In one of our previous blog posts, we already mentioned that most companies have a lot of user-related data at their disposal and might not even realize it. It doesn’t really matter whether said data was gathered from support requests, marketing analytics or user research–if it’s evaluated and used in the right way, it can increase a companies productivity and also give it a competitive advantage on the market. Because of this, it’s only sensible that companies try to use every bit of data they have at their disposal to its fullest potential. However, in the past couple of years, data protection has steadily become more and more important.
The demand for proof that companies make security and integrity of information a priority comply with confidentiality guidelines has risen accordingly. This concerns compliance with legal, regulatory and ethical requirements concerning especially sensitive personal data. To help companies and their employees manage data, make informed decisions and generally realize data’s true value a Data Governance Framework that details guidelines and rules can be used as an aid.
Sensitive data isn’t only created during interviews or usability tests but also in less direct ways such as web analytics. Irrespective of the data’s origins, data governance answers questions concerning topics such as “how can data be gathered?” “how do I need to manage data?” “how can I archive data?”. The best way to create a consistent set of rules including everything from the people who are allowed to handle data to technologies and tools that are needed to manage data is to create a Data Governance Framework including all relevant rules.
The Importance of Data Governance Frameworks
In the past data often existed within silos. This means that usually a given set of data was only used by the department or team that gathered this data. Doing this is nowadays considered inefficient and a barrier to effective communication and collaboration. Available data is a highly valued asset within the entire company and not only within the team that gathered it. Considering that numerous employees from different teams should be able to work with raw data or at least the resulting knowledge, Information needs to be structured in a way that is understandable for everybody involved instead of just for that team that originally gathered and evaluated it.
The first thing that needs to be considered is whether access rights have been granted in an appropriate way. Companies need to increasingly make sure everybody complies with policies and rules regarding data usage, the more people have access to that data. The need for a governance system that sets rules for every kind of relevant activity is ideal to regulate the work with user data. This set of rules needs to provide solutions for structuring data and making it usable, address inconsistencies in data that arise from the fact that data is gathered by different departments and answer ownership questions.
By defining a commonly shared set of rules and policies, data governance frameworks streamline the process of communicating knowledge, working with data and facilitate collaboration and therefore increases the value of an organization’s collective data and knowledge.
How to define Governance Policies
As a part of a governance framework “policies” describe a set of rules that ware put in place to safeguard an organization’s data assets. These rules establish different roles, responsibilities and different decision rights such as storage, backup, disposal, trustworthiness, access, accountability, and protection. Consistently making sure that these policies are followed reduces ambiguity and allows more control over the use of data. Thus it fosters the responsible use of and works with information.
In order to define rules, the teams that will work according to the policies such as IT business and marketing should come together, define used and needed data elements. Once the relevant data has been defined, they should discuss and ultimately agree on a set of rules concerning the acquisition, archiving and general management of data. These rules need to adhere to laws and general guides concerning the use of personal data but should also consider ethical issues and reflect the company’s philosophy.
Benefits and goals of Data Governance
Data Governance mainly tries to establish a set of policies concerning the work with data and tries to achieve a high level of adherence to these rules. Effects of this are standardized systems that are used when individuals work with data as well as an increased awareness concerning the handling and use of data which leads to increased accountability. As a result, companies should notice a number of benefits such as:
- Delivery of valid information through improved data quality
- successful, effective and informed business decisions
- