIM (sorry another acronym, Product Information Management, which is MDM for product data).  As you know data governance is all about the people and processes that manage data, so if you implement PIM without DG the types of issues that can occur are:

·      It is likely that the PIM solution will viewed as a technology refresh only and it becomes more challenging to engage the business.

 ·      If the business are not engaged they will not change their approach to capture and manage product data

·      If existing processes of capturing and managing data do not change, the quality of the data will be no better than on the previous system/systems and,

·      All the issues you are experiencing with poor product data previously will continue.  The list of such issues is extensive and can include such things as customers receiving different products than those they ordered or not even being able to find them on your website and also issues with supply chain logistics because product dimensions have been incorrectly captured.

If you're spending a significant amount of money, time and energy implementing a PIM solution, then surely you would want the data quality to improve and with it improve the customer experience and service and also reduce costs at the very least?

This is where data governance has it’s part to play, in ensuring the success of your PIM solution.  Implementing a data governance framework is crucial in defining and articulating the roles that your business stakeholders have to undertake in defining, monitoring and managing your product data.  This framework in itself is a key component in the successful engagement of your stakeholders and transforming for example Product Managers, from people who thought they managed products (and the suppliers of those products) into people who understand how vital it is to get the correct data captured accurately about those products.

When the data in your PIM system is well structured, well defined and of good quality, then the potential benefits to your company are significant.  So what are you waiting for?  Please make sure that if your organisation is currently implementing PIM, or any other MDM solution, that you implement data governance at the same time.

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Data Governance Interview - Nigel Light

I am pleased that this Data Governance Interview is with experienced Data Governance Practitioner Nigel Light who has been working hard to improve data quality at Ecclesiastical Insurance (and yes they insure churches!)

After completing a degree in Chemistry and Geology at the Univeristy of Leicester Nigel has since followed the traditional path of IT development and systems/business analysis (mostly in General Insurance), over the last 30 years. 

Outside of work he enjoys being outdoors, particularly cycling and walking, trying to tame his garden and is a long-suffering Gloucester Rugby fan/member (which, I feel, entitles me to the odd beer or 2 at times!).

How long have you been working in Data Governance?

 On and off, around 8 years.

How did you start working in Data Governance?

I first started working to improve our client data as part of a CRM project but have since been instrumental in implementing solutions to improve our decision making data.

What where your initial thoughts when you first fully understood what you had got into?

The anorak fitted!

I get satisfaction from making things better and delivering improvements. The link to the business benefits from improved data that can be made appealed to me and I soon became a strong advocate.

Are there any particular resources that you found useful support when you were starting out?

I have been lucky with the solution vendors that we have worked with in that they have been really keen to work with us,  understand our requirements and share their expertise.

I have learnt a lot from them and also from the Data Quality and Governance Community as a whole who are always helpful and forthcoming.

What is the biggest Data Governance challenge you have faced so far?

I think the challenge is yet to come. Setting up a Data Quality Programme is a no-brainer and most people buy into it; making it stick when other business distractions come along is much harder.

What have you implemented or solved so far that you are particularly proud of?

Apart from the technical solutions we have built and deployed, I am proud of the way that certain individuals within the organisation I work for have bought into the process; to the extent that one business area regularly reports zero Data Quality issues each month!

What single piece of advice would you give someone just starting out in Data Governance?

 Get away from your desk and spread the word.

Data Quality won’t truly become ‘Business As Usual’ within an organisation unless there is a shift-change in mentality and I try to take every opportunity I can to promote the benefits of the programme and support the business community who are actually responsible for capturing, correcting and improving the data – as well as deploying solutions to stop issues occurring in the first place.

This should be supported by some really meaningful KPI measurements to help monitor improvements which can be used to encourage, motivate and support change.

Finally, what do you wish you had known or done differently when you were just starting out in Data Governance?

I realised early on that all data issues could not be fixed in one project! It is a more of a slow burning, long-term aim with gradual improvements being made rather than a big-bang, one-off approach and on to the next task.

My free report reveals why companies struggle to successfully implement data governance. Discover how to quickly get you data governance initiative on track by downloading this free report