When is a Data Quality Issue not a Data Quality Issue?

When helping my clients implement a Data Quality Issue Management Process I always come across resistance to implement the process. Even when it is up and running some stakeholders come up with interesting reasons why they don't need to use it.

The most obvious one of course being that all their data is fine so there is nothing to report. Now I am optimist in most things but experience has taught me to be a little more realistic when discussing organisation's data and although in such circumstances I really want to believe them, experience tells me that that is unlikely to be the case.

An amusing situation I have come across is that the data was wrong but they don't know what was exactly wrong with the data, so they won't report it as an issue! Others include things like: "but it's a process that needs to be fixed not the data, so I won't report it as a data quality issue" and "it's not that there's a problem with it, it's just not there"!  There have also been numerous occasions when I have been told "but we have a work around for that, so don't need to report it".

Now dealing with stakeholders and the obstacles they throw up when you are trying to implement a data quality issue resolution process is exactly the kind of thing I like to write blogs on.  I'd really appreciate your input in sharing similar such comments that you have experienced, so that I can identify the common themes and then share some tips and advice on how to deal with the most common push backs!

In the meantime you can read my free report which reveals why companies struggle to successfully implement data governance.  

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7 Tips for Running a Successful Data Governance Forum

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At Data Owner Forums, Data Governance Committees or whatever you call yours, you must make everything appear effortless and elegant giving the impression that all is progressing swimmingly and easily.  But beware, it may well be the former but never underestimate the amount of effort required in order to create the impression of the latter.

The elegance of a swan comes to mind as the best analogy for the situation, especially early on in your data governance initiative when a great deal of frantic paddling under the water is required (but to be honest a fair amount of effort is required on an ongoing basis).

As the Data Governance Committee is often set up fairly early on a Data Governance initiative and may well be involved in steering the implementation of your data governance framework, it is vital that it functions successfully, so I thought I would share with you my top tips for running a successful forum:

Timing is Tantamount

Do not set it up until it has a function to serve. If it is the only part of your DG Framework which you have implemented, it is doomed to fail as it will have nothing to do. Everyone these days spends too much time in meetings, no one will thank you (and to be honest they probably won't agree to attend) if it doesn't yet have anything to do - it may be that you want it to steer the DG initiative but make that clear and include in its terms of reference how and when it will evolve into a business as usual body.

Casting the Chair

The chair of your committee needs to be a senior supporter of your data governance initiative, ideally your senior sponsor, to give it credibility and influence.  Do not think that as the Data Governance Manager you should chair this meeting - your role is to facilitate, provide expert advice and to ensure that all goes swimmingly, but never to chair the meeting.

Action Packed Agendas

Do not hold a meeting if there is not enough content on the agenda.  If there is nothing to discuss, debate or approve, what are you holding the meeting for? Straightforward updates on progress can always be circulated by email.  It is better to cancel or reschedule a meeting than to insist on holding it with a mediocre agenda - this will result in stakeholder disengagement.

Particular Preparation

Prepare, Prepare, Prepare! It sounds obvious, but is often overlooked.  The attendees of this meeting will be senior people who are pressed for time. Make sure that none of the time they have allocated to your meeting gets wasted, make sure everything is planned and organised and don't overlook the basic admin tasks such as booking meeting rooms, arranging conference calls and printing papers.  You do not want such minor issues to distract focus and eat into to the valuable time you have available for important data decisions to be made.

Perfect Planning

A continuation of the previous tip I'll admit, but you really need to plan well for the meetings.  Agree the agenda well in advance of the meeting with the Chair and give plenty of notice to those required to submit papers or present at the meeting (and it doesn’t do any harm to remind them a week or so ahead of when you need their submissions.)

Send the meeting pack out in advance but not too soon or too late. Too soon and it will get lost, too late and your attendees won't have time to read and digest the documents before the meeting.  I have found that two or three working days in advance works well, but that will of course depend on the culture and working practices of your organisation.

No Surprises

Never ask for big decisions to be made without giving plenty of warning. Share significant proposals with key members (ideally all of them, if you have the time and calendars allow) so that they are on board ahead of the meeting.  This is particularly important before the inaugural meeting of your committee.  Simply inviting them and hoping that they will show up on the day just will not work. Before the first meeting you have to make the time and effort to meet with each of your members individually, to gain their support for the forum and to give them each an opportunity away from their peers to provide input into the terms of reference for the committee.

