Top 5 Reasons How and Why Data Governance Programs Fail
Data governance can boost data goals and efforts to drive overall business strategy. Conversely, poor data ethics can significantly damage a business or organization in today’s data-driven market economy. Unfortunately, many enterprises are still failing with their data governance programs. Why does this happen?
This article will look at the top five reasons and areas that can impact your data governance program and what you can do about it.
What and Why of Data Governance
Data governance pertains to the management or control of data via set procedures and rules, including data policies, protocols, and guidelines, and the creation of a specific data governance framework.
The main goal of a robust data governance program is to ensure the availability, usability, integrity, and security of enterprise data and its security and integrity. Additionally, data governance can help an organization stay compliant with government regulations.
Why do you need Data Governance Program for your Business?
Data governance has been around for a while, yet it continues to be a challenge for many enterprises across industry types.
In several cases, enterprises are wary of the costs associated with data clean-up and also because they are reluctant to put in the necessary efforts that go into cleaning up their data.
If this is you, then here are six considerations on why ignoring the implementation of a data governance program can be counter-productive to your business goals and efforts.
1. Bad data can jack up business costs and directly impact business revenue.
2. Poor data quality only adds to the complexities of an ever-expanding data ecosystem – this, in turn, can severely impact your decision-making.
3. The volume of data is increasing exponentially – you will have to address how you manage, store, and secure all your data. If not, your data quality will suffer, and again, this will impact your business goals and efforts and lead to compliance issues.
4. The accuracy and integrity of data matter to enterprises. However, data is increasingly becoming important to the well-being of users as well.
5. Inadequate data storage and management can penalize your organization – this is especially important in light of several compliance laws aimed at securing personal data.
6. Besides legal costs, the implications vis-à-vis business reputation cannot be ignored. So any risk mitigation plan will be incomplete without adequate data management, storage, and protection.
Here are the top five reasons why data governance programs fail.
1) Poor Understanding and Inadequate Preparations
One of the leading reasons why data governance programs fail is that enterprises approach data governance without an adequate understanding of what it is and what needs to be done.
What most enterprises fail to understand is that data governance should be viewed as a program that supports the day-to-day running of a business and not as an additional overhead or cost burden.
The best approach is to start small and slow and scale up with your data governance program. Enterprises can start by focusing on one type of data and its life cycle and concentrate on its management from beginning to end. Be clear about assigning roles and responsibilities in data management.
Look at common and specific areas of trouble and the areas that can cause the most damage when testing and validating data instead of attempting problem-solving on a comprehensive level.
Consider adding new testing and approval processes as you move along. You can then expand your tech and processes to different data types.
2) Senior Management Misalignment
Often the lack of support from senior management can lead to data governance program failure.
Unless the entire management is on-board with the implementation of a data governance program, failure is inevitable.
As mentioned above, data governance should not be considered an overhead or a waste of time. However, in several cases, the senior management of a business views data governance only in terms of cost to the business.
So, in addition to implementation issues, because of additional costs associated with upgrades or improvements, senior management may shelve the program or just shut it down.
Given that compliance regulations such as GDPR justify data governance programs as important, senior management will have to seriously consider allocating long-term resources to cover the different data governance functions and roles on an ongoing basis.
3) Data Governance in Silos
Data governance is an enterprise-wide endeavor – so unless every department, including the IT department, communicates with each other, data governance will fail.
New data governance solutions and initiatives will have to be included on an ongoing basis, and this will require the support and cooperation of every single department and employee involved in the data governance process. Inclusive efforts will also require that each department work on its own goals and targets in addition to the overall goals of effective data governance. Furthermore, these goals and targets should be effectively captured and the responsibility shared for all successes, gains, or failures if they happen.
Enterprises will have to be open to bringing in outside expertise. In addition to requiring the expertise, the cost of hiring an expert might be lower compared to training or upskilling existing IT teams. These are some of the considerations that will have to be looked into at some point.
4) Lack of Clarity on Goals and Poor System of Reporting
This point again builds on the earlier point about looking at your data governance program as a support framework for your day-to-day business goals as opposed to simply a cost burden. Having goals and targets for your data governance is necessary.
Specifying goals for your data governance program can be the difference between the program succeeding or failing.
Your data governance program can have multiple goals, such as cost savings, reduction of internal errors, improved compliance, etc. Capture all data about your data governance program goals and targets, so you know where you are going with your program and judiciously compare the data to see if it is helping you achieve your overall business goals.
In addition to constantly monitoring your targets, you must share the results with all stakeholders in your data governance program to boost collective ownership and continued interest in the success of your program.
5) Failure to Identify Responsibilities Assign Roles
The success of your data governance program will largely depend on the team(s) assigned with the requisite roles, responsibilities, and authority. Lack of clarity in these areas can cause your data governance program to fail.
Establishing data ownership is necessary at different stages or levels of your data governance program. First, assign roles so everyone knows who is responsible for making changes, who is responsible for approving those changes, who can access which data type, and who is responsible for ensuring or maintaining data quality and security. Each of these roles and responsibilities should be laid out and defined within the organization’s structure.
The Bottom Line
Data Governance is becoming increasingly important than ever before. As data types evolve and new data challenges arise, the risks in data are bound to grow.
Data governance has become necessary, given the increased government scrutiny and the need to ensure complete regulatory compliance. Ensure your business is prepared and armed for the upcoming data challenges by focusing on implementing a robust data governance program in your data management and storage.