How Long Will My Data Governance Initiative Take?

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

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

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

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

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

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

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

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

• What is the scope of your initiative?

• How big is your organisation?

• How open to change is your organisation?

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

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

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

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

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

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

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

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

How to use a Lean Approach to Data Governance

Getting a data governance initiative started can be extremely challenging.  This is especially true if you work in an unstructured manner, trying to start too many tasks at the same time or doing things in the wrong order.

Over the years I have developed my own methodology for implementing Data Governance successfully.  This is based on my experience of what has worked successfully (as well as what hasn’t) over many years of implementing Data Governance.  Although I got into Data Governance by accident when I was a Project Manager, I had never particularly considered whether a lean approach could be applied.  So, when I was first asked whether a Lean approach would work for implementing Data Governance, I decided to look into it.

It didn’t take me long to realize that I have incorporated some of the lean principles into my approach without realizing it and that a lean approach would definitely be a good way to structure a Data Governance implementation.

To be successful, data governance needs to be implemented iteratively and efficiently and that is why applying lean principles to data governance works so well.

What is Lean?

Lean was originally created by Toyota to eliminate waste and inefficiency in its manufacturing operations. The process became so successful that it has been embraced in manufacturing sectors around the world and is now used in many different industries as it can improve how teams work together.

The goal of lean is to eliminate waste, i.e. the non-value-added components in any process. The idea being that until a process has gone through lean multiple times, it contains some element of waste. When done correctly, lean can create huge improvements in efficiency, cycle time, and productivity, which leads to lower costs and improved competitiveness.

The Lean Enterprise Institute (LEI), founded by James P. Womack and Daniel T. Jones in 1997, is considered the go-to resource for lean wisdom if you want to learn more about the details, but for this blog I want to focus on why it is a good approach for Data Governance.

Lean principles are all about the following initiatives:

• Empowering small teams

• Reducing cycle times

• Gradually eliminating waste

• Focusing on value

So let’s look at each of these in turn:

Empower Small Teams

Lean improvements start with people, and the same can be said for data governance. Applying lean principles allows you to focus on your team first.

Instead of creating a huge project team to implement data governance, setting up a small central team to support users across your whole business will have greater success.

Rather than being responsible for all data, a small data governance team can focus on:

• Identifying and maintaining existing data management activities

• Providing a framework for managing and aligning existing data management activities, and planning for future activities

• Coordinating the implementation of the data governance framework

• Acting as a liaison between the Business and IT to verify that business requirements are fully understood by IT and ensure the business is fully engaged in IT led projects

Reduce Cycle Times

Many data governance initiatives fail because they are too big in scope, cost, and timescales. Working on small phases or projects will more likely lead to success.  For example, try executing one process in a business area. When that is completed, implement that same process in the next business area.  Don’t try to achieve too much at once; if the data governance programme is too large and unstructured, the benefits will not be delivered efficiently and the entire programme might get stopped.  If you focus on small areas of scope, you are likely to achieve small but consistent successes in the implementation of your data governance framework.

Gradually Eliminate Waste

Implementing a data governance program through small frequent phases (or projects) allows you to use the lean problem solving approach: The Plan – Do – Check – Adjust (PDCA) Cycle.

For example, the initial plan step would review the business area you are intending to implement data governance in and take measures to fully understand the current situation.  What are the priorities and challenges in that area? This knowledge will enable you to plan the implementation for a data governance framework that will benefit that area.

In the do phase, you will implement the framework and identify and brief various stakeholders about their roles and responsibilities. During this phase, prepare stakeholders to start following one of the data governance processes or activities, such as defining data items for a data glossary, or using a data quality issue resolution.

Next you check the results of the do phase, confirm they align with expectations, and identify what can be learned from the experience. Determine if anything should be done differently next time.

Finally based on the insight gained, you can either adjust your approach before planning to implement the framework in a new business area or move back to the do stage to make changes in the first business area.

Focus on Value

Taking inspiration from George Orwell’s Animal Farm, we could say that all data is equal, but some data is more equal than others.  Lean uses prioritization techniques to focus on areas where you can gain the most value, and the same approach can be applied to managing data.  You can’t achieve value from managing all of your data with the same level of monitoring and control.  The highest level of monitoring and control should only be applied to the most critical data, needed to successfully run your business (I talked about this in more detail in this recent blog).  Applying lean principles and prioritising data governance activities for data that adds the highest value for the lowest effort will help engage stakeholders and demonstrate the benefits of data governance, while long-term activities (i.e. high value and high effort) progress.