 Stakeholder Support

You may well be presenting as Data Governance Manager and you need to ensure that you are well prepared for that, but do not forget your other stakeholders. Just because you are not presenting a topic doesn't mean that you can leave those agenda items to chance.  Support your presenters and stakeholders, both in advance of and at the meeting, so that their proposals and presentations achieve the desired outcome.

 

This list is certainly not exhaustive but by now you may well be exhausted from all that paddling!  But I hope that this has given you some insight into how to ensure that your Data Governance Council is successful and please do share your own tips for success by adding your comments to this blog.

 

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 - Robin Stielau

 

Robin Stielau is the IT Director with Brady Corporation, Milwaukee Wisconsin. Robin has  been with Brady for 33 years and is currently accountable for the enterprise global technologies that enable Sales, Marketing and Customer Services, global PIM (Product Information Management) capabilities and global master data governance.

How long have you been working in Data Governance?

I have been directly accountable for master data governance at Brady since 2015. 

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

What motivated me to accept responsibility for master data governance was the obvious business need and my passion for improved data. I had a very clear vision of how to go about getting it.  Master data governance was the responsibility of a central team outside of IT. Changing circumstances at Brady presented me with the opportunity to get involved and I requested the data governance function be moved into IT under my direction after which it was.

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

I call it a lack of ego. That doesn’t mean that I don’t have one, but one of the most important characteristics of success in governing data is recognizing and staying true to the fact that the data governance team does not own the data or decisions surrounding it. The reason we exist is to facilitate and hold those who do accountable. We are servants to the methodology. Facilitation skills are critical. Bringing together owners of various data domains with data consumers on a regular cadence to address data requirements, what healthy data looks like and how to measure it, improvement roadmaps to correct or complete data and data processes and to eventually provide visibility to improved business outcomes based on more accurate, complete and timely data.  Passion, commitment and grit as governing data is never ending.

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

  • Nicola Askham is a great resource. In a world of information overload, I found her communication on the topic to be most helpful in understanding what data governance was and wasn’t; her communication is clear and straightforward.
  • Talking with as many peers and experts as possible at conferences and other business meetings
  • Blogs, whitepapers.
  • Stibo was a great resource to me (our PIM is a Stibo product, STEP)

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

My biggest challenge was to change the perception in Brady of what master data governance is and is not. Previous data governance management was more involved in making decisions regarding master data as well as changing data the governance team felt needed to change. This was damaging to the program as business data owners were not making decisions nor were they always in agreement with the changes. “Under new management” – we changed this.

We occasionally have challenges with overloaded data owners or wrong people identified as data owners. Data owners can’t be by name only or any person that has some capacity, they have to have some skin in the game and be committed. If not, we force a change.

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

It’s a long term journey, not a race. Having strong executive sponsorship is definitely helpful.

My most memorable experience with data governance was the “ah-ha” moment one of our key business leaders had when shown the negative customer experience on one of our websites resulting from bad product.  In this case it was a size attribute for one of our key products; a set of signs.  The size had been entered on signs within the set in multiple (non-standard) ways; 7 x 10, 7 in x 10in, 7 in L x 10 in H, etc. Unfortunately all of the non-standard sizes appeared in the left hand navigation on the site. It presented a horrible experience for our customers and was the direct result of non-standard master data.

We now had a believer in the value of good master data. I use this example often when explaining the value of standard, accurate master data.

Having read my interview with Robin 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 - Charles Joseph of Datazed

 

Charles Joseph has recently set up as a data governance consultant, Datazed, following fifteen years working in consulting, compliance and insurance.  Charles sees data governance as the foundation of being able to make good data-led decisions.

How did you start working in Data Governance?

 It was a journey that looks logical in hindsight, but wasn’t at the time!  I started as a graduate consultant at Deloitte, got involved in a project to help the internal compliance team roll out a suite of new systems, and eventually focused on the data that supported those systems.  By this point, my three week assignment had gone past nine years!

I was then headhunted for a role at Beazley, which is a specialist insurer in the Lloyd’s of London market, on their data workstream for Solvency II.  That was in 2011.  At the end of 2016, I decided that I wanted to work for myself and incorporated as Datazed Ltd.

What are your plans for Datazed?

