Data Governance Interview with Rob Saundby

I have been working in IT for over twenty years, of which the last ten have been specialising in data management. During this time, I have been lucky enough to have worked across a wide range of industry sectors including banking, insurance, telecoms, media and retail. Because most of my engagements were through a consultancy, there has always been a strong focus on client delivery and, working with many different organisations, I have realized that data management is fundamentally quite similar, regardless of the industry sector. I setup my company Rockit Solutions in 2018 to specialise in data management.

How long have you been working in Data Governance?

Having worked in IT for several years, I always saw data as an integral part of designing and building systems to support business operations. Although it wasn’t called data governance then, the basic principle of needing quality, trusted data was always there. Back in 2010 when we first worked together, it was new ground working with data owners and data stewards and running a data governance forum. From 2014, I started to specialise in data management in financial services for a capital markets consultancy based in the City.

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

For me, this is a natural intersection of where technology and business meet. I think I have always viewed data governance through a lens of how it can be implemented, so a more practical rather than theoretical perspective. Working in the banking sector, I saw many parallels with the risk-based controls approach that financial organisations take, but for data, rather than other assets.

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

Over the years I have worked in most aspects of data management including; data governance, data architecture, data quality and have been interested in some of the more niche areas such as data cataloguing and data lineage. As a generalist I enjoy describing the big picture and have found that this is something that I can bring to the table for clients I have worked with.

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

I would recommend Data Governance 2nd Ed by John Ladley as an excellent book on the subject and for up-to-date discussions, I find LinkedIn very useful for the latest blogs and information.

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

The most consistent challenge is sponsorship. Having sustained, executive sponsorship for improving data in an organisation is the single most important factor for effective data governance. Without it, a number of things can happen; it can be a real struggle to gain stakeholder engagement and buy-in, reduced funding and team resources, lack of adoption, lack of appropriate tooling, no improvement in data literacy, in adequate training and education.

You have made Data Catalogue’s your niche – what led to this?

Although the people and process slide of data governance is clearly challenging in many organisations I think that the next step, of actually cataloguing data assets, measuring data quality and delivering tangible business value, you could call this “implementing data governance” is even less well understood. I would argue that understanding data is key to governing it, and so the process of understanding it, using a data catalogue tool is an important part of the process.

Why are Data Catalogue’s so useful for organisations?

There are a number of reasons why data catalogues adds value to a data governance initiative. First, they provide a single place to go to, to find out about data – where it is, what it means and who owns it. Of course, you could say that this can be done in Excel, but modern data catalogues provide different ways of visualising the information making them much more effective. Second, they can link related information such as owners, applications, processes and policies, in a way that provides context, which makes them very useful when deciding how to use data. Third, they can make use of scanners and classifiers, to make sense of databases and filesystems, much quicker than can be done by hand. This makes them very useful for dealing with the complexity and size of many modern enterprises.

What single piece of advice would you give someone looking to buy a Data Catalogue tool?

With so many different tools on the market, I would say be clear what you want a data catalogue to do. For example, if you want a technical solution to scan your entire estate’s data assets, you may choose a different tool to one that will be primarily be used to manage data steward activities and escalations.

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

One example is an organisation who embarked on a lengthy process to procure a data governance tool. The long and short of it, is that after detailed requirements were drawn up, tools evaluated and trialed, and feedback given from key stakeholders the best solution was found to be – an Excel spreadsheet business glossary published on their intranet. As it turned out, the company simply needed to start with a very basic approach that added business value from day one.

Data Literacy: So What?

A few months ago I was approached by Nicola to discuss the topic of Data Literacy as a series of thoughts around how there might be an opportunity to provide some training on the subject; as a result of that discussion Nicola asked me to write this blog to provide some insight.

The topic of data literacy seems to swirling around organisations at the moment and the push is to see how data literate they are and how they can get training to understand that. Now, I have been around data for a long time, over 20 years in fact, and I consider myself to be data literate; that said it doesn’t mean that I’m brilliant at all aspects of data.

The chances are that if you’re reading this blog then you’re either wondering what data literacy is all about, or you’re trying to find out more about training or assessment for your organisation.

