The tale of Dick Whittington and the missing data

2020 has been an odd year to say the least, and as we approach the festive season it’s hard not to think about all the things we’ll miss out on this Christmas. One of those things being the traditional British pantomime.

 For those of you who have no idea what I’m talking about, a pantomime is a musical stage production which takes traditional fairy tales and retells them with larger-than-life characters, slapstick comedy, jokes, gags and a big baddie we can all boo at. They’re a staple of the British festive season that we won’t be able to enjoy this year.

 But, fear not, because today I have for you our very own pantomime tale - a data pantomime. So, sit back, relax and let me tell you all about our hero Dick Whittington…

 Once upon a time… there was a man called Dick Whittington. He was a humble man. Loyal, dependable and hard-working. Devoted to his wife and to his work. He was employed at the Dense Doughnut Bakery and loved it. One day, his boss, Mr Dense, tasked him with finding a way to improve customer experience within their organisation and this is where our story begins…

Our humble Dick set out on his journey to improve customer experience. Being the eager employee that he was - and desperate to please Mr Dense - Dick went looking for a magical and instant solution. He trawled and trawled the internet but was getting nowhere fast. Distracted, he decided he would start his Christmas shopping, and headed to eBay. There, he discovered a listing for a magic lamp which he thought his wife would love. And, not one to hang around, Dick clicked ‘buy it now’ and selected express shipping.

 When his magic lamp arrived, Dick polished it furiously and to his surprise out popped a Genie, who offered him three wishes.

 “Aha!” exclaimed Dick. “That is the answer to all my problems! I will use these wishes to improve customer experience at Dense Doughnuts and still have the lamp to give my wife for Christmas!”

 So, Dick set about making his first wish and he asked for lots of shiny new technology tools to help him manage his customer experience. Secondly, he wished for an instantaneous data migration from their old systems to put the data into his shiny new systems. And thirdly, he wished for a self-service portal, so that customers could access their own records and manage them themselves.

 These were good wishes, but the old saying is true ‘you get what you ask for’. It was a disaster. The Genie hadn’t thought about the data that was going into these tools. And why would he… he’s a magical Genie, not a data scientist!

 Dick couldn’t launch his online portal because the customer data was so very poor, and they didn't want their customers to know how bad it was - that would’ve had the opposite effect of improving customer experience!  Even worse, half the data they thought they had about their customers didn't appear in the shiny new tools.  So, Dick had to go on a hunt to find the missing data.

 He searched high and low, low and high shouting (and sometimes crying) out: “Data, data - where are you!” “It’s behind you” would be the loud and increasingly angry reply from a mysterious chorus of voices.

 “It’s behind you, it’s behind you… IT’S BEHIND YOU!”

 But every time Dick turned around… it was gone. Poor Dick Whittington was on a wild goose chase.

 Feeling lost and confused Dick cried out: “Oh, woe is me. If only there was one place I could go to see what data we have in this company and where I can find it. If only we had a catalogue of Data. That’s what I should have wished for.”

 After hours and hours of searching, Dick finally found some data that he thought might do the job. But, worried of repeating past mistakes - or using the wrong data and damaging customer experience rather than improving it, Dick wasn’t sure what to do. He shouted: “IS THIS DATA GOOD ENOUGH?!”

 “Oh, yes, it is!” shouted the mysterious chorus. Quickly followed by “Oh no, it isn’t!” This went on for another hour.

 “Oh, yes, it is!”

“Oh no, it isn’t!”

“Oh, yes, it is!”

“Oh no, it isn’t!”

 Poor Dick was more confused than ever. Sherry Trifle, the resident know it all spotted poor confused Dick and came over to see if she could help make sense of his predicament.

 She said: “Well if you're not sure, do you really dare use this data?”

 “But I’ve wasted hours searching and this is all I have to show for it - I have to do something!”

 “What if you find out that it’s really bad quality, or even worse that it's the wrong data and we make the wrong decisions on it?” replied Sherry.

 “If only there was some way I could know if the data was good enough to use” replied Dick.

 Sherry said she knew a guy who could help and introduced Dick to a wonky looking chap with a big basket of dirty data.

 “Hello! I’m Wishy Washy - pleased to meet you! That looks like a lot of data you have there. I could cleanse that for you if you like?” he offered.

