I’ve met with hundreds of people over the years, discussing various aspects of Data Governance (DG) and it is absolutely amazing what I’ve learned about this space. It never ceases to amaze; however, of just how soft & abstract people tend to describe the value and work of Data Governance . In my mind, and in my practices, Data Governance is very concrete & tangible. Data Governance IS NOTthe platform for a group of people to discuss, pontificate and ponder about all things data, which is actually what a lot of organization’s are currently doing.
Data Governance is about 1) collecting an inventory of what data you have, 2.) quickly getting to agreement on that inventory and mechanism to manage the inventory, 3.) then putting machines in place to ensure that both the physical & conceptual (business view) of data is protected, steered & leveraged in the ways that best benefits the organization. These are three tangible steps that can be achieved — we don’t need to pontificate about “what is” and “what could be”, we can just do it.
To make all of those things possible it all starts with an inventory of what you have — just like a good CPA does in your first meeting, he or she will take inventory of your assets & liabilities, checkout your cash-flow and finally review your P&L. Getting to a business data inventory is actually very similar, in that you can look at your lines of business, within them are macro and micro business processes and within each of those processes are key Business Data Elements (BDEs) that are required for the process to function.
A Business Data Element is the thing that business people consider to be the data. In most situations these will almost always be related to key KPIs and metrics that matter. It is important the the KPI & metric still be identified as such. What we are trying to gather & collect from them are the variables of those KPIs & metrics, with the additional attributes that they “slice & dice” that information. The KPI variables & reporting attributes ARE Business Data Elements! Below is a diagram that illustrates both how important the Business Data Element is in having one view of your organization, but also provides additional context as to what the BDE is.
In the process of scoping the Business Data Inventory keep track of what processes & Lines of Business that you are collecting BDEs from, because that will be valuable metadata later. Capture all that you can by rolling your sleeves up and learning about those processes, asking about data along the way. Before you know it you have a massive list of BDEs that you then need to attach the believable experts (which will probably become your data stewards over time, but you don’t necessarily need to start with that title). Then, lock the believable experts in a room for few days and have them to group or cluster all Business Data Elements (BDEs) that are similar & alike — the goal is to get to one version of the BDE that represents the many that have been collected.
Building this Business Data Inventory is the magic, and probably one of the most important Data Governance deliverables that can ever be pursued. With the Business Data Inventory in place, it is possible to begin relating the physical versions of data to their one version of BDE associated (i.e. Columns ID245, IDAD1, IDWhatever are all tied to BDE: Customer Name). With this relationship network established, 1 BDE to many physical versions, you can begin profiling & analyzing the physical data you can relate data quality outcomes back to the business data element — this ties Data Quality work directly to business, and creates a nice buttoned up story for business executives to see the impact of data quaity issues to their business data elements (BDEs), and more importantly their processes. With this inventory it enables the business to analyze data quality issues by BDE; therefore, by the “Processes” of the business that are impacted. If you recall, we kept track of the BDEs & the processes from which they were collected along the way. When Data Governance takes all of this intelligence and relates it in your meta model, it creates an insanely powerful analytical capability to understand not only your data, but specifically how that data relates to key aspects of your business model.
[special_text tagname=”h1″ pattern=”no” color=”#ffffff” font_size=”24″ font_weight=”bold” font=”default” margin_top=”30″ margin_bottom=”30″ align=”left”]If you are interested in learning more about how to establish a Business Data Inventory, designing and developing a metamodel to support Business Driven Data Governance, then click here.[/special_text]
Without the Business Data Inventory, DQ, Profiling, and many other data architecture initiatives all just look like “another IT thing & therefore a colossal waste of money” to business execs. But when you can say,
“the monthly reserving process for the Annuities LOB experienced 27 data issues last month (4 were serious, most were insignificant), and we just found 2 of the serious recently, but those two issues have been steadily happening over a 6-month period. Over that time period it has cost our organization $350,000 in annuity payments that we were not obligated to pay –> all caused by a code that should be changed to 2 when annuity contracts are closed or satisfied. These two issues also resulted in 23 of our high net worth customers to receive notifications that they should not have received” — this is a phenomenal Data Governance story!
Because Data Governance can understand & interpret data, analyze quality outcomes, and relate all of that back to the business process, you can not only find an audience, but you can create an entire movement that will invest into that story — I know personally, because that’s my story for 13 years now! There are a few other practical data experts (I can’t stress enough the use of practical & experts used together there…) that are also explaining this conundrum & need for one view of business data. One of those folks, John Schmidt at Informatica, wrote a great piece called the DG Hairball that describes how the one organization that is supposed to be bringing things together often starts splintered and creates a hairball about the hairball, which helps nobody! You can check his article out here.
With the entrant of the CDO, data is his or her currency. It is the asset that they are using to enable and deliver revenue, cost reduction, risk reduction, and other strategic aspects of the business. Data Governance is not a soft or touchy-feely thing — there is real work that must get done. It’s time to stop pontificating — and get some @#!$ DONE!
If you are struggling with getting your arms around data, launching Data Governance or getting the data community to engage, then check out these focused offerings below that are designed to address the three problems described.
Data Summit Workshop
Our Data Summit Workshop has been a favorite of our clients. This 2-day workshop is designed to charge & ignite your Data Community, provide a common education & understanding around data, and finally collect key inputs to identify the gaps around data for your organization using our predefined Organizational Maturity & Data Certification Assessment tools.
We have created a multilevel approach to helping you navigate the abstract beginnings of Data Governance & Data Strategy work. Whether you are coming from the technology, architecture or business perspectives, we have the the right expert to help you navigate the waters.