I could tell you to just look around and see how it looks? I could just say well you could ask people how literate they feel? I could say many things but that doesn’t really answer the question particularly if you’re not overly sure what data literacy really is.

If that’s the case then read on, because I will provide you with a little insight into what data literacy is and how it might be of help to you!

My belief is that all organisations need to have a good level of data literacy in order to function efficiently, perhaps be more competitive or simply more effective; to do this you need to know that data literacy is neither a quick fix nor some kind of silver bullet; data literacy is a feeling, an understanding or part of your culture.  Typically its made up of three key areas:

The other thing we need to understand about data literacy is that for the majority of the time, it’s about people and there comes the challenge!

Adopting data literacy could be a major change in an organisation, you need to understand what it’s about and determine how literate you feel your organisation is.

Then having achieved that you will need to understand about how you can make use of the information that you’ve gathered and you would, most likely, consider analytics as a way of achieving that; by using analytics we could ascertain the quality of the data we use and then determine which areas are not quite as literate as we had thought.

After that, having determined what and how we need to take that all important step and make the changes that we need to ensure that literacy is taken on board in the business and that we have a method of maintaining the level that we need.

Don’t forget though that data literacy will be different at all levels of the business, some more distant from the actual work such as senior stakeholders may need less literacy around the data and more around the outputs that they request in reports from the analytics function. In this case you have to understand all the facets of the business, what they need and where they currently are.

Also don’t think that just because you say it’s a good thing, that people will just agree because they most likely will ask a whole lot of questions about how you know that. Don’t forget that attaining widespread data literacy comes at a cost. People will need to be trained to make sure they are as data literate as they need to be and that takes time. Finally don’t forget that although increasing the level of data literacy will undoubtedly deliver benefits, those benefits tend to intangible and undefined at the start of the initiative and if you’ve been around change programmes before you’ll know how difficult they are to drive through.

“It is clear that if you have a data literate organisation, you will be able to tell the difference just by how much more efficient it feels and the quality and speed of decisions you’re able to take.”

So the drive for data literacy is very good news and businesses should strive to achieve it. After all if we can all be more data literate and more careful about what we do when handling data then we can achieve more, quicker, with less friction and generally have a better experiences.

Data literacy doesn’t bring that on its own, however if you bring it into the mix of your organisation then you are taking one small step to being more effective and efficient and why wouldn’t you want that!

If you would like to find out more about data literacy training, then use the button below to arrange a call with Nicola to see how data literacy training might benefit your organisation.

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Written by Justin York - Justin is a Senior Data Governance Coach Associate, and is a performance innovation coach at Rubicon Coaching. He has over 25 years' experience in management positions in the military, and as a management consultant. He uses tools from coaching and consulting to bring change in both individual and team behaviours, as well organisational culture.

The Rocky Horror Data Show: Disastrous data definitions…

Data shouldn’t be a wild and untamed thing, but sometimes it is just that - wild… and untamed. And unfortunately for our friend Tim, he’s about to find out just how wild and untamed data can be. As this is ‘The Rocky Data Horror Show’… where the data is not what it seems.

Episode 4 - if you missed the previous episodes, you can read them here:

The Rocky Horror Data Show - where the data is not what it seems

The Rocky Horror Data Show: Did you get what you asked for?

The Rocky Horror Data Show: Not everyone’s on board…

Things at the Magical Wish Factory are still tough for Tim. He’s starting to make headway with senior stakeholders and they’re beginning to buy into the data governance initiative. However, progress is still slow because some of the definitions he’s receiving are not up to scratch. In some cases, he’s having to send them back two and three times before they’re suitable enough to be included in the glossary.

So far, he’s had definitions back that use acronyms to explain acronyms and department specific terminologies along with spelling and grammar mistakes galore!

Janet, the Head of IT, is wondering why they can’t just use a list of standard definitions to speed up the process or use the glossary from Tim’s old job.

Tim explains to Janet: “This isn’t part of the process that can be skipped or glossed over, so to speak. Part of the reason for this is that organisations, even those within the same industry, very rarely use the same terminologies in exactly the same way.

