How To Select The Right Data Governance Tool

There are many tools on the market now that can help you with your data governance initiative. In particular, there are numerous products that hold and manage your data glossary, data catalogue and data dictionaries.  These have proved very popular and the number of players in the market has increased over the last few years.

If you are lucky enough to have the budget to purchase such a tool, please make sure that you're well prepared so that you can choose the right vendor for your organisation’s needs. If you select the wrong tool, it won’t help your Data Governance initiative and even worse it could distract from or even derail it!

To help you avoid making such a mistake I want look at some of the common pitfalls in DG tool selection and the kind of questions you need to ask your vendors, so that you are really clear on what you're looking for before you embark on a tool selection process.

Let's look at the most common pitfalls first.  The three main ones that I've seen are:

·      Little or no business user involvement

·      Unclear requirements

·      Overly complex initial implementation

Taking each of these in turn:

Firstly, there's little or no business involvement early in the process. Many people wait until the tool is purchased and even being implemented before they involve business users.  In my experience, this is a huge problem and should be avoided at all costs.

I have seen a few implementations go wrong because the eventual business users were not involved in selection.  Think about it from their point of view.  They have not asked for such a tool, nor does it help them to do an existing task more quickly or easily.  So, when you come to implement your shiny new tool, the business users feel they're having some IT tool foisted upon them. Generally they do not react well and I can recall one instance when the whole implementation had to go back to the drawing board.  Once the business users understood what they needed to use the tool for, their requirements were vastly different from what had been delivered.

The second pitfall is being unclear on what you require of the tool. Often someone has latched on to the fact that a tool could help them and dived straight in and bought one without being really clear what they want the tool to do. Please make sure that you take  time to work out what your objective is from having the tool. Once you've worked that out, progress to defining some clear detailed requirements (just a requirement to have a data glossary is not sufficient).

Finally, another common pitfall is trying to make the initial implementation too complex. Some of the more established tools on the market have been around for a while and have evolved over time to provide a multitude of functionalities, all of which can facilitate and enable your data governance and data quality activities. But please, when you're looking at selecting a vendor initially,  be very clear what you want a tool to do now. Also, consider what you definitely want it to do in the future.  Finally, you can make a “nice to have” list. Just make sure you take a thorough approach to determine clear requirements.

I've seen implementations of tools fail or the wrong tool selected because of vague or overly complex requirements (just because the tool does it, does not mean that your business really needs it).

Now we've looked at what the main pitfalls are. I wanted to share with you a few questions that would be useful to ask the vendors to ensure they're a good fit for you and your data governance initiative. Since I've highlighted the need for objectives and clear requirements, the first question to ask them is, how does their tool meet your requirements.  Notice I say how does it meet… and not does it meet. If you ask “does your tool meet our requirements”, most vendors will say yes.

What you want to know is how.  Is it simply out of the box functionality that is ready to go or will there have to be manual workarounds, or even worse a lot of customisation or configurations in the tool that may make future upgrades very difficult for you.

Secondly, I'd ask what implementation support will be given to you. You have to remember these tools are by their very nature, flexible, and you need to set them up in a way that works for your business. This means that you will need some support from the vendor. So make sure that you are very clear upfront about what kind of support they will be giving you.  Knowing what is and isn't covered will prevent any nasty surprises in the future.

Thirdly, ask what training they provide for both you and the team implementing it. Perhaps they may even support training your business users on how to use their tool.  Definitely work out what training you want and ask what training is available.

Some final thoughts on how to choose the right Data Governance Tool for your organisation:

I’ve said it already but please remember that to successfully choose the right tool for your company, it is absolutely vital that you are very clear on what you need the tool to do before starting a selection process.  Clear requirements should be the start of the process.

Make sure that you understand not only the support arrangements of the tool (as I mentioned in the last section) but also the upgrade path of the tool. I've come across more than one situation where an organisation has customised a tool to such a degree that is not possible to follow the upgrade path.  On one occasion they needed a project to redesign and implement a new data glossary to be able to upgrade and take advantage of the new functionality.

Lastly, I would say that when you're working with vendors, going through workshops or maybe an RFP process you are going to meet a whole variety of personalities. Bear in mind that these are not the people that you will be working with if you choose and select this tool. Whether you like or dislike them, do not be swayed by the personalities.  They will not be around for the implementation, and the ongoing support will be provided by other people. So don't let yourself be influenced just because you like or dislike their sales team!

Just remember that such tools can be great enablers to your data governance initiative, but they need to be put in place once your data governance initiative is already going so that you are very clear on what you want.

If you are currently looking at choosing a data governance tool why not book a call to discuss how I can support you through the process:

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Data Governance Interview with Jorg Schorning

In this interview Jorg Schorning has been kind enough to share his experiences working in Data Governance. Jorg has been working since 1987 in mostly the utilities, healthcare (care not cure) related to data, information, architecture and business processes. Nowadays he specialises in Enterprise Architecture, Data management and COBIT5 Governance related questions. He currently works for a Dutch consultancy firm Novius, where he acts as Consultant, Architecture/Data coach/trainer and COBIT Assessor.

How long have you been working in Data Governance?

Data Governance hands on: as a project leader I had to migrate lots of Data from old systems to new replacements, but always with the major responsibility to archive the old data for regulatory reasons. As an Architect I deliver services to several clients in order to get Common Data Models in place and maintained. So in total more then 20 years. Looking at the aspects of DAMA, in almost every aspect I have had assignments to optimize process and data working together.

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

First of all let me explain in general how I see governance comparing to management. Governance is steering, giving direction to, monitor this direction and evaluate to adjust the direction with a rather longtime horizon in mind and not more. Management however is more the HOW, create a PDCA cycle to realize the direction starting today and moving to the required direction.

So for me it’s not a single subject to make a career. Data Governance is the glue to make sure that useful data is created, monitored and maintained and above all adding value to the company! I like to help my clients (business executives and CIO) to get grip on the steering aspect and let them give direction to the organizational units to realize what is needed.

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

• I always use “common sense” and try to let stakeholders use this as well.

• I make an accountability framework (of only data in this case) of the stakeholders and look for clues if this is working properly, identify potential issues, focus on behavior of involved people.

• I have developed antennas’ to “feel” where there is a lack of good data, probably due to some missing aspect of data management or even missing processes.

• I look at the current use of data and the desired future use.

• Finding missing architectures (mostly information architectures).

• Identifying (data)links between the processes and the IT.

• Discussing with business what their needs and problems are on the data area

• Using a heatmap based on the DAMA Wheel to address aspects and discuss them.

• I always look at the whole lifecycle of data, from birth (creation) up to death (purge), use COBIT 2019 Managed Data and its activities.

You work a lot with the Utilities / Healthcare Industry – how mature would you say they are in Data Governance?

In some areas of the DAMA Wheel they are very mature or capable as I rather like to address it. This is from the perspective of todays’ business and handling the operational dataflow. Become data driven e.g. demands more capability on data management.

And on top of that the aspect Data Governance and the implementation of it in a practical and handy sense is and stays a hell of a job. Terms like Accountability, delegated accountability and Responsibility makes often eyebrows frown and the reaction is either a clear but wrong answer or a big question mark about accountability.

How clear do you believe the Utilities / Healthcare Industry as a whole is on the difference between Data Governance and Information Governance?

The basic difference in this question is that information is data that is put into context and thus seen as valuable business asset. Recently it is noticeable that business strategy points to data (or even better information) as an asset incorporated with the statement: “We want to be data driven!”. However only few realize how this point could be reached. That a solid basis, a data foundation is needed before getting the advanced analytics in place.

To help my clients with this struggle and to make sure that efforts to improve data management as basic capability I focus first on the direct value delivering data aspects by using a Data Heatmap based on DAMA. This heatmap per business area gives insight in people, process and technology related capabilities. So the result of the focus is make optimal use of scarce resources.

Data Governance 2019 Round-Up

Happy new year!  I hope you are rested and ready to continue implementing Data Governance in your organisations.  I find that the new year brings about renewed energy. At this time of year I am always enthusiastically consuming and reviewing content that will help me do a better job in the coming months.  I know I am not unusual in this and it is amazing the number of Data Governance initiatives that are started or re-launched at the beginning of a new year.

