Can You Automate Data Governance?

Last month, I was at the IRM UK Master Data Management and Data Governance conferences in London. It's great to attend data conferences as they provide valuable opportunities to both learn from others and network with fellow data professionals. This conference was no exception. There was a real buzz and enthusiasm amongst everyone and I was really pleased to see that once again there were an increasing number of attendees with Data Governance in their job titles.

As well as presenting a tutorial on Communicating Your Data Governance Message, I also co-presented with Conrad Chuang of Orchestra Networks. I'd never presented with Conrad before, but as soon as we started preparing for the presentation it was clear that he is as passionate about data as I am. In preparation for the presentation, our conversations frequently included sharing our anecdotes from helping companies with their data. In fact, we did this so much so that it soon became clear that we both had valuable experiences that we ought to share with an audience and by the time we got to deliver the presentation it felt more like Conrad and I were having a conversation about data governance than doing a formal presentation.

The topic of our presentation was Automating Data Governance Policy. The title itself is an indication of how the Data Governance arena is evolving and maturing. Only a few years ago, there were no tools that could help you with your Data Governance initiative whereas today there is a choice of tools.

Last month Conrad and I shared a number of facets of Data Governance as well as related activities that can now all be facilitated with the use of tools. Please note that facilitated is the important word in the previous sentence and you cannot get away from the fact that Data Governance is primarily about people and processes. Tools cannot change this, they can just make life easier for you when implementing and embedding Data Governance. Anyone who forgets this will struggle to be successful!

But if you are clear on the best way to use such tools, they can be very valuable in accelerating and embedding your data governance initiative. If you were not able to attend the conference and missed our presentation don't worry. The feedback was so positive that Orchestra Networks have asked me to repeat the presentation with Conrad as a webinar later this month. You can find out more and register for the webinar here.

If you did make the conference and have found other ways to automate your Data Governance activities please let me know. I'm always keen to hear about innovative practices!

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 Questions - Josiah Kimani

Josiah Kimani is a dedicated professional in the data industry. Having studied in Kenya at the Strathmore University in Management of Information Systems, he exudes a great passion on the quality and governance of data for the benefit of any organization he engages with. He specializes in quality of reference data, process improvement to ensure data is right first time and also issue resolution management, because as sure as you will find issue with data, he believes you need a robust mechanism to resolve those issues. He is an expert in his own right and a delight to work with.

How long have you been working in Data Governance?

I started working in data governance as a freelance consultant for small businesses in 2008. I then took it seriously in 2011 when I realized that it was an extremely important space to be in. So I would say 7 years in total.

How did you start working in Data Governance?

Well I started by helping out small businesses in capturing their data in a structured manner that allowed them to report on the performance of their businesses. This then led me to an environment where data was not very well handled by front line staff which was having an impact in the way the businesses would report. The obvious answer was always the fact that someone in the business knew a lot about the subject and could act as the Subject Matter Expert to fix the issue halfway through and present the results but this never really tackled the underlying root cause. So my passion is to get things right the first time and to put in measures that properly resolve and eradicate root cause, began there.

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

Well, initially, I thought it was quite easy to resolve and when dealing with smaller companies it is indeed quite easy. However, working in the data governance space and getting it right requires change in attitude and behaviour as well as keeping your eye on the big buzz of return on investment. Combining these three things and still being able to maintain professional working relationships could prove to be a challenge and that is when I realized that it was not such an easy space to be in. I knew right then that I required excellent communication skills and stakeholder engagement and management skills.

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

Absolutely! Resources were both the people and the tools. Working with people that understood the data at the frontline and also with IT resources that did not just dwell on the infrastructure but also the data that was held in the infrastructure, made all the difference. These people became the data champions that I would use whenever I needed to impress upon their teams on the importance of good data practices. In addition, the IT experts used open source tools to implement data cleansing capabilities as well as providing outputs that did not meet the business rules. Bringing together the human resource and technology allowed the right results to be achieved but I also used these results and exceptions to address the processes that either needed review or to implement new ones where they did not exist.

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

As I mentioned earlier, getting data governance right requires a change in attitude and behavior towards data. This change is not specific to just an individual or a team but is an organizational change and being an expert in this field, the natural instinct is to lead on those changes. However, if the culture in place is ingrained in the people, the deliverables in the organization then become the “elephant in the room” that need to be tackled but it is not an easy one to deal with. The challenge is to get buy in from the organization both top-down and bottom-up. It requires pegging the concerns identified to the wider organizations KPIs which will be music to the ears at the top but also to elaborate what it means to fail on KPIs from the bottom-up. This also presents a further challenge to the data governance team and that is; understanding the business enough to articulate those specific improvements to both those at the top and those at the frontline. It therefore, goes to show that data governance teams require a combination of business savvy skills as well as a good understanding of Information Systems along with good communication, negotiation and liaison skills that bridge between technology, people and process, which is not always a readily available combination in the market.