“This means there is no bank of standard definitions to pick and choose from; what works for one organisation will very rarely work for the next.”

Tim decides he’s going to send out a list of hints and tips to help people write the best possible definitions.

“But why does it matter so much?” asks Janet.

Tim goes on: “If it is not carefully crafted, the glossary can quickly become an unstructured dumping ground, ironically reflecting the reason the organisation needed one in the first place.”

Tim sends round a memo explaining that a good definition should be unique and distinguishable from other definitions and be written as a descriptive phrase or sentence.

Tim also advises that restating the words of the term in a different order is not sufficient and asks people to avoid using acronyms or other abbreviations as these could cause confusion. His advice is to state what the concept is - not what it is not and to be clear, concise, and unambiguous.

Tim also decides to work with the teams involved in creating the definitions for the most problematic terms.

He works to identify stakeholders who are willing to act as owners of the terms and others who are willing to articulate the term. Tim encourages stakeholders to be rigorous with their definitions and the information they keep on the terms.

Tim explains that a definition can’t just read: ‘Customer Type - the type of customer’. This isn’t a good definition because it tells us 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.

Part of this process for Tim is also making sure that both senior and junior people in the Magical Wish Factory have a part to play. Senior people will be accountable for terms and will need to review and approve definitions and junior people tend to be more involved on a day-to-day basis, so they often know more about the issues.

There needs to be collaboration between the two to set up through the glossary in which the junior people begin articulating terms and the senior people review and approve.

Tim is hopeful that with this advice and by working with stakeholders on the most problematic terms that the Magical Wish Factory will be well on its way to creating an excellent glossary…

Stay tuned for episode five of The Data Governance Coach’s new series ‘The Rocky Horror Data Show’ and follow the adventures of Tim and Janet as they try to implement a successful data governance initiative at the Magical Wish Factory.

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

Do you know what is in a Data Governance Framework?

If you are reading this blog, then there is a very high chance that at some point in the not-too-distant past you have googled the term ‘data governance framework’. Not only that, but you’ve also probably also had a whole myriad of answers come back. Some of which probably make it look really, really complicated.

A data governance framework is something that you can make as complicated as you want to but from my experience it really needs to be as simple as it can be. I advocate for simplicity when doing data governance above all else, and if you watch any of my videos or blogs then you’ll already know that. In fact it is one of the key principles for successful Data Governance which you can read about by clicking here. Now, that doesn't mean you can't go back and add more detail when necessary but start simple and build on that as and when you need to.

That doesn’t answer the question at hand though, does it? So, what does a data governance framework consists of?

Well, for me the only way to be successful with data governance is to first work out why your organisation needs data governance, and then to design and implement a framework that meets those needs.

 When I'm designing a data governance framework, I make sure that it has three key things in it: a policy, processes and roles and responsibilities. And these will almost certainly differ from organisation to organisation.

Let’s start with the policy. I've seen many examples where people have spent a lot of time and effort researching data governance, what they think they ought to have in their framework and dumping everything they found in their data governance policy. This ends up giving you a policy that is really long… some I've seen like small novels! And to be fair, I may have written some that length in the early days too.

But when you come to share them with any stakeholders, particularly senior ones, they're going to be completely put off by the sheer level of detail. That scares people off, and you won't get your senior stakeholders approving your approach. You may even impact the success of your Data Governance initiative at that point.

The other thing that I frequently see is people thinking they can fast track this part of a data governance initiative by copying somebody else's policy and framework. So, they look on Google or they ask a friend who's doing a similar job at another organisation if they can have a copy of their policy.

I would really warn you against this because a policy should be written to reflect how your organisation wants to do Data Governance. Picking up somebody else's and just adapting and amending a few bits means that you haven’t got a policy that was written for your organisation. Therefore, it's extremely unlikely to be useful or relevant for your organisation. And again, more likely to put more people's backs up and damage your Data Governance initiative.

For a policy to be really useful (i.e.. help you implement Data Governance successfully) it needs to be written with your organisation in mind, and consider the following:

• What is the scope of your data governance programme?

• What is it that your organization is going to do to manage its data better?

• What roles and responsibilities are you going to have to manage your data better? 