Having spent my working career at just two organisations, I’m really excited to be getting out into the wider world and working with lots of different people to help them with their data challenges and opportunities.  This could range from a review of their existing approaches, all the way through to creating a data strategy and managing its execution. Anyone who could be interested in this should contact me via my website or LinkedIn.

I’m also partnering with some software vendors in the data space.  What’s really great is that these partnerships are not exclusive, as there is an appreciation that the solution has to be right for the client.

You can find out more about Datazed at www.datazed.co.uk

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

When researching for the Beazley role, I realised that I had done a lot of data quality work, but without the structure around it.  Ken O’Connor’s blog and Dylan Jones’ dataqualitypro.com were particularly helpful. 

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

Once we had delivered on the Solvency II work, we naively felt that we could strip off the gold plating of S2 and deliver some really useful data processes to the rest of the business.  The almost total lack of buy-in from those other departments made me realise that we had to work much harder on selling these ideas and benefits.

The other memorable challenge was the first time I presented to an audience on the subject of data governance.  It was nerve-wracking to expose my own opinions and ideas to people working in the same industry – but it’s an incredibly good way of making sure that you fully understand those ideas and that they make sense.

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

Pick your organisation very carefully.  There are many organisations with data teams, but few of these roles are similar when you actually see the job specification. 

Look for a manager or leader who, when you meet them, is passionate about what data can do.  Then be that passionate yourself.

I learned a lot about data governance from the material shared by experts in the field – I mentioned Ken and Dylan’s websites above, but there also plenty of groups on LinkedIn in our area, some of which have some great insights and discussions.  This inspired me to go on and do a few Pulse articles myself.

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

Periodically, there will be doors that can be pushed open to get good data practices in place.  This might be regulatory (e.g. Solvency II, GDPR) or project based (e.g. a Finance Transformation Programme).  These opportunities do not come along often, so exploit them as much as you can.

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

 

Data Governance Interview - Father Christmas

In my final blog post of the year, I have been extremely lucky to do a Data Governance interview with a very special person.  Known as Father Christmas to my English readers and Santa Claus to my international audience, this person is the personification of Christmas.   Although he may not be your “typical” Data Governance person, it does play a crucial part in the success of his endeavours. Read on to find out how…

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How long have you been working in Data Governance?

Well to be honest, it’s not what I consider my main role, but it has formed a vital part of my activities for as long as I can remember.

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

To be fair I probably didn’t give it any thought for the first few hundred years, but as the population and the traditions of Christmas grew, it became obvious that I had to do something about my record keeping, so that I could continue to deliver the excellent service that children around the world have come to expect. So when I started noticing mistakes about who was on the Naughty and Nice Lists, I knew we had to do something to manage our data better.

I suppose you must create a lot of data?

I certainly do, there’s the main records like childrens names, their location, their behavior records and also their taste in toys.  History is very important as well – I don’t want to give a child the same present this year as last!

In the early days that was all we focused on, but then we realized lots of things need good data.  For example maintenance records and flying hours for the sleigh.  One year we found out to our cost what happens if you don’t replace key mechanical parts before they wear out!

Location data is also key in planning the optimal route for Christmas Eve.  It used to keep a whole team of elves occupied all year updating and maintaining our geodata, but these days we source that data externally and that team have been able to return to their preferred toy making roles.

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

Now that would have to be my perfectionism and need for everything to be delivered seamlessly, also to exceed my customers expectations every single time.  That makes me focus tirelessly on getting the data right so that everything happens just like magic on that one all important night of the year.

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

To be honest there wasn’t anything available as I was working out how to manage my data better!  I think the first article I ever saw online, that mentioned Data Governance, was a scientific study of penguins in Antarctica.  That was about 15 years ago and it was not really of interest to me as I’m based in the North Pole, not the South and had pretty much got Data Governance sussed by then!*

What was the biggest challenge you faced implementing Data Governance?

That would be getting the elves to engage in the process in the first place – they really didn’t get what data had to do with making and delivering toys!  It took me several attempts before I worked out that I had to explain Data Governance in terms of what it meant for them. 

So when I stopped talking about the need to manage our data better in vague terms and started talking about making sure that the rights toys were made and delivered on time, to the right children, it started making sense to them and the initiative really started to be accepted and make a difference. 