 Dick wasn’t really sure if that was the right thing to do but he was running out of options and took Wishy-Washy up on his offer and followed him to the laundry.

 The laundry was full of hustle and bustle. It was noisy with machines spinning round and round cleansing data and making it ‘better’. Dick asked Wishy how they knew what they were doing and how they would figure out which parts of his data were good or bad.

 “I don't know - we just put it in the washing machines, and it comes out clean!” replied Wishy. Dick was worried. And he was right to be. When Dick got his data back it was definitely different. But he was still not convinced that it was right.

 It all got too much, and Dick sunk to the ground feeling hopeless and defeated, wondering why on earth Mr Dense chose him to take on this project to improve customer experience…

 That’s when suddenly POOF! In a big puff of sparkly fog Dick’s Data Fairy Godmother appeared! She explained to Dick that all the things he’d wished for from the Genie were wrong. BUT, all hope was not lost as the things he'd wished for during his journey (one place to document all the data and where it is held, a way of knowing how good, bad or otherwise the data was and finally a sensible way to fix bad data) were the wishes he should have asked for to begin with. And that he didn't need a Data Fairy Godmother or a Genie in a lamp to give him those wishes – he could simply start a Data Governance initiative!

 The END!

 Now you see, pantomimes can be fun to visit once a year but are a long, drawn out nightmare to live in. Don’t be like Dick and don’t make the wrong data wishes! Avoid working in a data pantomime, implement Data Governance and remember Data Governance is not a project - Data Governance is for life, not just for Christmas!

 If you need help getting started then I have a free Data Governance checklist, which will set you on the right path. You can download it here

 Merry Christmas!

Where Can I Find 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.

A data governance framework is a set of data rules, organisational role delegations and processes aimed at bringing everyone in your organisation onto the same page when implementing Data Governance.

So, while I believe that there is no such thing as a standard data governance framework, I do believe that there are three key things you have to include in your framework for it to be successful: a policy, processes and roles and responsibilities. And these will almost certainly differ from organisation to organisation.

A quick Google search will pull up dozens of templates, readily available for you to download - but you know that old phrase ‘there’s no such thing as a free meal?’ It applies here. 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.

So, if somebody tells you that they have a standard Data Governance framework that's the silver bullet, the easy way to put Data Governance in place, please promise me that you will run a mile. It is not worth the effort, because what you'll do is waste a lot of time and effort doing something that's wrong for your organisation.

There is no such thing as a successful standard Data Governance framework. And, I would encourage you to take the time and effort to work out what your organisation needs and implement a framework which reflects that.

So I don’t have a standard framework that you can use, but you can download my free checklist by clicking here which will take you through what you need to do to design and implement a Data Governance Framework that is right for your organisation.

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 Jason Hare

In this interview Jason Hare kindly shares his Data Governance experience. Jason is a former archaeologist and open data practitioner. He has been working in IT since the later 90’s. His interest in data governance stems from his time managing municipal open data programs in North Carolina.

How long have you been working in Data Governance?

In one capacity or another, I have been involved in data governance since the early 2000’s. I did not know back when I started that there was a whole discipline around governance and data management. I knew I had a data integrity and availability problem with a piece of software I was working on and so started thinking about how to solve that problem.

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

My whole IT career was more accidental than intentional. I started bagging and tagging artefacts. The idea that we could store data electronically and use metadata to describe the provenance of artefacts was how I became interested in information technology. Knowing what I did about social science, I was always thinking about the quality of the data coming from these information systems. Since about 2000 I stopped thinking I would go back to social science and made governing data my focus.

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

I follow my curiosity. That has made my professional life fulfilling to me. My curiosity seems to run towards how to make the lives of people better through making data better. What makes me successful, or at least successful to me, if a culture change approach to governance. People and process, the understanding of why data governance is important, that is what is most important to me. 

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

I enjoy reading and discussing data governance issues with Peter Aiken. I think he was the first person I met that had ‘data governance’ somewhere in his job title. I have also read a lot of what Kelle O'Neal, John Ladley, Christopher Bradley and of course you Nicola. I like learning from my customers as much as I like reading what others think about data governance. 

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

I am sure, like many of your readers, there are so many. The biggest type of challenge I face is convincing an organisation that repeating the same process over and over and expecting a different result is not going to work. That is true for just about anything but it seems to be especially pernicious about data governance engagements.

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

I have a fondness for the public sector and how smaller local governments can make better decisions around policies that affect real people. In the US, the local government has a bigger impact on individuals than the Federal Government does. The data with which local government makes decisions is often rife with bias. This may or may not be intentional. I would like to work in local government again.

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

Read the literature but be prepared to find that the literature does not often match reality. My biggest mistake starting out was trying to fit some situation into a framework. Rarely do real-world problems fit neatly into a framework. I also find keeping up with the legal side of what we do keeps me in step with how governance is changing and cross walking with information assurance.

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

I could but I might violate my non-disclosure agreements. Ask me about “biscuitgate” and I can share with you how a little creative data governance and open data worked together to solve a social issue with an online map.

You can find out more about Jason and connect with him on LinkedIn by clicking here.

Why is it So Hard to Write a Data Governance Policy?

Today's question is one that I have been asked many times over the years, and in particular more recently since my blog post on whether you need a Data Governance policy. You may remember in that piece I told you that you absolutely do need a Data Governance policy. Which, naturally begs the question "Why is it so hard to write a data governance policy?"

I think the main reason for this is that there are very few people out there that have ever written a Data Governance policy. And, if it is the first time you have ever written a Data Governance policy, that chances are, you just do not know where to start.

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 are 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 almost completely put off by the sheer level of detail. Of course, there is always a temptation to try and put too much into policies, but that scares people off, and you won't get your senior stakeholders signing it off. You may even impact the success of your Data Governance initiative at that point.

The other thing that I frequently see is people thinking that they can fast track this part of a Data Governance initiative by copying somebody else's policy. 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 actually haven't got a policy that was written for your organisation. Therefore, it's extremely unlikely to be useful or relevant to your organisation. And again, more likely to put more people's backs up and damage your Data Governance initiative.

In fact, sometimes I find myself writing a policy for my clients and they often assume that I will just take a previous policy I've written and tweak it for them. However, this really wouldn't be very helpful for the new client, as it wouldn't be designed to meet their needs!

And, as with all things data governance, I don't think that there is such a thing as a standard approach - there certainly is not one for a data governance policy. Think about it this way… if there is no such thing as a standard data governance framework, why would you think that a policy written for another organisation would work for you?

Unfortunately, a lot of people don’t realise this, and I’m often asked if I would share a template or an example for data governance policy that they can copy

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. You should consider the following:

• What is the scope of your data governance programme?

• What is it that your organisation 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 as a result 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. So, what's the answer? As I said, this is a question I've been asked so many times over the years, and I have been asked many times to write Data Governance policies for people, so I decided that this was something I really needed to help people with. So, I'm really pleased to announce that my latest course is ‘How to Write a Good Data Governance Policy’.

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 Lara Gureje

Lara Gureje (pronounced ‘gurej’) is the Founder & CEO of DatOculi LLC, a Data Governance & Stewardship Consultancy, Coaching & Training firm with its headquarters based in San Francisco.

Lara is a renowned Data Governance & Stewardship Advocate with passion for the heavily regulated industry. She is a seasoned Data Management veteran with over 20 years of experience, with 11 years experience working for the Big 5 consulting firms like Coopers & Lybrand, PWC and IBM. Lara has recently launched her own Consultancy offering where she helps organisations mature their data management practice whilst building successful cultural transformation, and fostering ethical use of data for competitive edge and insightful analytics. 

How long have you been working in Data Governance?

I’ve been working in Data Management for over 23 years in total and would say the last 6+ years is where I’ve primarily focused on Governance around data holistically. 

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

I actually consider myself lucky on this, for me and for those who have worked with me over the years as I journeyed through my career. Data Governance is a natural fit for my personality and my passion. I think I had stepped into the role long before they knew what to call it. I kicked off my career in Europe in software development & coding. That career did not last long before my strength for data management and analytics took centre stage and that was what opened the opportunity for me to be brought over to the USA by PWC at the time. 

I’m people-centric, with a great collaborative and community-building skill set. Working with people is very natural for me as I’m able to engage people quickly where they are and journey along with them, to where they desire to be. Data Governance is a people-centric discipline that fits very well into my personal DNA. To that effect, I was nominated into the role when the opening came up in my last company, after so many failed attempts of bringing someone in, to successfully champion the governance adoption.  

In a nutshell, Governance & Stewardship around Data has given me the rare opportunity to ‘make my vocation my vacation’.