• What kind of processes are you going to implement because of having data governance?

Now, the answers to these questions will not be the same for all companies and I can honestly say that every organisation I have ever worked with has been unique in its approach to data governance. I admit sometimes the differences are subtle, but for a policy to be valuable, these subtleties really do need to be addressed.

Next you should include some processes, because I find that if you don't tell people how to do it, they tend to do their own thing, or they don’t do it consistently, or they don't do it at all. So, we need some documented processes for people to follow so they know and understand what data governance is and what you want them to do.  Which processes you have will depend upon what benefits you are trying the achieve but should include a central process of investigating and resolving data quality issues.

And then finally, we need some roles and responsibilities because I'm sure you have been to the same meetings… you know the ones where everybody is in violent agreement that something needs to be done, everyone agrees on the actions and then we come back to the follow-up meeting… and everybody thought that somebody else was actually going to do that action.

Well, data governance is just like that. I can't tell you how many times I've told people

why I think that we ought to do data governance at that organisation and everybody agrees with me. Nobody ever says, “that stupid, we shouldn't do it”, they always agree that it should be done.

They might give me all sorts of reasons why it can't be done right now... because they're busy, they don't have the resource etc, but they don't say that it's the wrong thing to do. What is quite common is everybody thinks that somebody else is going to do it for them.

That is not the case - almost everyone has a role to play if you're implementing a data governance framework, and so your framework itself needs to detail those roles.

Ensure your roles and responsibilities are properly defined and you have found suitable people for each of these roles. There is no point in defining roles and responsibilities and then finding people to fill the roles if you don’t explain to them what you want them to do and how they should do it.

It sounds obvious but make sure to document your processes and provide adequate instruction so that everyone knows what they should be doing.

Don't forget if you have any questions you’d like covered in future videos or blogs please email me - questions@nicolaaskham.com.

Or you’d like to know more about how I can help you and your organisation then please book a call using the button below.

Data Governance Interview with Kim Woodward

Kim is a collaborative Data Governance leader specialising in the strategic design, delivery and implementation of global data management and governance practices in the Finance and Pharma sectors.  She has been involved in the design of enterprise data policies, maturity models and data governance operating frameworks and has led the technical and business implementation of data management technology such as reference, master and data quality solutions.

How long have you been working in Data Governance?

For about 10 years now.

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

It’s something I landed in!  Early in my life I was a data analyst where I always recognised the importance of high value data that’s easy to find; during my career any roles I was in I naturally focussed on the data aspect in order to have confidence in any processes or outputs I delivered.  One role in particular was in headcount management covering data of 8000FTEs… that’s a lot of people to count, and they rarely sit still!  It was this point where governance and oversight, together with the right framework was important so that no matter what the ask was for, e.g. headcount financials, perms vs contractors, number of seats in a building etc, I was always able to give the right number for the right use-case.  To get it right it needed data owners, system owners, data flow, lineage, definitions, data quality, etc… my introduction to a holistic data governance viewpoint.

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

Good question, you’ve got to be a little bit of a data geek and at minimum passionate about data – how you develop that is hard to articulate! 

For me it’s about collaboration, really understanding the end use-case and working closely with business stakeholders.  I wholeheartedly believe (and know) that data governance is an enabler to increase the value of data.  Business users, process owners, product owners, business decision makers, etc all need high value data to enable their deliverables to be trusted and drive the right business outcomes.  For example, why build a cool, real-time visualisation tool if the data in it is of poor quality or be unprotected when people gain access to it; people won’t buy into the product as they won’t trust how the tool is utilising data.  So strong characteristics of a Data Governance Leader needs to be one who collaborates, understands, listens in order to develop the right environments so that products or services can be used with full trust by its consumers.

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

To be honest, I’m very much a “learn on the job” type person so for those starting out I would recommend you build your networks, find data SMEs, ask to learn from them, and you will be educated with some great tips and stories along the way…

However if you like a big read then the Data Management Body of Knowledge, fondly known as the DMBOK… it’s like the bible of data!

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

Scalability and Stakeholder engagement.