In case you are like me, I thought it would be useful to share a round-up of my most popular blogs from 2019. There may be one that you missed, or perhaps one of these may be particularly relevant for you to revisit:

1. What is the Difference Between Policies and Standards?

2. Data Owners and Data Stewards - What is the difference?

3. Why Data Governance Can Be Overwhelming

4. What's the difference between Data Owners and Data Custodians?

5. Why are there so many different Data Governance definitions?

6. Free Checklist To Support Successful Data Governance

7. What do you include in Data Quality Issue Log?

8. What is the impact of a poor data culture?

9. Why is a Data Governance Business Case Hard to Get Approved?

10. Do You Need To Prioritise Your Data?

I hope at least one of these is useful to you at this point in time. 

If you have a topic that you would like me to cover in future blogs please let me know.

If you need a deeper dive into a structured approached to design and implement a Data Governance Framework successfully, don’t forget that I offer both face to face and online training.  You can find out more about these on my website here: https://www.nicolaaskham.com/data-governance-training/  

There is currently a 20% early bird discount available on my next public course in London in March available, but only for a couple of weeks!

If you want to have a chat about your Data Governance Training requirements why not book a call by using the button below?

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Why Data Governance Can Be Overwhelming

Lots of people who come on my training courses say that they are feeling overwhelmed by the sheer magnitude of what they've got themselves into, and are confused by where to start their Data Governance initiative or (if they have already started) what to do next.

To be honest, that’s exactly how I felt when I was first starting out in data governance. I used to compare it to juggling.  Many years ago, before I discovered data, the Bank I worked for sent me on a leadership course. On that course, they taught us to juggle.  Some people found it just clicked and they were amazing at it, but I found it incredibly difficult.

However, at the end of a five day residential course, I did manage to successfully juggle three balls (for a short period of time). Other people on the course managed more than three balls, but we each discovered our limit of how many balls we could keep in the air at any one time.

When I first started out in Data Governance, I  felt the same. There is so much that you have to think about when you're doing data governance, that it can feel just like you are juggling.  There are too many balls for us to keep in the air at any one time.  I came to the conclusion that you can't do everything at the same time. More importantly, I worked out that you shouldn't be doing them all at once anyway. That might be good news, but where lots of people struggle is knowing which activities you do need to do and in what order.  

When I was working on my methodology I noticed that you need to do certain things in the same order for your initiative to be successful. Having said that, there's also a number of other things that will vary depending on your organisation and exactly what you're trying to do.  

The juggling analogy has stayed with me because when I had a video made to promote my online training course last year, the juggling balls came to mind. You can see that video here if you're interested.  

My methodology takes you through everything you need to consider and do in the right order. But that doesn't mean that Data Governance isn't without its challenges. There are many challenges and the biggest one is the culture change you need to instigate. At the moment, most people in your organisation probably aren't thinking about data being part of their job at all. To be successful at data governance, you need everybody in your organisation to start thinking about the data they're creating or using, worrying about the quality of it and whether they should be using it for the purposes they are.

That's a big challenge on its own and there are lots of activities, communications and training that you're going to need to do to affect the culture change you require.

A second challenge I frequently see is that data is not a top priority. Perhaps you are lucky enough to work for an organisation that is focussing on “becoming a data-driven organisation” or is embarking on a digital transformation.  This sounds great as clearly your organisation is finally interested in data, right?  Sadly most people focus on the exciting outcomes and don’t understand that their data needs to be well understood and of good enough quality to facilitate these lofty ambitions.  If this is the situation you are facing, it will take a lot of effort to convince your stakeholders that they need to implement Data Governance first so that such initiatives can be successful.

You've got to make the case for data governance before you can even start designing and implementing a framework (as I've mentioned many times in the past, there is no such thing as a standard data governance framework!) 

When you do get approval to start, there is a lot of work to figure out a framework that will suit your organisation’s structure and culture and once you’ve done that you're going to need to do an awful lot of stakeholder management.   

You need to engage your stakeholders, identify and train Data Owners and Data Stewards. You are going to need a detailed communications and training plan.  I often say that you cannot do too much communication about data governance because you are trying to affect the culture change that I mentioned earlier. These communications need to be good quality, well written targeted communications and briefings. This in itself is a mammoth task.  

