When should you enlist an executive sponsor for your Data Governance initiative? What are the 3 things you must focus on when launching your own personal Data Governance business? What’s the difference between a framework and a strategy?
Jill Dyché kindly took time out from her busy conference schedule to answer these and many other questions that are commonly asked by members.
Jill is Vice President of Thought Leadership at SAS.
Dylan Jones: Hi everyone and welcome to Data Quality Pro.com. I’m delighted today to be joined by Jill Dyché who is over here for the Data Management and Information Quality 2011 conference in London. You used to work in the UK is that right?
Jill Dyché: Yes, I worked here in 1997 and miss it terribly but it’s great be back.
Dylan Jones: So if anyone has spent any time online or on social media you will no doubt have heard of Jill, she is thought-leadership at SAS DataFlux with an extensive background in Data Governance, Master Data Management through her role at Baseline Consulting, a company which recently merged with DataFlux. Jill is also a renowned author, which books do you have out at the moment Jill?
Jill Dyché: I’ve got 3 books, the latest one is Customer Data Integration, Reaching a Single Version of the Truth, which was really the first book on MDM.
Dylan Jones: So, a huge amount of experience and Jill has kindly given us some time today to chat about some of the questions our members have raised and also we’re going to talk about the presentation she gave at the DM&IQ conference this week.
So let’s start with your presentation. The topic was: Beyond Data Governance: Building Your Corporate Data Strategy.
Jill Dyché: Yeah it was a great conference.The theme from my presentation was that companies really need to start looking at data governance in terms of their business strategies. So the reason that has come up a lot from our clients is that they are socialising the idea of data governance. They have these meetings but at the end of the day, they really can’t articulate the problem set and data governance ends up being an academic exercise really quickly.
So we’re finding that when we pivot the discussion to data strategy the business is more willing to engage in a conversation and the problems that we’re trying to solve become much clearer.
Dylan Jones: One of the things that stood out for me in the presentation, there were some great slides regarding data governance in 2010, you then zoom forward to 2011 and of course you’re out there in the field talking to companies so the slides talk about the challenges companies are discussing now and the thing that jumped out at me was that you mentioned the need to enlist executive support and buy-in was slipping as a discussion point. Why do you think that is? I assumed that discussion point would do the reverse and increase as more companies mature and look for buy-in.
Jill Dyché: It’s not really if, it’s more when. So what companies have ended up doing is, executive sponsors are enlisted too early and so what happens then is that everyone is running around talking about governance, there is an executive sponsor that is waiting for something to happen and everybody is talking and no-one is executing.
So what we’re finding now is a lot more people are more intent on designing data governance and figuring out what it looks like and THEN enlisting an executive sponsor as opposed to prematurely starting to socialise the idea without a plan.
It’s not that the discussion is going away, it’s that the discussion is happening later in the data governance planning process which is where it should happen, not at the beginning. We need to tell executives what data governance looks like in the context of our business and then enlist them once they see the value.
Dylan Jones: These discussions on data governance are interesting because I was talking to a guy during one of the sessions at the event and he’s been in IT for many years. He was dismissive about data governance labelling it as a bit of a fad, making the point that it’s something we’ve been doing anyway since the 80’s with an already defined term for it, which he said was Data Management. Now, you had a great slide which illustrated the differences between data management and data governance. So when someone has to stand up and differentiate between these terms to a bunch of execs and a person asks “Hey, isn’t all this just data management, haven’t we been paying for this all this time?” what are the differences that they should be drawing on?
Jill Dyché: Yeah, it’s cute because your friend is right but he’s wrong. We have been doing data management since the 80’s and arguably even before that but data management is not data governance. Where people get wrapped around the axle is that data governance becomes this huge “bucket” that everything gets put in and we’ve seen the analyst firms talk about Enterprise Information Management (EIM) and Information Lifecycle Management (ILM) so there are all these terms, everyone is throwing everything in there.
One of the things we’ve done is differentiated Data Governance, which is the business-driven policy making and oversight of information, the key word there being “business-driven”, we’ve differentiated Data Governance from Data Management which is the tactical execution of those policies, right? So your friend being in the data management world is already executing on a lot of this stuff and yesterday at the conference I asked the audience “Can you do Data Management without Data Governance?” and the answer is “Yeah, you can” because a lot of us have already been doing that in the world of Business Intelligence (BI) where we’ve got our data models and we’ve got our information architectures and we’ve got our metadata and we’ve got our data quality.
So you can do data management, you can execute, it’s not as elegant or as business-driven without data governance but you can do it.
