Ironically, when we use the phrase "road map" to describe anything other than travel, what we're talking about is not really much of a map, and it generally doesn't even have roads! Instead it has come to mean both something larger (a plan or strategy) and something smaller (accomplishing a particular goal or completing a particular task).
Still, it's a useful metaphor. A road map shows an area or region, and the various roads that traverse it; it's up to the person (or the algorithm, today) looking at the map to decide which route to take in order to reach the destination. Similarly, when we work with organizations to help them develop a data governance road map, that work involves surveying the territory, plotting potential roads, and ultimately settling on a preferred route and pace to get them where they want to go.
At its most basic, then, your data governance road map has to start with figuring out what your current state of data governance is, and what you'd like your future state to look like. There are a number of tools you might use to assess your current state, such as the Data Management Maturity Model, or variations on it that focus more directly on data governance. You could work with a consulting firm, which is likely to have its own questionnaire or assessment tool. Or you could create your own framework organized around three or four major categories: what can you currently accomplish easily using data? what can you accomplish with difficulty? what can you not accomplish that you would like to? Our experience has been that if you talk to enough people in your organization, certain common themes and observations will emerge.
As for identifying and describing a desired future state, people in your organization are probably going to have different visions. Working from an existing data strategy, or developing one, can be helpful here. If there are many changes or improvements that could be made, figuring out the ones that will most directly help with your organization's strategic goals will speed the process of bringing your map into readability.
A data strategy helps clarify which aspects of your desired future state are most desirable, or most critical to achieve. A current state assessment tells you where you're starting from. But it can also tell you where you have existing capacity for growth, or where there are resources in place on which you are really lean. To extend the metaphor a little further, this assessment helps you understand what kind of vehicle you're driving, whether it has four-wheel drive, how full the gas tank is, if a toll transponder or satellite navigation system is installed, and so on. Some of the roads you might take could be icy, or backed up from traffic, or under construction, and you'd probably want to strike them from your map even before you set out on your route.
Your data governance goals will undoubtedly have much to do with existing problems and shortcomings. If data quality is perceived as an issue, then certifying data might be a goal; if reports and analyses take too long to turn around to be actionable, then a robust BI environment and toolset might be your goal; if users seem careless with data, or uncertain about how to access and utilize it securely, then a rigorous data protection program might be your goal.
Use your strategy and your strengths to guide your decisions. We recommend prioritizing activities not only by which goals are most important to you, but also by how attainable they are. A successful data quality improvement process requires data managers and stewards who speak the same language and share the same goals, as well as technical resources who can profile data and script mass changes and updates. You may have a group of smart analysts and data scientists in place who are hamstrung by an outmoded architecture, but perhaps you don' t have the funds for a wholesale BI upgrade. Data protection activities require both education and enforcement - are you able to commit to both right now?
There might not be a direct path for you on your data governance road map. Or, as with actual travel, the most direct path might not be the quickest or easiest. We recommend planning your route using the following guidelines:
- Decide on a route that will address real problems that real people are facing. (Hint: not having enough meetings to attend, or committees to belong to, are not usually the real problems facing your data stewards, modelers, and consumers.)
- Recognize that multiple vehicles and drivers will take this trip, and allow for them to take different roads at different times, if necessary. Your data quality work might precede your data privacy work, but maybe the privacy work will go faster once it begins.
- It's a long journey, and there will be stops along the way. Break your larger goals into manageable tasks with visible milestones.
Publish your route(s), and let your employees know how long you expect the trip to take. Remember, it's a caravan, not a race. That everyone arrives at the destination is much more consequential than who gets there first. Be flexible rather than rigid, and pragmatic as well as idealistic. Expect that there will be unintended detours, plan for delays and traffic jams, and hope for some fortuitous bypasses as well.
We wish you well on your journey. And who knows - maybe we will travel with you!
Hope this blog post was beneficial to you and your organization. IData has a solution, the Data Cookbook, that can aid the employees and the organization in its data governance, data stewardship and data quality initiatives. IData also has experts that can assist with data governance, reporting, integration and other technology services on an as needed basis. Feel free to contact us and let us know how we can assist.
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