At that point it changed from mutterings about “he’s lost the plot” to elves clamoring to be Data Owners and Data Stewards – it was an amazing and heartwarming time!

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

Don’t expect miracles, it is going to take a long time and be hard work but believe me, it will be worth it in the end!

 

So think on for next year and then yule know what miracles Data Governance can truly help you achieve.

Yo Ho Ho!

 

*Interviewers note – If you think Father Christmas is making this up, I can assure you that that scientific study does indeed exist, I recall it being the first mention of Data Governance that I too ever found online!

 

GDPR and Data Governance

With a number of my clients, I am finding that I am getting increasingly involved in their GDPR Projects as having a good Data Governance Framework helps you meet some of the requirements of GDPR.

GDPR impacts everyone who holds personal data so I thought I would ask Tejasvi Addagada to provide a useful overview of the subject:

 

It is imperative that the privacy needs of EU residents must be harnessed through GDPR by 25 May 2018. Moreover, GDPR necessitates coverage of private information that is processed by any organisation, across the globe. This means every organisation with global presence must embrace these privacy requirements. Regulatory landscape is fast evolving while also requiring firms with global operations to adopt the highest regulatory requirements from a region that can be leveraged as preparedness in other regions.

Privacy is not only a requirement from GDPR, but is also a major driver from an organisation’s perspective of risk. Most of the personal information collected for years now is vulnerable to threats and events of malicious theft, accidental disclosure, failure in appropriate design and usage. Today, protecting an organization’s reputation is the most significant risk management challenge. Negative publicity to a firm, will cause a decline in the customer base, reduce revenue and lead to costly litigation.

Privacy is not a new dimension that firms are planning to embrace suddenly. Most mature organisations have Information Privacy and Data Privacy clearly delineated and accounted for by stand-alone division in a firm. In my experience, I have seen Information privacy aligned with the Technology Risk function while Data privacy, as predictable, lies with Data Management and Governance. There are a couple of good articles that brief on the way forward for “Privacy as a dimension” within Data Management.

I was on a holiday this week, to Wayanad, a hill station in Kerala that boasts plush landscapes, streams and the native culture of the locals.  I booked the hotel on a travel app, which for sure has collected my personal information. This data has been shared with restaurants owned by the same group that gave me offers and requested feedback for every dining experience. Sadly, the hotel doesn’t have a travel desk, but using his contacts, the desk manager fixed our local travel arrangements. Further, the Government forest division that manages the tourist destinations collected my private data for accounting and safety, at 5 destinations. In a span of 3 days I know there is redundancy and various levels of data that is collected by various organisations. When I asked the hotel on the management of the private information they were not sure on any procedures that exist today. Further, most of the data exists still exists in paper.

Most financial organisations embracing data management and governance have, for some time now, integrated Data Privacy and Security as an integral dimension. Working with these firms, I can say that they are prepared for GDPR. There is a Governance function that directs, monitors and evaluates while also enforcing accountabilities through ownership and data stewardship and ownership. On the other hand, a percentage of other organisations have some level of privacy management capabilities customised in the form of projects, for specific needs.

GDPR stress on the responsibilities, accountabilities, and evidencing the controls for privacy.

Here are ten simple steps to get started –

1)    A current capability analysis must be performed to understand the people, process and technology capabilities in place to collect, process, manage privacy and security controls for Personally identifiable information of customers and employees. This will be much easier if data privacy management is already an integral dimension, embraced by a Chief Data Office.

2)    The firm must draft a data privacy policy to ensure enforcement of compliance with mandatory regulatory, internal compliance, best practices, legal and ethical requirements along with the need for managing risks. These aspects must be clearly embedded into the privacy policy to provide guidance to personnel. This assists the personnel in carrying out any activity that includes private and confidential information. It is suggestable to understand the needs for privacy and options to achieve privacy management, before embarking on a full-scale implementation. Data Management Strategy must be developed to include Data Privacy management aspects leveraging current capabilities assessment. Data Management Strategy and Privacy Management must be aligned with organisational objectives. In addition, the target control environment and organisational structure for Data Privacy and Security Management must be defined including the identification of a privacy officer etc.

3)    From the current capability analysis, understand the “Direct Client identifying” and “Indirect client identifying” data that is collected and processed by the firm. There is a difference between a privacy and security classification. If the firm doesn’t have classifications available it needs to engage with the risk function to baseline the levels of allowable privacy classifications. Based on the same the council and data stewards can enable the data owners to classify the data that they own.