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

I think for you to be successful at Data Governance, you obviously need to be tooled, trained and equipped well for success, this is very fundamental. However, there are some things that have to be part of your natural DNA to be successful in this discipline. I’ll call out a few that has worked for me over the years in my delivery:

• Coming from a position of pain is always a great asset for a Data Governance Leader and I can attest that this has helped me a lot. What I mean by that is that you need to be intimate with what poor data quality means and its impact on an organisation.

  People telling you the horror stories in their data is not good enough. I believe, having been at the receiving end of the lack of governance, that kept me up at night, positioned me to be a better stakeholder to champion a successful adoption. For example; my career journey, through the data management maturity and evolution over the years, started with development through Data Acquisition, Integration, Management, Analytics and Distribution. This career journey in hindsight definitely positioned me for Governance & Stewardship in a unique way than many. 

  The issues around missed opportunities and pains around data quality became very personal to me by the time I assumed full-time leadership in Data Governance.

• People skills and a great collaborative spirit is also a great asset I was able to tap into. I’ve often referred to this as a personality fit, to work for the United Nations to resolve global issues between nations with different ideologies from one another. Getting them to sign the peace accord and having this personality has to come from a deep place where its more of an art than a science.

• Rightfully messaging a good understanding that Governance is a journey and not a destination is also very important. Knowing how to start small with quick-wins and build upon success is always built into my framework. This always helps to set the right expectations and build workable building blocks for success in your deliveries. 

• Knowing to continuously build advocacy and woo community of allies to help accelerate Governance adoption journey is also something I like to build into my rhythm. Governance is a cultural transformation, the more allies to help evangelise your mission, the better it becomes and the quicker your organisation will start seeing the ROI.

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

Books are good to read, but I’m one of those that believe practical Governance is what we need to mature this discipline. There are lots of books out there and cookbook ideas, unfortunately, do not work for real-life governance. If you’re going to read a book, I'll recommend, picking up something that shares a case study of what success or failure looks like. No two Governance adoptions are exactly the same as the uniqueness of each organisation, their culture and goals which will drive what governance means to them. Hence, I advocate practical Governance, not something that looks good on paper and unrealistic for your setup. 

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

The biggest challenge I’ve seen in most governance adoption always revolves around the foundational gaps. i.e. poor understanding of what Governance is; lack or weakness of executive buy-in; internal politics; poor delivery expectations; lack or inadequacy of funding and poor leadership.

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

Any highly regulated industry that has invested heavily in regulatory compliance over the years, trying to leverage their investment in other initiatives, like MDM, GDPR and CCPA to pivot from compliance led data infrastructure to profit-led data infrastructure.

OR other organisations that are simply trying to drive their business growth through analytics (AI/ML). I’d like to help them position Governance around their input data to optimise ROI in their delivery.

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

• First and foremost, you have to be passionate about data & people.

• Don’t begin with tools - understand what Governance is all about. A tool is an enabler that has its place once you understand what governance is about. You’ll know where and when to engage the right fitness of tools as you go on.

• Get trained on Data Governance and Stewardship, find a coach or a mentor. 

• Follow thought leaderships and read case studies of governance implementations.

• Attend 1 or 2 yearly conferences to keep up-to-date with trends.

• Be patient with yourself.

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

Not sure if I’ll call it humorous somewhat, but I’ve often found it interesting that a lot of organisations still fail to realise the inherent value of investing in Governance around their data asset. It's probably the best investment they could ever make to realise all of their other strategic goals. 

But, they have no problem investing in the latest and greatest technologies to work the magic on their competing demands, MDM/KYC, GDPR, CCPA, AI and other. This, unfortunately, is evident in the number of professed ‘magic tools’ out there lining up to help organisations ‘mask’ their underlining data quality issues to deliver some of these demands. Hardly a week goes by where I don’t get solicitation of companies requesting help and assistance in tool selection for one data need or the other. I find this somewhat ironic as most of these organisations have unfortunately learnt to live with their ‘chronic poor data quality’. They have bought into the promissory note of vendors telling them they don’t have to worry about the state of their data as their tool has the ‘magical whip’ to ‘bandage the noise’ in their data.

The reality is that poor quality data does not magically disappear. If you failed to create a governed and trusted environment around your data, it will continue to hunt you. You will not be able to realise the full potential of your innovative investments in all other data initiatives until you address this. 