So having considered all of this it's no big surprise that a lot of people get overwhelmed with data governance and just don't even know where to start.

That's one of the reasons I started offering data governance training five years ago.

I went through the pain of my first few data governance initiatives before I worked out my methodology. I realised that I could help people avoid some of the pitfalls and the pain that I had gone through by sharing my methodology and that's exactly what my training course does. I take you through stage by stage what you need to do and in what order. I also share skills, tips and techniques to make you more successful. 

What is more all attendees of my training course (both in-person and online) get a copy of the actual checklist I use when implementing data governance for my clients.  So they really don't need to feel like they're juggling.

My next public course is in London next March and if you book before the end of January there is an early bird discount available.

If you want to make 2020 a great year for your Data Governance initiative, why not come along (and if you’ve got unused training budget, why not book before the year-end to make sure your budget doesn’t get forfeited).

If you have any questions about the course and whether it is right for you please feel free to schedule a call with me using the button below:

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Rupal Sumaria - Data Governance Interview

I am really pleased that one of my clients has kindly agreed to share what it is like being new into a Data Governance role. Rupal recently changed roles from Business Intelligence Support Manager to Data Governance and Analysis Manager at Penguin Random House UK. In her role as BI Support Manager, she saw first-hand how Data Governance impacts Data Quality and focused her efforts on fixing issues, improving the process and wherever possible educating users on data rules. In her new position, Rupal will now focus on embedding good data culture and sharing existing best practices in Data Management and Quality across Penguin Random House UK.

 How long have you been working in Data Governance?

 I’m very new to Data Governance, taking on the role officially only a month ago!

 How did you get into this area of work?

My boss Pete Williams, Director of Data and Online at Penguin Random House convinced me! He pitched Data Governance to me (warts and all) and I was sold. I’m still figuring out my role, and being able to set my own direction and path is very exciting.

What is driving your org to invest in this?

The publishing and media industries are undergoing huge changes as they respond to changing consumer behaviours, growth in our digital presence and new data-savvy competitors like Netflix and Amazon Prime as we compete for consumers’ leisure time.

In order to grow our business and ensure we are as data-savvy as our competitors, it is vital we maintain clean data and embed a framework that supports our future.

 Why is data governance important to you?

Data is created, stored and used in every aspect of the publishing business, but data concepts can feel really abstract in a highly creative industry. As a result, we need to empower and engage users to have honest and open discussions about data.

Part of data governance is to change the mindset that data quality, management or storage is solely a technology problem, as data issues affect decision making across the board. It’s exciting to lead conversations about Data Governance and hopefully make an impact on the business.

 What tips have you been given so far?

The top tips I have been given are:

1.    Create a strong business case that aligns to your business strategic goals so that Data Governance resonates with your senior leaders and they support the initiative.

2.    Don’t shy away from challenging areas that think they have perfect data.

3.    Don’t focus on what you call Data Governance; it’s the practice, people and process that are important.

4.    Don’t worry about who takes on what role, i.e. Data Owners, Stewards, etc. It is more important to have a process that allows for Data Quality Issue Resolution.

and were they useful?

 The advice is all very sound and simple but harder than it seems!

 1.    The business case proved to be the easiest of the tasks as we were very prepared and our senior leaders responded positively to the initiative.

2.    It can feel quite intimidating working with senior leaders but luckily Penguin Random House leaders are very friendly, understanding and patient.

3.    The Governance term felt very heavy-handed and as our business is very focused on the power of words, we changed the name to Data Management and Quality.

4.    This has been the most challenging, we very quickly got caught up on trying to assign roles without really taking stock of our Data Domains. We are now working to re-focus on the process, making sure to give everyone the support and resources they need for their roles.

 What tips would you give to someone at the same stage?

 Data Governance can be daunting. Talk to people that already work in Data Governance to seek advice and make sure you have a sponsor from your leadership team.

Also, don’t underestimate how much time you might spend organising people into workshops and arranging meetings to get Data Governance off the ground.

How Long Will My Data Governance Initiative Take?

In this blog, I want to answer a question that I am asked several times every week. To be honest, it’s not an unreasonable question, but it’s not an easy one to answer!

