Many companies accumulate piles of data but are not taking advantage of its insights. The missing connection here is the conversion of data into accurate, consistent, comprehensive, and current information.
Technology can help you with this but the main aspect here is to establish a data governance plan. Besides, people and organizations need to treat the data as their company asset by committedly implementing the defined rules and procedures. It has to be the goal, which many businesses have failed.
You can read plenty of advice associated with data governance best practices on the Data Management Education blog before you embark. Data governance consultant from EWsolutions can help you in determining how to implement data governance as well as control data flows accurately.
Avoid data governance implementation blunders
No strategy
Data governance is an all-encompassing strategy, which defines how to obtain accurate, clean, usable, and safe data. You can randomly solve a couple of challenges successfully but when you accept more complicated projects lack of data governance strategy can drive you towards the wrong path.
Data governance is not a program that is set once and forgotten. You need to start small and grow over time to fulfill your business needs. A data governance strategy dictates how to store and protect data, sets rules for data access and usage, and defines controls to ensure policies are followed.
Committee overload
Data governance committees include people that represent different departments and units. It is good to work in a group but unfortunately, there are plenty of people participating in the process.
More people in each committee mean more politics and more diluted the responsibility of data governance becomes. For success, limit the committee size between six to twelve people. Ensure that committee members are given decision-making authority, whenever needed.
Storing everything for a lifetime
A good data governance strategy includes data retirement. Every data entered needs recycling at some point. Unfortunately, businesses decide not to delete any data, which means they keep storing ROT [redundant, obsolete, trivial] data. They spend lots of dollars every year storing data, which they will never use. Keep everything is illogical, and their data governance program is a disaster.
Assuming technology is the solution
Enterprises invest in data quality, data integration, and data management software to support their program. Vendor publicity and pricey tags build a hope that the software will perform the entire hard task.
It will allow enterprises to avoid offensive people, processes, and political problems. It is a wrong notion! Purchase of software is good but it is the internal collaboration that can make or break the data governance initiative.
Trying to resolve all issues in initial phase
Data governance efforts will fail if you try to resolve every data issue in the project’s initial phase. Companies try to resolve the biggest data issues that span across the entire business, which are generally political and have been accumulating for years.
It is an impossible task to tackle this political buildup and establish data governance simultaneously. You need to think universally but act locally. It means to break down data issues into incremental deliverables because ‘too big and too fast’ invites disaster.
Data governance is a joint endeavor and if you avoid the errors mentioned above then your data governance program is a success.