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

One thing I have been really proud of and continue to be proud of since I first started this journey in data governance is the processes that I have put in place. At every organization I have worked for, I have implemented a process that did not exist and one that continues to be used long after I have left. I do not profess to have perfect processes and neither do I believe there is such a thing. In fact, I expect that long after I have left, my processes should undergo reviews that improve them or even discard them in tandem with the ever changing demands and technologies. In addition, the processes I have implemented always consider the people and the technology with clear accountabilities. My pride comes not by implementing the process alone but ensuring that the accountabilities are relevant and agreed. The accountabilities are activity focused and not individual focused. Now you might ask what does that mean, and in simple terms it means that putting someone accountable to something and having no actions attached to that accountability means nothing. However, putting actions in place that require to be addressed and then assigning those to an individual or team means that something will be done about it. Many are the times where I have seen accountabilities distributed on a position and individual basis but when you look at what the person actually does to ensure that there are some actions taken to deliver as part of a process you find nothing and this is what organizations call “process breakdown” because the actions have not been attached to a person realistically.

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

One single piece of advice is lead as an expert and believe in yourself. The old adage of “this is how we have always done things” results in someone who is starting up to carry on with the same old ways of working. If one is starting up and they want to lead in the end then they need to follow the simple ABC of governance which I use and it is – Accept nothing, Believe no one and Check everything. Whether one does these on their own or within a team it is important to be vigilant and challenge the status quo because underneath the surface lies a lot of theoretical approaches that have little practicality in supporting the current business status.

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

I have no regrets about anything and I believe that the time I ventured into data governance was my time and I still consider myself quite young so I have a long way to go. However, If I had known that there was such a deep rooted data governance issue in many industries, I would have invested more time much earlier. I don't believe that I am any worse right now but I would be a more seasoned data governance guru. I am also a mentor at the University of Westminster and whenever I get an IT student, I inform them much earlier in their career that Data Governance is a field they need to start investing in much earlier so that they can hone their people and business skills as well as their technical skills and after a number of years they will have the skills I mentioned earlier which are suitable for the data governance expert.

Having read my interview with Josiah 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 - Lee Edwards

Lee had several years in business operational experience before discovering a talent for data design and modelling in 1997.  As Lead Data Architect for the European Enterprise Data Warehouse she successfully incorporated data from several disparate business types across more than 20 different countries into an integrated data model, supporting the business in fulfilling both Management and Regulatory Reporting requirements

Lee also spent 10 years articulating the need for a cross business data management program, campaigning to gain support and ultimately executive approval for the initiative within the European organisation.

Passionate about Data Management, Lee works to progress the industry through serving as Chair of DAMA UK and VP Marketing and Communication for DAMA International, regularly speaking at local and international conferences and acting as a mentor for chapter members.

How long have you been working in Data Governance?

Thinking back, this was when I first started producing management reports on Lotus123 as a clerk umpteen years ago. I was building new functionality to replace paper based reports and the first thing I did was question fluffy or inconsistent definitions with “tell me exactly what this means and how you use it” – of course I didn’t realise then that I was doing DG.

How did you start working in Data Governance?

As a Database Designer and Dataflow Architect I led the analysis for mapping disparate systems from multiple locations to my nice clean conformed streamlined data model. This required much iteration of “how do you know” and “where is the information” and ultimately generated the evidence to justify the requirement for proper DG control.

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

I’m not sure that I know that even now! It’s a constant challenge but rewarding when you can make a difference and prove out that your input benefits the enterprise.

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

Probably predictably but I have to say my DAMA colleagues providing both sound advice, education opportunities and personal validation that I was on the right path and gaining control of enterprise data is the right thing to do.

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

The increase of globalisation and having to start yet again persuading a whole new set of people that it is required and the right thing to do. I’ve observed it’s a human thing to want to make it yours and the Not Invented Here syndrome is very real and can be draining. There is a constant need to keep the evidence of wins (costs and time saved, risks avoided etc.) fresh and at your fingertips as new people come along.