Any framework needs to be scalable across the organisation; its not possible to do data governance well in silos, so influencing is critical to ensure that the model can operate effectively across functions.  For implementation your business stakeholders need to support the cause, it can’t be a way of working that is “put on them”, it just won’t work that way.  Finding engaging ways to bring them along the journey is essential, i.e. how you can bring value to their use-case.  The other critical point on scalability is having a good scope, you simply can’t do data governance across everything at once, so what data is most critical for the current business strategy, and start there… Start small and grow.

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

 A high-end clothing company to get a good staff discount.. 😉 I joke!!

On a serious note, I’ve always fancied getting close to people data (HR) and having good data governance over that.  The reason being is that people are an organisation’s greatest asset along side data.  I’m passionate about people, their health and wellbeing, their talent and development.  Having great data for great insights to help grow a high performing and talented workforce would be a great thing to be involved with and aligns to what I am passionate about.

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

Engage business stakeholders early; bring them along the journey with you by allowing them to provide input into the shape and design of the framework.  A collection of minds and hearts will grow the right framework for the organisation and generate buy-in along the way.

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

 There was a story about the after-party of a Global Data Governance conference… but that’s for another time!

The story I would like to share is remembering that it wasn’t that long ago when we didn’t have technology in day to day processes. I was visiting one of our country data governance representatives, and there had been some clearance of a storage room at a very old site of the organisation.  In it was a huge, old, leather-bound book of life policies, and it had hand-written customer information in it, but some customers would have still been alive today, very old but alive!  It was just a moment, remembering data is everywhere, in any form, the data in that book needed the same attention and protection as any data in any system.  The original source of data!

Five Common Data Governance Misconceptions

I’ve been doing data governance for a long time now. And it’s safe to say that time and time again, from organisation to organisation, I come across the same mistakes and misconceptions that are limiting organisation's chances of implementing data governance successfully.

But it doesn’t have to be this way - forewarned is forearmed after all! So let’s look at the five most common data misconceptions:

Number 1: Thinking there’s such a thing as a standard data governance framework

I’ve been asked many times over the years, ‘Where can I find a standard data governance framework?’ and, as with a lot of Data Governance questions, my answer is always the same… I don't even know whether one exists. I have never looked into it because I know from my many years of experience in Data Governance that they won't work.

If you think about it, a standard Data Governance framework has been designed as a theoretical exercise.  It certainly wasn't designed for your organisation.  The only way to be successful with Data Governance is to first work out why your organisation needs Data Governance, and then to design and implement a framework that meets those needs.

I can (almost) guarantee that as any standard framework was not designed for you it is not going to meet your needs. It’ll very likely be too complex, too convoluted, and too focused on things that really aren't appropriate for your organisation.

And the cost to your organisation when your standard Data Governance framework inevitably fails to get the desired results could be huge.

It won't be well received, and you'll have to start again. And if you've already put people's backs up by making a mistake, it's going to be even harder to get them to buy into the right Data Governance framework at a later date. And let’s face it, it’s hard enough to get people excited about Data Governance in the first place…

You can read more about this here.

Number 2: Thinking data governance is a one-off project

This common mistake is easily made because it seems logical to treat the implementation of data governance like any other project. Getting stakeholder involvement is essential to successfully implementing a data governance initiative and getting their buy-in. However, this is not something that can be simplified to a list of tasks.

Once you get stakeholder buy-in, you are then faced with the even bigger challenge of changing attitudes, behaviours, and even the culture towards data. I hope you can see that this is going to take something a bit more sophisticated than conventional project management.

When a data governance initiative is led as a project, it appears that progress is being made as tasks get completed. However, nothing substantial will change until the people change. And to change behaviours, attitudes, and culture, you must win hearts and minds. This is almost always overlooked when the success of the initiative is measured by deliverables ticked off a checklist. A proper change management approach is what is needed.

Without getting the stakeholders on-board, you will struggle to integrate your data governance framework so that it becomes business-as-usual. Without stakeholder buy-in, the organisation will eventually resort back to their old ways and the data will suffer...

In short, the whole initiative will have been a complete waste of time and money, and subsequent attempts to re-implement data governance will be resisted by stakeholders as they will assume that it’s a waste of time.