The inverse however is not true. You cannot do Data Governance without Data Management. A lot of our clients ask us “Can you come in and do a Data Governance Masterplan for us? Give us our roadmap.” The first question is “if we do it, if we come in and build that for you, what’s your ability to execute?”. So a lot of them, particularly on the executive side, are completely unaware of their organisational sophistication with data management.
So I think that by differentiating the two terms, Data Governance and Data Management, it not only makes the processes around each one clearer, it makes the skills and roles a lot more robust.
Dylan Jones: On that topic of strategy, I recently wrote that a lot of people get confused between frameworks and strategy. It’s one of the questions we get asked all the time “can you send me a strategy document, can you send me a framework document”. These materials, you see them going round the web, cropping up in presentations. So they get the blueprint and “hey presto” they feel they now have a Data Governance Strategy. Where do you feel companies go wrong when putting these strategies together because clearly having a blueprint or framework is only one part of the process but you and your team have a real reputation in the industry for excellence in helping companies put the right strategy together, what are some of the common mistakes that you help these guys resolve?
Jill Dyché: That is a great point that you raised because a framework is not a strategy. It’s cute because sometimes we’ll have clients come to us and say “Just give us your data governance template, we’ll buy it”.
The point is there is no template. Unlike other strategic initiatives that involve IT, Data Governance needs to be designed. The cultural factors, the workflow factors, the organisational structure, the ownership, the political factors, all need to be accounted for when you are designing a data governance roadmap.
People need a mental model, that is why everybody loves frameworks and trust me we are great at creating frameworks but they are not enough and I think the mistake that people make is that once they see a framework, rather than understanding its relevance to their organisation, they will just adapt it and plaster it up on the whiteboard and show executives without any kind of context. So they are already defeating the purpose of data governance which is to make it work within the context of your business problems, not just have some kind of mental model that everybody can agree on but it’s not really the basis for execution.
So it’s a really, really dangerous trend that we see where people equate strategy with framework because strategy is really a series of collected actions that result in some execution and that is exactly what data governance is.
Dylan Jones: So another popular topic is that of the Data Governance Council. I was reading back through some of your old blog posts and articles you had written in the past and you have, not what I call a negative view on Data Governance Councils but you certainly see companies making mistakes with councils, what sort of mistakes do you see?
Jill Dyché: This goes back to the point I made earlier about executive sponsorship.
People are doing it too early, it’s not that it’s unnecessary but two years ago we were talking to clients and they said you know, we don’t know where to start, we are brand-new, what should we do? Now when talking to clients about data governance, they are still early but they have already formed a council. That is an even worse place to be because there is a group of people, ideally stakeholders, that are cross functional and waiting for something to do. They are waiting to make decisions and without processes they sit around and complain about data. What we find, and I talk about this in my presentations, we call it the kick-off and cold cuts approach to data governance, where somebody brings in lunch, and everybody starts to talk, you know about how we’re going to solve the data governance problem, people start complaining about data. The next meeting happens, and fewer people turn up, there is no lunch and it just sort of erodes peoples confidence because there is no clear workflow, there is no clear problem, there is no clear solution and it just becomes this organisational inertia. So what we tell people is design your data governance program, understand what the intake process is for data problems, understand the ownership issues and the decision rights and then enlist a council of people who are actually going to participate in the day-to-day improvement of data and the day-to-day policy-making and the day-to-day business rules and who are willing to tie-break because we are essentially going to make this systemic over time and so the people need to have enough organisational authority to make decisions and they need to have enough organisational authority to ensure that data management tasks get executed. Bringing them together without some of this work is just inertia waiting to happen.
Dylan Jones: Whether it is MDM, data governance or data quality, one of the biggest challenges our members face is the thorny issue of our ROI. Through your work with Baseline Consulting, and obviously now DataFlux, you are obviously intimately involved with getting programs to that executive presentation stage, getting that business case over. What tips can you provide to those members, who right now, may be staring at a blank sheet of paper with the words “data quality business case” stamped at the top? What kind of pointers can you give to those folks so they can help convince the execs for a call to action?
Jill Dyché: It’s a great question, because yesterday at the IRM conference a guy came up to me and said: “I love what you just talked about but how do we convince our executives that we need to fix our data?”
And, you know, like every good consultant I answered a question with a question by asking “What is the need, pain or problem you’re trying to solve?”.
So it was interesting because this guy hadn’t started thinking in those terms, instead he had started thinking, well, we just need to fix data and where do we begin? So our answer is you start with a business problem, start with something that needs a solution.