Before I go into any detail trying to answer the question, I want to make one thing very clear: there is no end date on Data Governance.

Data Governance should be something that you are implementing and embedding within your organisation, so that it becomes part of business as usual. For this reason, as anyone who has worked with me or attended my training courses will know, I make a point of impressing upon everyone that Data Governance is NOT a project. If you truly embed Data Governance into your organisation it should never end.

However, having said that, it is entirely possible that you may want to do a project (or project-like initiative) in order to design and implement a Data Governance Framework in the first place. So perhaps the question should be “how long will it take to design and implement a data governance framework and start delivering some benefits?”

But to be honest, that questions isn’t any easier to answer and you could say that both are “how long is a piece of string” questions. Last year, I was lucky enough to be on a panel debate at Data2020 in Stockholm with David Dadoun from Aldo and Andrew Joss from Informatica. Whenever I participate in a panel debate, I always start with a sense of trepidation as to whether my fellow panelists will have the same views as me or not. In this case I did not have to worry because both David and Andrew were very experienced in Data Governance and had seen many of the same challenges that I had over the years. This meant that we all agreed that there is no such thing as a standard Data Governance Framework or a standard approach to implement it. It also meant that— much to the frustration of the Chairman— we took it in turns to answer many of the questions with “it depends.” The panel debate was filmed and you can watch it here if you’re interested.

The reason I tell you this is that whenever I am asked this question, I am always tempted to respond with “it depends.” However, this would not be useful for the person asking the question, so instead, I have to follow up with some supplementary questions. These will include things like:

• Do you have an agreement to commence a Data governance initiative?

• How many resources have you got to work on the initiative?

• What is the scope of your initiative?

• How big is your organisation?

• How open to change is your organisation?

And depending on the answers to the above, I may well ask “is your organisation ready for Data Governance?” Please note this final question is not the same as “does your organisation need data governance?”

Back in 2014, the Data Governance guru Gwen Thomas (founder of the Data Governance Institute) wrote a fantastic article called “When You’re Not Ready for Data Governance.” I frequently direct people to have a look at this post to help get their head around whether now really is the right time for them to commence Data Governance, because sometimes you just have to accept that now is not the right time.

So having asked the first round of supplementary questions (detailed above), if I am convinced that an organisation is ready and able to commence designing and implementing Data Governance, then I need to answer further questions. These are around what they are aiming for and where they are starting from. To help answer these questions, a lot of companies turn to a data governance maturity assessment of some kind. These are very valuable tools in helping an organisation decide how mature they need to be, and in identifying where they currently are.

Please be aware that sometimes organisations can get tied up in “analysis paralysis” and spend inordinate amounts of time and effort on completing a maturity assessment. This is not useful, and care should be taken to only go to the level of detail needed to understand what capabilities your company is hoping to attain, plus identifying its current state.

There are multiple different maturity assessments available. As with all things Data Governance  I prefer a simple approach and you can download a very quick and easy Data Governance Health check questionnaire for free here. If a more detailed assessment suits the culture of your organisation better, I recommend you look at the freely available maturity assessment published by Stanford University. Sadly they recently removed their assessment from their website, but Alex Leigh has created an excel spreadsheet version that you can download from his website.

It is only after you have gone through the analysis outlined above that you will be in a position to estimate how long implementing Data Governance is going to take in your organisation. Now clearly the timescales are going to vary, but in my experience, it is going to take you the best part of a year (and probably longer) to design and implement a Data Governance Framework over at least some part of your data or organisation. This doesn’t mean that you won’t be able to deliver some quick wins during this period, but it will take a reasonable amount of time and effort before your Data Governance Framework starts to deliver value on a regular basis.

I don’t say this to put you off starting in the first place, but I have seen so many people underestimate the amount of effort and time that a Data Governance initiative takes, and it is vital that you manage your stakeholder’s expectations from the outset.

So whilst I can’t give you an easy answer that works for everyone, I hope I’ve given you some insight into how to work out the answer for yourself.

What is the impact of a poor data culture?