4)    It is much easier to manage the data if it is logically classified into domains based on its business characteristics like the customer domain. Likewise, employee personal data can also be classified under a human resources domain. Further, based on current need, a dataset or a sub domain can be classified as customer preferences that would make it much easier to manage data related to customer consensus like opt-in/opt-out.

5)    Through Governance function, the chief data office ensures that ownership of data is aligned, data owners are accountable, stewards are made responsible for enforcement of activities related to privacy management. Further, these roles would be updated in the data glossaries and dictionaries through Metadata management. Once data ownership is enabled the existing privacy classifications for customer and the employee data can be actively managed. This also sets the context for the data owner in capturing entitlements (control requirements) across the data lifecycle. From a risk perspective, these activities play a key role in strengthening the 1st line of defence in the firm.

6)    Based on the plan for implementation of controls for data privacy, projects must be sponsored and roadmaps must be put forth, perhaps timeboxed to meet regulatory timelines. Once the controls are in place, their existence along with KCIs, KRIs need to be captured as Metadata in a glossary. This strengthens the evidencing aspect of the regulation. Further, the control indicators and risk indicators must be aggregated as scorecards for reporting to board regulators.

7)    The firm must embrace “Privacy by design” mainstream by having to operationalise policy in every change (projects). This ensures that every new capability or change to existing process, system or organisation structure is assessed for privacy impact, controls and best practices ensured and recorded.

8)  Data privacy management must ensure that all privately classified data elements are classified, recorded for entitlements, security controls for privacy included Eg: deanonymisation, masking based on context, encryption, transfer contracts to name a few. Entitlements and controls must be recorded as Metadata in glossaries.

9)   The controls for securing private data, are established at a data service level wherever applicable rather than at an application level. The divisional and governance forums ensure that the guidelines for data controls are placed for new changes and changes to existing capabilities. Once the Privacy Impact Assessments are performed, the gaps are analysed and a program focusing on establishing a control environment for such data domains is commissioned in line with the funding model. Any non-adherence to establish controls should be signed off by the governance council with adequate evidence to bypass the controls. The level of controls includes administrative (process), technical and physical controls to secure Private data.

10) Data Privacy cannot function alone and would require close integration with other dimensions including Metadata, Data Quality, lifecycle and risk management.

a.    Metadata management is a major enabler to classify data into domains and assign privacy classifications.

b.    The data quality function ensures that integrity of data is maintained while data privacy and security ensures that modification is being performed by designated roles. Further, the currency and accuracy of personally identifiable information must be ensured.

c.     Data Lifecycle management simplifies the data landscape allowing the firm to understand - Which system or personnel or process collects a data element like tax number? Where else does tax number flow in its processing? Where is it stored, transformed, decayed? Which process or personnel or system applies tax number and for which purpose?

d.    The Data risk management ensures adherence to regulatory needs including privacy assessments, risk scoring, control assessments, risk event or privacy incident reporting and escalation. It also ensures that there are policy self-assessments and identification of blanket in-flight risks along with risk evaluation and response.

Having read this article with Tejasvi 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

Tejasvi Addagada is a Data Management and Governance consultant with nine years of success in assisting clients, develop and optimize data governance solutions. Tejasvi has worked with the top ten major global financial service providers by providing a wide range of services including strategy analysis, data analysis & architecting, service rationalization, digital transformation and process excellence. Tejasvi has diverse experience in the areas of consumer banking, commercial banking and capital markets. He has served as a process and domain consultant for the top ten major banks while receiving several accolades for the success achieved.

Now, he is delivering his services to a major investment management firm as a principal data consultant in the Data Governance Office. Before this stint, he has worked with two major banks in setting up and orchestrating data governance services from grass roots.

Tejasvi is an avid thought leader in the industry. He likes to connect with other thought leaders while blogging on the technological and business advances. His write ups address common challenges and opportunities that the firms need to tackle to make their way forward in the industry. Apart from that, he is an abstract painter and an art enthusiast and likes to spend time with family.