Business engagement is absolutely vital to the success of all data governance activities, and underpinning these activities with the solid foundation of a data governance framework will help you achieve lasting data governance success.

Don’t try to do too much at one time. If your data governance initiative is unwieldy, it will be too big to get started and too slow to deliver benefits.  Applying a lean approach to data governance can help you work iteratively, checking and improving as you go and focusing your efforts on activities that will deliver the greatest value to your organization.

My Data Governance Checklist gives you a structured approach to design and implement a successful Data Governance Framework. You can download the free version of this checklist here.

What should you include in a Data Governance initiative?

One of the many challenges you will have to face when implementing Data Governance is agreeing the scope of the initial phase of your initiative. By this I don’t just mean which data domains or business functions are going to be in scope. I’m thinking of associated activities like data retention, end-user computing, and data protection. Being a bit of a Data Governance purist I maintain that such activities are most definitely NOT data governance. It is easy therefore to make the logical conclusion that they should not be in the scope of your initiative. So what I say next may surprise you:

Do not immediately go on the defensive and refuse to take any (or even all) of these activities into the scope of your initiative!

Now you may be wondering why someone who spends her time educating people on what Data Governance is would say that! Well, when I’m training and coaching people it is important that they understand what Data Governance is, but when I’m implementing Data Governance in practice, I take a pragmatic approach.

However, I would not want you to think that I would just say yes to an ever-expanding scope. There are a number of factors that would make me consider bringing these additional data activities into the scope of my data governance work, which include:

• If you work for a small organization that does not have the luxury of separate specialist teams to cover each data management discipline;

• If they overlap with other projects ongoing at the same time;

• Or if a senior stakeholder requests it.

Whilst you may become aware of other activities that you want to bring into scope, they are most likely to come to your attention through your senior stakeholders – so let’s consider this question:

How do you manage senior stakeholders who ask you to extend the scope of your initiative?

Now whilst it may be tempting to protect the scope of your initiative, remember they have their own agenda. They are not trying to derail your plans, they just have concerns of their own or issues that they need addressed. The first thing you are going to need to do is to listen and understand what their concerns are before you try to educate or influence them. After all, how can you properly allay their concerns if you don’t fully understand them?

But remember whilst it is imperative that you understand why they’re asking you to extend the scope, when I say educate or influence them, I don’t mean your initial stance is to say no! When talking to your senior stakeholder, ask lots of questions and constantly consider the following:

• What exactly does this person need done?

• Does it have any alignment or overlap with your data governance work?

• What will happen if this additional work does not get done? (And in particular will it cause a problem for your data governance initiative?)

Even if the answer to this last question is no, it may still be necessary for you to consider that if you say no, that this senior stakeholder could divert resources currently allocated to your initiative to address this other issue.

Are there benefits and/or efficiencies to be achieved by taking on this work? This can be especially true if you are talking to the same stakeholders.

My advice is to look for solutions that help everyone. This is not about you or them winning. This is about doing the right thing for your organization. Find out why he/she is concerned about these other topics. Is it because they are not being done, or is it that they are being done but are not visible or are being done but not well enough or quickly enough?

Now obviously I’m biased, but I truly believe that well implemented data governance can be the framework against which you align an awful lot of other activities in your organization (well at least those concerning data)! Once in place, you can use your data governance framework to coordinate, oversee, and escalate other data matters to the appropriate people. That said, it is not the answer to everything and you should resist taking on everything (unless of course you are Superman/Superwoman), or at least agree to timescales for adding additional scope once the implementation of your data governance framework has reached a certain stage.

If you do take on something that perhaps you feel is not in the area of your expertise, that is ok – just be honest and clear on the matter. Explain that whilst, for example, you may not be a data retention expert, you see how including that in your data governance initiative has benefits for the organization. Confirm that you are happy to do the necessary research and support the work if you are given the necessary expert support (for example from your Legal Department).

Remember that whether your data governance initiative is small and focused or has gained additional scope, stakeholder engagement is absolutely vital for success. You need to spend a lot of effort engaging your stakeholders. If you could lose their support by not addressing their other concerns, it’s got to be worth considering whether the additional work is something that you can take on.

Finally, if you want ideas on how to go about engaging your stakeholders, you can download my top tips on stakeholder engagement for free if you click here.

Originally posted on TDAN.com