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

Launching data for essential daily Regulatory Reporting in 7 months from a standing start. This was achieved by having thorough control and understanding of the data sources used and harmonised in a monthly BI system and reusing rather than starting again. Sounds like the obvious thing to do but it continues to astonish me how little enterprises seem to do this – start again still appears to be the default. 

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

Work on your communication skills, have an elevator pitch ready, learn about different types of people and how to adapt to get your message across. Oh and join DAMA if I’m allowed to say that! I have found the learning opportunities invaluable.

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

That it was DG that I was doing. When I started it didn’t really have a name, if I’d known about the job brand it may have been easier to communicate and perpetuate – but who knows!

Having read my interview with Lee 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 – Jim Barker

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Jim Barker is a professional in the IT space that has had varied roles starting out as a mainframe programmer, leading data initiatives at Honeywell, and moved on to a product management leadership position for Winshuttle with a focus on data improvement in early 2015. Jim wore out many pairs of shoes as a front-end screen developer prior to PC’s and the Web, grew up with ETL, BI, and Statistical tools, and led many SAP deployment projects, and introduced and evangelized data governance and ‘data as an asset’ at Honeywell. Key highlights of his career include architecting the data warehouse solution at Thomson Legal and Regulatory including a very early start in Big Data in 2001 and Data Governance in 2003, developed the Velocity Data Migration Methodology at Informatica in 2005, and leading data for SAP Site Deployments with Honeywell at over 600 sites in 45 countries..

How long have you been working in Data Governance?

I have been working in and around data governance and data quality since 1994 as part of data warehousing, data integration, and data migration initiatives.

How did you start working in Data Governance?

I was first introduced to data quality at a health insurance firm in 1994 when I used Code1 (Method 1) on the mainframe to correct subscriber and clinic data. This included building improved interfaces with CICS to prevent bad data from being set up in claims systems.

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

I was younger then, and my first thoughts were why is this so difficult? Why can’t folks just set up data right in the first place...that has changed over time but those were my first thoughts. When I first had leadership responsibilities it became more practical, how can we come up with solutions, techniques, and tools to help correct problem data and also stop it in the future.

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

The first real governance solutions I worked with were at Thomson, we leveraged a lot of business objects capability along with First Logic data quality tools...but since no-one was really writing about data quality or data governance at that point, the foundational project management techniques provided by the project management institute (PMI) were what our team used to build out our governance capabilities...

Later, I found some of the information being published by former data warehousing gurus to be helpful, people like Larry English.

As well as working in Data Governance, you’ve also been pursuing a PHD in the discipline. How have you found that?

It is interesting to see how much academics dislike the communication style of consulting and IT leaders. I found that I had to spend much more time writing any coursework to meet style expectations.

The most valuable and enjoyable part of the activity was learning different ways of collecting information through varied qualitative study methods, and using those to talk with other professionals in the realm of data governance.

What do you hope to do with the results of your PhD dissertation?

Once I complete my defense I would like to use my findings in a couple of ways, publish some summary articles, and would like to expand to write a book on lean data management.

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

I think the biggest challenge is how to meet the divergent challenges of new product introduction timescales with the need to have data set up correctly. Folks working in business functions (not data stewards) can get very focused on cycle time reduction and sometimes lose the ability to see the forest thru the trees; they are so worried about getting a product set-up they don’t want to take the time to get the data right and are willing to pay the price in the long-run. This is common across CPG, Manufacturing, Finance, Information, and Defense organizations...with finance firms most interested in getting it right in the first place.

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

Two things come to mind. We built a global team at Honeywell that built out a set of data quality scorecards that helped to expedite the data migration process so with a relatively small team we were doing 10 or more SAP deployments at once and putting focus on time but also on getting the data right. This is something that we received an innovation award from Informatica on for efficiency in M&A.

Second, is building out the data migration methodology at Informatica that many software firms are now using as the standard for what I would call agile+ (the plus being data governance).

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

Keep your eyes open. Don’t go blindly into a tools-only solution, every time you read something or hear something from an expert...figure out what it means in your organization and customize a solution that uses perspectives from many different sources of information...i.e. avoid groupthink.

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

I think I would have put more emphasis on process mapping and focus more on policies and procedures. It is much easier to deal with tools, it is more difficult to understand the process and correct it with the aid of tools to make a difference.

I also wish I would have really understood that you can’t do it alone, you need to have a collection of folks working in concert. People are a huge part of data governance efforts and you need to find ways to get folks in all parts of the organization to embrace the importance of having the data right and go down the data governance path with you.

Having read my interview with Jim 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 - 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.

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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