Now the hard part about doing any kind of business case for data quality or data governance is that often business cases and ROI are only as good as the existing measures that are already in place. So companies are not yet measured the as-is are going to have a hard time measuring the to-be. The challenge with any business case, particularly when you need to calculate hard return on investment, is to look at existing measures. I’ve got an example in my book of Harris Entertainment and how they had measured the percentage of stays in their hotels by frequent guests before their total rewards program, and then after their total rewards program, they had hard revenue figures with hard revenue dollars. So the extent to which you are already measuring is the extent to which you can make a case for better data, better business decisions, better business programs, customer retention and sales uplift.
So at the end of the day, we need to measure and depending on what your business problem is, that should at least help you narrow your measurement focus. The risk here is trying to boil the ocean, so you should come at it via a business problem or, as I talked about at the IRM conference, via a business strategy.
Dylan Jones: That’s a really good point. One of the things I see often with people is that they go out and get the tools, they get the latest technology and it’s almost as if they’ve got a solution looking for a problem and they need to turn things around so that’s a really good tip, thanks for sharing.
Again, something we’re trying to focus on a lot at the moment with Data Quality Pro is helping our members who get to the top or the pinnacle of their career be it in MDM, data governance or data quality figure out where do they go next? They may have helped their company implement an MDM or Data Governance program and do not want to go down the CIO or executive route, because they love the topics of data governance and so on. So quite a few of our members now are looking to launch their own business and we are looking at pilot schemes that will help them take that first step. I can think of one person right now, in particular, she is at the top of her game in the data governance sector, has heaps of experiences working with several companies and is confident enough to go out on her own but is obviously nervous about what is involved, is it going to work etc. For people like that are there any tips or advice you can share because obviously you’ve been there, you have helped create a hugely successful consulting business through your own organisation at Baseline Consulting, so what kind of advice can you offer people who are about to make that leap into launching their own consulting business?
Jill Dyché: Yeah, I can think of three things to tell your friend and God bless her for wanting to put herself out there like that, we need more people in the industry that can walk the walk.
The first thing is to have a point of view. I think at Baseline one of our competitive differentiators was we were always aligning IT and the business through our projects. So whether we were going out and designing Business Intelligence (BI) processes or whether we were actually designing a data management organisation or introducing data stewardship processes we were always aligning the business and IT, engaging everybody and then redefining those rules of engagement. So we got to be known for business/IT alignment.
So I would suggest first and foremost, have a unique point of view that becomes a part of your brand.
My second piece of advice is to have the stories to tell. Nothing clinches a new client like a success story or a case study and I think the reason my books have done so well is because we have got real life client examples in those books that talk about how people have deployed data governance successfully, how people have actually implemented master data management programs at the enterprise level. You know, we talk about clients like ING Insurance, Harris Entertainment and Qantas Airlines, those stories resonate with people, often people are customers of those particular companies and they like to hear how they are succeeding.
The last thing I would say is just put your backpack on and get ready to hit the road, because sometimes as a consultant your credibility is directly proportional to your distance, right?
So I would say just be ready to travel because if you are any good you are going to be in demand.
Dylan Jones: Fantastic advice, thank you Jill. So to find out more about you where’s the best place to visit online?
Jill Dyché: Well, they can see my blog at www.jilldyche.com and they can visit both of us, Dylan, at the Data Roundtable (http://www.dataroundtable.com) those are obviously two good places to go. And of course the DataFlux website.
Dylan Jones: Enjoy the rest of your trip in the UK Jill and thank you again for sharing so many great insights with us today.
Jill Dyché is the author of three books on the business value of IT.
Jill’s first book, e-Data (Addison Wesley, 2000) has been published in eight languages. She is a contributor to Impossible Data Warehouse Situations: Solutions from the Experts (Addison Wesley, 2002), and her book, The CRM Handbook (Addison Wesley, 2002), is the bestseller on the topic.
Jill’s work has been featured in major publications such as Computerworld, Information Week, CIO Magazine, the Wall Street Journal, the Chicago Tribune and Newsweek.com. Jill’s latest book, Customer Data Integration (John Wiley and Sons, 2006) was co-authored with Baseline partner Evan Levy, and shows the business breakthroughs achieved with integrated customer data.
Jill is VP of Thought Leadership and Education at SAS.
- Company name: SAS
- Company website: http://www.sas.com
- Location: California, USA
- Blog: http://www.jilldyche.com, http://www.dataroundtable.com/?author=3
- Twitter handle: @jilldyche
Publications by Jill Dyché