Do I Really Need a Data Governance Policy?

It’s very rare that I’m able to give such a definite answer to a Data Governance question, more often than not my answer is usually ‘it depends’. Because so many aspects of Data Governance are nuanced and depend very much on your organisation's objectives and what you hope to get out of implementing Data Governance.

In this case, however, the answer is yes. Yes, you absolutely do need a Data Governance policy. That is, if you want to effectively and efficiently implement Data Governance in your organisation. Which, of course, you do, otherwise what would be the point in doing it at all?

This is a lesson I learned the hard way. When I first started doing Data Governance, I would say in the first three or maybe four initiatives that I worked on, I didn't have a Data Governance policy in place at all or not until it was too late. So, what I am really trying to tell you is learn by my mistakes! Make sure you have a Data Governance policy in place.

Learn from my mistakes

Now, the reason for this is mainly because without it, you're implementing Data Governance on a best endeavours’ basis. You're hoping that you can influence some people and enthuse them to start doing Data Governance. And, I can tell you from my experience, that sooner or later, you're going to end up talking to somebody that says, "Do I really have to do this?"

And this is exactly what happened to me. In my very early days in Data Governance, someone came to me and said: "Well it was all very nice Nicola and it was good while it was working, but that was flavour of the month and we've decided not to do that anymore." You do not want that to happen to you.

They might not be a deliberately obstructive person. But they'll be saying this because just like most of us they have so much going on that they don't have time to do everything and if they don't have to do Data Governance, then they won’t. It’s an easy one to drop off the bottom of their to-do list. So, if you have a Data Governance policy in place, it sends out a very clear message that senior stakeholders in your company have said that you are going to manage your data properly.

Remember you’re doing this for all the right reasons 

Data Governance is something that can deliver such fabulous benefits to your organisation. You do not want your initiative stopped because you didn't take the time to get a Data Governance Policy in place very early on, so I really would encourage you to do that.

If I’ve managed to convince you that you need to write a Data Governance Policy but you are wondering where to start, you can get all the information you need and a simple approach in my new short online course: How To Write A Good Data Governance Policy.

How Often Should You Revisit Your Data Governance Maturity Assessments?

In my experience so many people seriously underestimate the speed at which they're able to implement data governance - so, when a client asked me how often he should revisit his Data Governance Maturity Assessment I thought ‘that is such a good question, I’m going to write a blog about it’. And here we are.

First things first, what is a ‘Data Governance Maturity Assessment’?

Very simply, your Data Governance Maturity Assessment is a helpful tool I often recommend organisations use to answer questions around what they are aiming for and where they are starting from when implementing a new Data Governance policy.

And, as such, doing, and revisiting, a data governance maturity assessment can really help identify what progress has been made and perhaps areas that need to be focussed on in the next phases. So, I think they are a really, really useful tool - especially as you can expect a new data governance initiative to, in my experience, take the best part of a year (and probably longer - as there’s no end to data governance) to design and implement a Data Governance Framework over at least some part of your data or organisation.

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.

How do I get a Data Governance Maturity Assessment?

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. 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.

So, I have my Maturity Assessment - how often should I look at it?

The timing is going to be important after all you don't want to be revisiting your Maturity Assessment too often because, actually, nothing will have changed in the passing time and all you will end up doing is bugging people. And, even if you use a very light touch Data Governance assessment tool, you're still going to be bugging people and asking them for their time. You don't want to do this unnecessarily.

What I recommend will depend on your circumstances, but definitely no more frequently than six-monthly, because in my experience, not enough will have changed to make it worth the effort of doing that - so I would say six-monthly, or maybe yearly.

I think you need to have a look and understand what's been moving on in your organisation and whether it's worth doing it again at this point. But, one thing I would also say is, when you're looking at the results of a Data Governance Maturity Assessment don't take all of them to mean that you've not accomplished anything.

Sometimes you've done the hard work and revisiting a Data Governance Maturity Assessment and asking for new responses is a really good measure of how well you're communicating.

I can't tell you how many times in the past - particularly in the early days - I've had results back and being devastated because I thought, well, we've done that bit already. ‘Why are they saying there's no data owners in this area as there clearly are?’ And, then when I take the time to take a step back and think about it, I realise that actually… we've done the work as a Data Governance team. But what we hadn't done was communicate it to the wider audience.