Tejasvi can be reached at Tejasvichand@gmail.com

Data Governance Interview - Mark Horseman

Mark is an IT professional with nearly 20 years’ experience.  Mark moved into Data Quality, Master Data Management, and Data Governance early in his career and has been working extensively in BI since 2005.  Mark currently leads a team of IT professionals architecting a Data Warehouse at Vecima Networks.

How long have you been working in Data Governance?

I’ve been working in Data Governance off-and-on since 2007/08, but have been working with Data Quality since 2004/05.

How did you start working in Data Governance?

I started my IT Career in Sales in the 90’s, achieved a B.Sc in Computer Science and moved to programming.  During my internship, I worked on an Identity Management System for the University of Saskatchewan.  As part of that work, a lot of my programming was dealing with data associated with Students, Staff, and Faculty.

From that experience, I had moved on to Student Information Systems, and worked on integrating data from our Identity Management solution to our purchased Student system.  (“SCT Banner” at that time, now known as “Ellucian”)

After that integration, we worked on a Business Intelligence solution, and I became keenly aware of issues in Data Quality (2004/05 time frame) and how Data Quality impacted the understanding of the operations of the institution.

From there I moved on to Institutional Research, and began getting into data definitions and understanding data stewardship, ownership, and governance, although no one called it “Data Governance”.  I had begun reading as much content as I could, and kicked off my own blog as a method to reach out to the really talented people in the field.  This is where I ran into “The Data Governance Institute” (http://www.datagovernance.com/), books by Jill Dyché, and Jim Harris’s “OCDQ” blog.

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

I had an epiphany that I landed on something that sounded a bit like IT, but wasn’t really an IT problem or process at all.  It was something that required outreach and awareness that data is an asset and that stakeholders needed processes to ensure that the data asset was a value to the institution.

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

Besides the excellent things mentioned above, the sheer brilliance and content available on Twitter.  There are a lot of really talented people out there providing thought provoking content absolutely free!

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

The word “Data Governance” is the biggest challenge to its implementation.  In the places I’ve gone to talk about Data Governance, that’s the comment I hear.  This could be a Saskatchewan / Canadian culture thing, but it’s as though the term “Governance” implies a level of bureaucracy that people find intimidating.  I find that processes around data management require a packaging that doesn’t include the term to achieve acceptance.

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

Back in my Higher Education days, I had implemented the “Data Quality Golf-Card”.  We had used the Kimball idea of Data Quality Screens (think panning for gold).  Using these Quality Tests, we had assigned a value to each time when data failed to pass through the screen.

Each screen was associated with a particular stakeholder and we met regularly to try and get their score down to “Par”.

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

Work hard at understanding the culture and what types of processes will be a good fit.  If there are vestiges of process in-place, work with it to implement Data Governance.

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

I wish I had started sooner.  BI without Data Governance was more challenging than it needed to be.

Having read my interview with Mark 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 - Nigel Turner

Nigel Turner

Nigel has worked in data management for over 25 years.   He spent much of his career at British Telecommunications (BT) where he led a series of company wide data improvement projects which brought huge benefits to BT.  Also in BT, he created and ran large Information Management and Customer Relationship Management (CRM) consultancy and delivery practices.  After leaving the company in 2010 Nigel has since been a data consultant with several organisations including Trillium Software and FromHereOn (aka Enterprise Architects).  Currently he is Principal Information Management consultant EMEA for Global Data Strategy.  He has been an active member of the Data Management Association (DAMA) for many years and is currently Vice-Chair of the DAMA UK chapter.  

How long have you been working in Data Governance?

At least 20 years, probably before the term Data Governance was even coined and popularised.  Although we did not have a name for it at that time, Data Governance became an issue in BT in the 1990s. When running data improvement projects it became obvious that a lack of business leadership and accountability for data was a major cause of the data quality problems we uncovered, and a significant barrier to fixing them.  So we placed a big emphasis on getting business people interested and actively involved, and they eventually led the improvement projects.  In practice they acted as de facto data owners and data stewards, even if we didn’t call them that at the time. 

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

Like many people, purely by accident.  Until the 1990s I had a pretty bog standard IT career, progressing from a programmer to business analyst, then onto team leadership and project management.  Then I ran a project to investigate and remedy outstanding software faults on BT’s biggest customer service system at that time.  Its achievements were brought to the attention of a BT board member, the Director of Strategy.  She met me and said ‘I want you to lead some work I have started on how we can improve our overall management of data’.  Saying no was not a good career option, so that’s how I got into data as a focus in its own right.  From there, data quality and data governance eventually became an abiding interest and passion.