Number 3: Thinking it can be done quickly

This follows on nicely from the last misconception… Implementing data governance will take a reasonable amount of time!

In fact, I’d go as far as to say it will take a very long time to implement it fully across your organisation and to be honest, you probably will never get to that stage because as your company or organisation evolves and changes, your data governance framework will also have to evolve and change to match your needs.

This is not a short sprint. I wouldn't even call it a marathon. This is just an ongoing activity that we will always have to be doing.

Number 4: Think you can DIY Data Governance based on internet advice

It's true. There's a lot of good advice on the internet on how to do data governance (I hope I've contributed to some of that myself) but I do urge you to be aware when you start googling Data Governance and ‘how to do it’.

There is a whole range of advice available ranging from the excellent and very practical, simple advice to very complicated and confusing, ambiguous advice… not to mention all the advice that is downright wrong!

And this wrong advice is usually the most dangerous because as you’ll find out as you embark on your journey there are a lot of terms and roles that can be easily confused if you’re not getting good advice.

For example, Data Protection (also known as Data Privacy) is often confused with data governance. It specifically revolves around the protection of personal information and although more recent Data Protection regulations, like GDPR, do have requirements that are more easily met if you have a Data Governance Framework in place, Data Governance is a separate discipline.

Likewise, Data Retention, which focuses on how long you should hold onto data before deleting it, is something which your Data Owners should be consulted on but is a fundamentally different discipline. And while these separate disciplines all carry value in their own right and can - and should - be aligned with your Data Governance framework, they are ultimately separate. 

Unfortunately, the confusion surrounding the links between these different areas can feed into the misconception of Data Governance as a sort of grand, big Brother-esque surveillance program designed to watch business users’ every move with their data.

This isn’t the case at all! Data Governance is actually more about getting your business users to care about their data and its quality.

 Number 5: Thinking you need to have a team of consultants to help you

Many people are put off implementing data governance because of this misconception and understandably so because this will be very expensive. And given what I've laid out in the previous point around the wide variety of advice that’s out there you can see why people might feel so overwhelmed that they endeavour to bring in someone who can take care of it all for them… but trust me, you can do this without bringing in an expensive team!

Now, don't get me wrong, I am a data governance consultant and I think that data governance consultants can add real value, but be careful… as I’ve said before, this not a project.

You do not want a team of consultants on site for months or even years doing this for you. When the budget runs out, they will walk out the door taking with them all the knowledge and network that they've built up over time.

If you need help, make sure that you work with the consultants in a way that helps you to implement data governance and ensures that you get the skills and knowledge you need to run and support your data governance initiative yourself.

 Next Steps

If you are just starting out in data governance, then this is a good place to start as it links to a number of blogs that will give you the basics:

• If you feel you need a bit more information why not come along to my next live online data governance training course on the 7th & 8th June.

• If you can’t make the date or the times don’t work for you, then you’re in luck as there is a pre-recorded online version also available.

• If you feel you know what data governance is but are still facing some challenges in your implementation, then why not join my next data governance mastermind.

Or if you feel that your needs are a little bit more complicated than that, why not book a call to discuss how I can help you.

The Rocky Horror Data Show: Not everyone’s on board…

Data shouldn’t be a wild and untamed thing, but sometimes it is just that - wild… and untamed. And unfortunately for our friend Tim, he’s about to find out just how wild and untamed data can be. As this is ‘The Rocky Data Horror Show’… where the data is not what it seems.

Episode 3 - if you missed the previous episodes you can read them here:

Episode 1 - The Rocky Horror Data Show - where the data is not what it seems

Episode 2 - The Rocky Horror Data Show: Did you get what you asked for?

Tim is settling in well at the Magical Wish Factory, and he is really enjoying working with and getting to know all his new colleagues. However, he’s still getting a lot of resistance when it comes to the thing he’s actually there to do - implement data governance!

