Part III: Just say no to modelling the universe
by: Bill Cason – Troux CTO – July 31st, 2012
Gathering and assessing data can be quite seductive. But it’s the equivalent of modelling the
universe, and it’s a recipe for disaster. In fact if we see any problem today in our EA deployments, it’s that people get so excited they want to gather all their data at once. This is the last of the Top Three common mistakes Enterprise Architects (EAs) make when starting (or re-starting) a program. I call this “Building the Answer Machine” – and it doesn’t work.
In this scenario, you are asking people for more data than you need, without any scope control or business value focus. Obviously you don’t want to collect data, just to see what you can find.
Instead, consider these three recommendations when embarking on a data gathering effort. They will help you successfully identify and gather the data that is most important to your business. #1- Leverage a wider team with a focus on business value to help you identify which data is critical. #2- Automate as much of the data collection process as possible. #3- Market your success internally so that contributors appreciate the fruits of their labor and are more inclined to embrace the data gathering effort moving forward.
Leverage a wider team
You will have lots of stakeholders and constituencies requesting answers. You can quickly lose sight of being able to deliver value in a timeframe that is acceptable to management. Queuing up priorities and managing scope control is hugely important. Otherwise you will have plenty of stakeholders disappointed by your inability to answer their questions.
The EA team is responsible for creating business value with the information that is collected. But don’t waste EA resources gathering that information. With executive sponsorship in place, the enterprise will see it as a priority to identify data stewards. The data stewards will then provide the required data you could not automatically collect. This in turn ensures EA resources are focused on analyzing the quality of the information, and identifying gaps in order to initiate the decision-making process.
Automate data collection process
Based on my team’s experience, as much as 80 percent of the information required to initiate an EA program already exists in the enterprise. In many cases, you can automatically collect important information from other IT and business planning repositories so you don’t have to expend human resources to find what’s already being managed. That said, stay focused on collecting only the information necessary to answer the high priority questions your business wants to address.
Market your success
Don’t forget to market your success internally. You secured support from the organization by promising something good for them, so make sure you go back and tell them you did it. Then the organization as a whole can share in your success.
When you gather all this information and start to see results – in this case the answers to critical business questions – share those results.
Remember, the data acquisition process is accretive. The data you get to answer the first set of questions becomes foundational for answering the second set of questions. You don’t use information, throw it away and stop asking questions. By involving the wider team, you empower and encourage people to embrace the EA processes and use the output to change the business.
We already know that organizational change is one of the hardest challenges any company can embark upon. Ensure you are taking the right steps by aligning a wider team to provide information, automating the data collection process, and marketing your success internally. The EA practice can then deliver true organizational change in a focused and organized manner, on a timeline management expects, and with the support of both your executive sponsor and the whole of the enterprise.
Read other articles in this three-part series: How to avoid common mistakes with your EA Program:
- Part I: Overcome the experience gap when initiating a new program
- Part II: Focus on business value, not the tool
