03/18/2015 | Data and Analytics | Thought Leadership
Information has always been important to our daily use, but in the era of Big Data it’s become more important than ever. Much of the conversation around Big Data has been focused around the technology necessary to collect and store information, but what we should be paying attention to is why data needs to be governed and how to manage it reliably and consistently so that sound decisions can be made.
Usage starts where data first enters the organization—at the source. Some data are entered via various transactional or point-of-sales systems. Others data are acquired where they are merged, cleansed, transformed and consolidated downstream. Eventually all data points get aggregated in a warehouse and subsequently queried or get “data-marted” for specific analysis. This analysis supports various decisions throughout the organization – operational, tactical and strategic. The quality of the data defines what will happen downstream as data travel across and within the organization. As important decisions depend on data being usable, it is important that data elements are managed to their best quality. How do we ensure this? Here are 5 simple steps.
1. Establish Data Owners & Stewards
In the world of Data Governance and MDM, data owners, data stewards and systems owners & stewards are all important roles defined in the establishing of key players – Committee, Program Office, Working Groups and Stewards. When you have data owners, accountability and responsibility is quickly established.
2. Establish Priority
Is the data hemorrhage occurring in specific areas that are severely affecting decisions? Treat those issues quickly so that foundational and fundamental tasks can operate normally and the environment is stabilized. This gets you a “quick win” to establish the value of data projects to the business.
3. Seek Sponsorship and Create Champions
Data Governance cannot succeed if you don’t get executive sponsorship. The action necessary to resolve data issues will be like tentacles reaching far into the organization. It will get territorial. Data Governance will expose problems related to process, technology, or people to the top so that the business can address what is not operating, needs fine tuning or is outright missing. Data is a powerful indicator. To harness that power, you need all the executive support you can get. You will also need champions to actively and continually evangelize your effort.
4. Support with the Right MDM Tool for Measurable KPIs
MDM technology fits Data Governance like a glove to the hand. Your results will be best when they operate together. Conduct an in-depth assessment to ensure the most appropriate and effective tool for your organization is chosen to support your data governing efforts. Strive for a golden set of master elements (Vendor, Products, Customers, Employee) amid data cleansing, merging, transforming and integration. This is where success criteria (KPIs) are established with data owners and stewards. The KPIs must be measurable, managed and monitored, which is why working in conjunction with an appropriate MDM tool will greatly enhance success. This also answers the “you can’t manage when you can’t measure” question.
5. Create onus with each member
The data owners, stewards, working groups and IT systems are the mechanical components of the Data Governance organization. The oil that lubricates this machine is the onus on each member to maintain data at its finest level as they create, edit, transform, delete and archive data elements. The onus at the individual level is the only thing that can lead to pristine data. This is what sets the stage for useful data analytics and insight.
The above is simplified but gets you familiar with the fundamentals of Data Governance & MDM. What should you be asking yourself once you have the basics?
Looking ahead
I started playing soccer when I was six years old and enjoyed it so much it’s become an adult passion. After tearing my ACL, I decided to continue that passion but from a different perspective. I became a referee. During one of our advance training courses, the instructor taught us to recognize a foul that’s forthcoming–for example, watching a player taking off 15 yards in advance with one target in eyesight that is not the ball. Officiating is not just all about remembering all the rules. Recognizing and reading the situation to see what is going to happen helps to manage the game. By reading the look in the players’ eyes and posture, or noting a tackle or missed call that happened just before that, you can see frustration brewing and size up opportunities for the player to vent before they happen. The instructor summarized this skill by telling us to constantly ask ourselves “what do you see coming?”
That statement still resonates today as I step on to the field, helping me prevent many unwarranted injuries and, most importantly, protecting the safety of each player.
Bad data can have worse consequences than an injury or missed call resulting from a foul. It could mean losing huge revenues through operating under the wrong assumptions and making the wrong decisions.
When you step into the field of data dealing with its intricacies and challenges in an attempt to protect the most important asset of the organization, what do you see coming?
