We believe all CIOs know that a failure in data governance can bring significant loss to an enterprise, including property loss, damage to brand reputation, and even legal risks. So, how to develop a strong data governance strategy to ensure that enterprise data is more easily accessible and manageable while fulfilling security and compliance requirements, has become a necessity during the process of digital transformation of an enterprise.
With the increasing emphasis of enterprises on data, data governance solutions and the related technology are becoming more developed. Unfortunately, there are a lot of IT practitioners who are still struggling with the challenges of data governance. To help more enterprises solve their data governance challenges, this article has compiled 7 common mistakes made.
| 1. Take Data Governance as a Technical Project
A data governance solution is a technical project that is flexible instead of fixed. Namely, the strategy formulation of data governance is not expected to be simple planning or a project release since a data governance strategy that is unable to keep up with changes is bound to end up in failure.
In addition, inappropriate data governance strategies can block enterprise business from normal development, which causes each department to have to rely on themselves to solve problems.
Conversely, a good data governance strategy can help the business. For example, some enterprises might process with cash flow through process management. And employees would say they are totally comfortable with this way because they know the importance of securing cash flow.
If data is a great asset that an enterprise needs to protect, then the assessment, collection and retainage of a certain amount of data and types of it is a difficult task. If data is well governed, it can create significant economic values, whereas it can result in a huge waste of resources if it is simply stored without weighing the pros and cons of it.
| 2. Neglect Efficient Communication with Leadership and Business Level in Groups
Data governance is an overall plan based on the enterprise width. At the beginning of the planning process, it is important to communicate with the Business Department and reach a consensus to avoid any misdirection.
Data governance is not supposed to be seen as a ‘favorite’ in the IT Department, and it is also important to get buy-in from the company leadership and business departments. To ensure the scalability and sustainability of implementing data governance, CIOs should identify business objectives as well as focus on value outcomes and productivity improvement before proposing the data governance planning.
| 3. Fail to Include Real Owners of Data in Data Governance Processes
The biggest mistake behind many failures in data governance projects is that they do not bring the real owners of data into the project and do not get their approval and support.
One thing you need to know is, an enterprise or an organization that is going to govern data does not necessarily own or use the data, but only acts as a data steward. Therefore, it is a major challenge to find the people who actually own or use the data and make them have a clear understanding of plans and benefits of data governance.
Data governance is a top-down assignment, which can be effective only if it has the support from the entire chain. Conversely, if there is opposition from any sides during the process, it means the data governance still needs to be improved.
It is easy for a data manager to purchase a platform capable of data classification or data management. But if you want to change the data structure or purge useless data, you must get the support from the real owner of it.
| 4. Little Attention to Regulations and Standards
It is the most effective method for data understanding, data collection and data usage that combining General Data Protection Regulation (GDPR) with Privacy Impact Assessment (PIA), which is also the best way to link people, contents, time, locations, reasons and means related to data processing together.
Some enterprises that do not process data in accordance with the requirements of DPIA / PIA would lose their data protection capabilities and be disadvantaged by the use of unauthorized data, including being subject to severe penalties from regulatory authorities.
| 5. Insufficient Underlying Technical Capabilities
A critical mistake that many IT leaders often make is that introducing a data governance strategy without the support of underlying technical capabilities.
If you transfer data from a local centralized system to a cloud platform and don’t have the management ability of it, the business team has to figure out how to manage the data in their own way. Obviously, it will put the data governance team on the back foot if you don’t have the best preparation, rushing data to the cloud.
On the contrary, if we develop a complete strategy before we decide to govern data, so that everyone can manage and use data under the same planning with useful tools and platforms, we will absolutely get twice the result with half the effort.
| 6. No Comprehensive Training System Established
Data governance will fail finally if there is no relevant strategic guidance to further improve and strengthen the results of data governance and encourage employees to use new data sharing platforms.
It is recommended that all employees be trained before they use an online data governance platform to avoid them using unauthorized data or apps by chance.
Before standardizing specific information, a data management team should listen to employees to know their needs and demands and which information or collaboration tools are more important. Furthermore, it is also important to maximize data security by using effective tools and preventing the disclosure of sensitive information.
| 7. No Project Leader Designated
When developing data governance strategies, a specific project leader should be designated, and he needs to communicate and cooperate with the senior management of the business in order to finalize plans.
Meanwhile, a data governance supervisor needs to regularly call conferences with the IT Department and the senior management team in a company, optimizing and adjusting the data governance plans continuously.
To sum up, data governance strategy is significant that needs to be carefully developed. If there is no unified planning, each business unit will develop its own business system, which leads to the meaninglessness of data governance finally. In particular, as time goes by, there are more and more apps and data, and then the management will become more complicated if data formats are not unified.