In this blog, I want to look at how a poor data culture can impact on staff in your organisation. Most of the articles I write focus on what you need to do to implement data governance, but I had such a great response to my post on why the data governance business case is so hard to get approved, that I thought it was worth delving a little bit more into the topic of poor data culture.  This could also be described as a lack of data literacy in your organisation.

All too often I come across organisations who have a very poor data culture. By that, I mean, that they don't really think about data at all. I see this improving all the time but awareness levels are still low.  Some industries (those where they make, move and sell things) I can understand that perhaps the focus is on the thing that is being made, moved or sold and less about the data around these processes.  However, for many service industries like financial services the products aren't tangible. The products don't exist in the real world, they are only data and yet many such organisations still suffer from a poor data culture.

It's absolutely vital that we get everyone in our organisations, whatever sector we work in, to start thinking about data, and the impact that poor data is having on our organisation. So in this blog I want to consider the impact a little more.

In my last blog, I advised you to look for your data quality issues. Maybe you found examples of where poor data quality has caused a loss.  Identifying a measurable cost to your organisation is fantastic, but if you found examples of poor data culture how are you going to measure that?  To be honest, it’s not something that often gets mentioned in a business case.

I can't tell you how many times over the years I've had people tell me that part of their job is to fix and cleanse data. I can think of one instance in particular when a student actuary was spending two weeks every quarter, cleansing and fixing a spreadsheet before it could be loaded into one of their complicated actuarial models.

I was aghast that he was wasting eight weeks every year fixing data in a spreadsheet. This person had been doing the role for 18 months and had been told that this cleansing and fixing the data in the spreadsheet was part of the process that had to be followed!  Actuaries are very intelligent and possess impressive analytical and statistical skills. Do you think it's good value for them to be removing duplicates from spreadsheets or reformatting data in spreadsheets? I certainly don't.  

This is just one example but I think it's fair to say that there are probably intelligent individuals doing monotonous routine tasks like this in most organisations  What impact is this having? You have a company not able to fully benefit from these skills and added to that these individuals are going to get disenchanted with the role and be less productive or even worse may look to move to another organisation.

Sadly I see this on so many occasions across all sectors and business areas.  Where individuals tell you that there's no point telling you about their data quality issues, because they've been there forever and nobody is ever going to fix them.   This defeatist attitude not only creates a poor data culture, but soon impacts the culture of the whole of organisation.

Think how much more engaged and efficient your staff would be if they didn't have to fix broken data or poor quality data before they could do their ‘real job’.

I've come across loads of similar examples over the years, but I was keen to see if other people’s experiences were similar.  I asked for input on LinkedIn earlier this month and had some great responses.

Obviously, this blog has to be a digestible length so I'm not able to include all of the examples but I wanted to share with you some of the impacts on culture that were disclosed.  Don't forget to keep reading to the end because I've saved the best/worst one for last!

Many examples raised the common issue of a culture of tactical or short term fixes that create data issues and build or reinforce data silos.  This means that organisations are then not able to take advantage of new technologies to use that data, some people shared examples of investment having been made in Artificial Intelligence or Machine Learning Tools to then find that the data wasn’t good enough to use them.

One example mentioned the care sector, one with a heavy dependency on people but which doesn’t take the time to train them in the importance of data.  This results in well intentioned people but poor quality and poorly managed data.  The management then can’t rely on that data so seek workarounds, perpetuating the poor data culture, increasing inefficiencies and increasing staff turnover.

And the final example is a sad but excellent example of what can happen if you neglect your data culture.  Someone shared that a 3 year regulatory reporting project involving approximately 100 people and significant investment in technology had failed because of a lack of data culture.  Data analysis and data quality had been de-scoped from the project and the end solution would not work because of poor data quality.  The person described the situation as like trying to make a chocolate cake without any chocolate – an excellent analogy.  This culture took its toll and the individual concerned ended up resigning taking their valuable skills to another organisation.

Please take these examples as a useful warning.  It does not have to be this way, if you get it right a good data culture will empower your organisation to see data as an asset and managing data as an asset will enable you to use data to focus on and deliver value.

One of the respondents, to my request for input to this article, summed up the situation nicely:

Leaders need to work to create an environment that is conducive to a behavioural shift and that is what a good data culture does. It is the foundation of successful change.