And, Data Governance doesn't work unless everybody's on board, you need to make a sustained culture change. You need lots of comms for that. So, Data Governance maturity tools are very useful tools when used correctly, and just don't do them too frequently. 

I hope that was helpful and don't forget if you have any questions you’d like covered in future videos or blogs please email me - questions@nicolaaskham.com.

Or 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.

Data Governance Interview with Ed Mathia

In this Data Governance Interview I spoke to Ed Mathia. Ed is a Data Scientist who learned very quickly that data quality is paramount, and that the processes to make data right the first time increases its value.  When he finds incorrect data he works to change the data source to ensure the company has good information and makes good decisions. I’ve always enjoyed my conversations with Ed and in particular love his analogies when explaining Data Governance.

How long have you been working in Data Governance?

About 15 years ago, I became the Specification Manager for a semiconductor materials manufacturer.  My team was responsible for keeping the product specifications for the company.  The old timers used to say that a specification mistake released to production was equivalent to buying a house.  We recalculated when I was there, and a mistake could easily be 2 million dollars - that is a nice house.

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

I have heard people talk about Data Governance as an unusual field, but I think that we are just early in the curve.  Data Governance reminds me of the Quality profession twenty years ago.  Companies understand Quality now, but it took Toyota and Motorola to show the benefits of great quality and the ISO-9000 standard to show the right processes.  I think twenty years from now that viewpoint will be strange.

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

I think it is critical to have a good understanding of data science and machine learning.  Companies have so much data, stored in a variety of systems, that it becomes hard to find the fixable issues and the impact of the issues on the business.  It is a lot like a Magic Eye poster.  If you don’t know how to look at the 3D image, then all you see is the repeating horizontal pattern that looks like nothing.  With the right pattern matching techniques, you can resolve the special 3D picture.  Finding those patterns in the business data means you can fix the right problems based on the impact.

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

Nicola, I always found that your coaching calls are the most useful support.  Books like the DAMA manual are great, but they are generic and don’t help with the specifics of communicating with your company.  Being able to ask specific questions, to draw on your vast experience and get options very quickly is extremely helpful.  I always found the coaching sessions to be like Christmas - I look forward to them for a long time but they are over too soon.

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

As in most areas of life, communicating the need for change is one of the biggest challenges.  Everyone knows that bad data causes pain and has to be fixed before getting the right decision.  Companies accept the pain when they think it is a small, easily-fixed issue - like a paper cut.  But if everyone accepts little inefficiencies in the data then you have a big problem.  A piranha only takes a small bite, but a lot of small bites can do a lot of damage.  That is why I think it helps to have a good understanding of data science.  It is hard to find the inefficiencies spread through the company but it is possible -  using data science I found 6 million dollars of expedited shipment fees and one hundred thousand hours of productivity loss due to poor master data settings.

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

I think one of the most beneficial areas are company supply chains.  In the US, financial services are awaking to the understanding of the need for data governance, but supply chains aren’t seeing the need yet.  However, every dollar the supply chain saves impacts profit directly, while financial services are predicting which customers and products might be successful.  Manufacturing is a field ripe for harvest.

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

Hang in there even when things seem tough.  Everybody is hoping to hire a pharmacist who will give them a pill to make them skinny.  Data Governance folks have to be personal trainers telling clients they need to eat right and exercise.  Even though it is the right way to lose weight, they won’t want to hear it.  Hang in there and be consistent.

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

I once saw a data field that took on opposite to its original intent - sort of like the word “dust”.  Dust can mean either add or remove fine particles depending on whether you are talking about cleaning the house or making powdered donuts.  When I was managing the specifications at a silicon wafer manufacturer, one specification was how close to the edge the backside seal had to extend.  Several application engineers chose to check the “Edge-to-Edge” process specification instead of putting in the number of millimeters from the edge the seal could extend.  They were thinking that the “Edge-to-Edge” process sealed all the way to the edge, but it was actually a 15-year-old process that had the worst sealing coverage.  It really shows how important data governance is.  It would have been much clearer to focus on the specifications on the customer needs rather than which process to use.  Then the process could change as long as it met the customer's needs.  Specifying the process meant that we couldn’t give the customer a better product when new processes came along.

You can find out more about Ed and connect with him on LinkedIn by clicking here.