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

I suppose it’s for others to judge my success (or otherwise) but I feel I’ve been helped by a couple of things.  First, I am not, and never have been, a technology geek, despite my many years in IT.  So my natural instinct is to start any data challenge not with technology, but by a focus on business and its people.   Nowhere is this more important than Data Governance where 80% of success depends on getting people to think differently about data, and in creating a direct link between Data Governance and what the business is trying to achieve.  Technology has an important part to play in delivering Data Governance, but is always an enabler, never a starting point. 

Second, a sense of humour definitely helps. All of us who have tried to sell the benefits of Data Governance have at some point been met with scepticism, indifference, incomprehension or downright hostility.  The ability to try to overcome this with a smile and a lighthearted quip, coupled with an underlying determination to win people over, has definitely helped.  It doesn’t always work, but it often can.   

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

I always found inspiration in the early pioneers of data quality and Data Governance, Tom Redman and Larry English.  Between them they have published several books and are the founding fathers of the discipline.  It’s also worth looking at the Data Management Association (DAMA) Body of Knowledge (DMBOK) which has a useful section on Data Governance.  Moreover in DAMA UK we are running a very successful mentoring scheme, where grizzled Data Governance people (such as myself) help and advise less experienced people.  This is proving to be a great success.      

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

It has to be my time in BT.  When I started, as is the case today, BT was a large and very complex global organisation with vast volumes and varieties of data, held on multiple platforms and systems.  When embarking on the Data Governance journey the hardest part was not working out what the finishing line would look like, but where to start.  So I spent the first few months in my role trying to work out the first steps.  Eventually I connected with some enthusiastic business and IT people in BT’s Wholesale division, and helped them launch some pilot data improvement projects.  They were a great success, with large business benefits, and it was a lot easier from there.  The primary lesson?  In Data Governance it’s important to show real returns early to secure and sustain support, so find a known data problem area, and start tackling real problems.

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

This is a tricky one.  Since leaving BT I have talked and worked with over 150 organisations on their data and Data Governance challenges.   They include both the public and private sectors, pretty much every industry vertical (including Retail, Energy, Utilities, Transport, Banking, Professional Services and so on), and span across many countries. 

What’s struck me is that whereas all appear very different and have widely varying drivers and business models, the challenges they face are remarkably similar.  With Governance, they consistently centre on getting senior executive support and buy in, building the business case, winning business and IT hearts and minds, creating realistic & deliverable action roadmaps, and proving the projected benefits. So, to answer the question, I’d like to help all of them!

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

In Data Governance, influencing skills are critical.  In many organisations, managing data inefficiently is business as usual.  And it’s been done that way for so long, it often feels like you are trying to move the moon with a drinking straw.  So plan your strategy for how to kick start the cultural and behavioral change needed.  Identify the early key stakeholders and get to understand their business and what drives them.  Use this to prepare your influencing strategies before you engage with them, and relate Data Governance directly to their concerns and aspirations.  

One final piece of advice.  When you are dealing with busy people with many urgent and often competing priorities, don’t ask too much of them, especially in your early encounters.  Ease them in to the Governance world through simple and incremental steps.   You’ll frighten them off if you ask for the world.

Finally I wondered if you could share a memorable data governance experience (either humorous or challenging)?

One that always sticks in my mind is an early workshop I ran with some business people in BT.  To prove the need for Governance we profiled their key data sources and produced lots of hard evidence of data issues and problems.  Most attendees found the results surprising, and sometimes shocking, and so were quickly receptive to listen to our proposal for improving its quality and management.  But one attendee was adamant that ‘our tool must be wrong’ and refused to accept the findings.  He stormed out and told us ‘he would prove it’.  Thirty minutes later he came back to the workshop, sat down and sheepishly told us that our results were indeed accurate; he’d checked the source system!  He quickly learned that the real state of data is often at odds with people’s perceptions.   From that point, he became an enthusiastic proponent of Data Governance.   

Nothing counters negativity like facts.  As the former UK Prime Minister Benjamin Disraeli once said, ‘To be conscious that you are ignorant of the facts is a great step to knowledge’.  In Data Governance, as in life, this is invariably true.

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

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