Tim is facing two major issues - the first is just trying to build a decent data glossary, and the other is a little more serious… some senior stakeholders still don’t really understand why he’s there or why the Magical Wish Factory even needs data governance to begin with. In fact, some think it can just be done with the wave of a magic wand…

Unfortunately, the former seems to be a symptom of the latter. Despite Tim’s pleas, no one is putting any effort into their data definitions and Tim suspects its because he’s not got the buy-in of all the senior team. Their impassiveness is seeping down through the ranks - and no one is taking the initiative seriously.

Tim suspects that part of the reason for this is some senior stakeholders still don’t fully understand why data governance is so important and has been telling Janet, the head of IT, about his suspicions.

Tim explains: “Understanding why we are implementing data governance is crucial for several reasons, but most importantly everyone needs to know the ‘why’ in order to guide them through the data governance strategy and the change management adoption that we’re trying to put it place.

“Unfortunately, it’s not enough to just know that you should have data governance, it’s also important that everyone here at the Magical Wish Factory understands why we should have data governance. If not everyone understands and can relate to the ‘why’ then there is a risk that the whole initiative could come off the rails.

“You need everyone, particularly those who will be involved in the implementation of the data governance initiative, to buy into it for it to be a success. You cannot start to manage your data as an asset and realise the value of it if you don't address culture change and adopt a change management strategy early in the process.”

Tim tells Janet that in fact, just last week, the Chancellor asked him what exactly his role was and why they couldn’t just use the magic of Artificial Intelligence instead. This is particularly concerning because change management starts from the top - and if senior people aren’t on board then the people Tim is going to and asking for things like data definitions aren’t going to be on board either.

Tim knows that magic AI is only as good as the underlying data and that the magic needs quality data to learn from, or before long that’ll be a mess as well so he’s decided to sit down with the senior team and explain why: AI needs the right data in order to learn.

“So, as a consequence, if we've got missing or inaccurate data, our wrong and potentially inaccurate data can and will guide the magic AI in the wrong direction and it will make the wrong decisions and the consequences could be costly and maybe even disastrous.

“If we’re going to spend time and money integrating AI into the Magical Wish Factory, then I really feel quite strongly that if we want to reap the proper rewards of these brilliant magical technologies, we must implement data governance first so that we get the results we want.

“It’s quite simple: we need to make sure we've got our house in order before we start embarking on an AI and ML (magical/machine learning) journey.”

Now, as the senior stakeholders begin to understand better why the Magical Wish Factory needs data governance and get on board with the initiative it’s time to address the issue of those dodgy definitions…

 Stay tuned for episode four of The Data Governance Coach’s new series ‘The Rocky Horror Data Show’ and follow the adventures of Tim and Janet as they try to implement a successful data governance initiative at the Magical Wish Factory.

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

Helping Charities Do Data Governance

As you probably know I help organisations understand and manage their data better. Typically people turn to me because their data is a mess and they need help unravelling it or because they realise they are pouring cash into new initiatives that are failing because of poor quality data.

I have been designing and implementing Data Governance frameworks for almost two decades and have helped hundreds of organisations implement Data Governance, giving me a unique level of experience and insight into the typical challenges they face.

From my experience it is clear that a lot of organisations don’t value their data as an asset. As a result they don’t manage it correctly and this can lead to rising costs and inefficiencies and wrong decisions being made. This is not good news for any organisation, but is really bad news for a charity and the causes they are helping.

Having worked with a number of charities, it is clear to me that Data Governance can make such a difference and enable them to help more. Yet charities find it hard to justify the costs of getting training on how to do Data Governance.

A few years ago I started offering free places on my training courses to charities, because I feel it is important to give charities the skills to make sure that data is used to solve problems and make better informed decisions.

I am so passionate about the value that Data Governance can bring to the charity sector that I recently joined Pledge 1%.

My pledge is to offer a free place to a different charity organisation on every single one of my public Data Governance courses.

I want to be part of a world where everyone understands the value of data and uses it to make a positive impact. So I’m thrilled to be part of Pledge 1% and committing to supporting charities on their Data Governance journeys and truly harnessing the power of their data.

If you are a charity and would like a free place on my February Live Online Data Governance Training and Clinic - get in touch by emailing nicola@nicolaaskham.com

And if you’d like to know more about how I can help you and your organisation then please book a call using the button below.