Helping you improve the data culture at your organisation is a key part of the Data Governance Journey that Alex Leigh and I have created together, you can find out more about that here.

Why is a Data Governance Business Case Hard to Get Approved?

When I'm running training courses, one of the early topics we cover in the day is the various challenges of implementing data governance, but to be quite honest, the challenges start long before you even start designing and implementing your data governance framework.

It can be a real struggle to get your data governance initiative approved in the first place. So I wanted to have a look at the reasons why this might be the case so that you can both plan for and mitigate them.

I think the challenges span four main themes:

·      data governance is rarely considered a top priority

·      it is hard to measure the value of data governance

·      it is hard to measure the success of your data governance initiative

·      your organisation may be successful in spite of its data

So let's have a little look at each of these in turn.

Data is not a top priority

This has been a common issue for many years, although the more recent focus on data and the drive for organisations to become “data-driven” has meant that this is getting slightly easier. But, be warned, it comes at a price as many senior executives hear about the “cool” data initiatives such as AI and Big Data Analytics and they want those without putting in place the data foundations (i.e. Data Governance) that enable such initiatives to be successful. 

 In order to overcome this, you need to sell Data Governance in terms of the outcomes it will deliver, and you need to tie those outcomes to the things that are a priority for your organisation (a good place to look for these is in your corporate strategy).

It's hard to measure the value of data governance

The problem is a lot of the benefits which Data Governance will deliver can't be measured in advance. They are intangible.  You could say that you will protect the company from things like reputational damage or investigation and censure by regulators, but your stakeholders could respond with something like: “We've never had data governance before and have not faced those particular issues”.

However, I think it's fair to say that every organisation I have helped implement data governance has achieved significant cost savings.  Most organisations experience many inefficiencies as a result of data not being available or accurate.  Alex Leigh (a fellow consultant I often work with) always says that these inefficiencies cause a lot of organisations to be “data fix factories”. 

Reducing inefficiencies is just one cause of an increase in profits after implementing Data Governance.  Many of my clients report that they've been able to better identify new opportunities or provide better customer service because the quality of their data is better.

These are good examples of where data governance has helped find and resolve issues.  The trouble is that you don’t find and resolve them until you have put Data Governance in place. At the time you are asking for your business case to be signed off, it feels a bit like you're gazing into a crystal ball. You don't know what the issues are that you are going to solve.

My advice in these circumstances is to go on a hunt for your data quality horror stories. Try to get some examples of real things that have gone wrong in your organisation and cost money.  Without having some real concrete examples, you are building a business case based on an unquantifiable value that may be delivered at some point in the future!

It is hard to measure the success of your data governance initiative

This is very similar to the point above because if your potential future benefits are unknown it is hard to agree on indicators to measure the success of your initiative.  You will undoubtedly make cost savings and increase profits, but if you don’t know where these will be, you also don’t know what to monitor at the time you are writing the business case.

Using the data quality horror stories mentioned in the previous section will help you articulate where you will be looking to measure success. Another area to consider is new systems. If your organisation will be implementing or designing a new system, you will not have to spend a significant amount of effort and analysis of data (as was likely the case). Data will be well documented and its quality understood in advance of the project. So try to get evidence of how much effort this has taken on previous projects.

Sadly there is no easy way to answer this is advance - you are in effect waiting for things to go wrong so that you can fix them.

Your organisation may be successful in spite of its data

Finally, an issue I've seen a number of times.  If your organisation is successful in spite of a lack of understanding and control of their data, it is hard for senior stakeholders to understand why they should invest in Data Governance, especially if there is no regulatory requirement for your industry to do so.

In this case, my advice is the same as point 2 – you need to find your data quality horror stories to provide evidence that poor data quality is having an impact on your organisation.

I don't want you to think that it's all doom and gloom. Creating a successful business case for data governance is possible, but I want you to go into it with your eyes open and aware of the challenges facing you. Having help from someone who has done it before, is a great way to make your business case more successful.

Alex Leigh and I have been working together for the past couple of years and because we have complementary skills (and like working together!) we have decided to formalise some joint product offerings. Helping you develop a successful business case is the first service that we are pleased to launch.  You can find out more about it here or get in contact if you would like to discuss it with us.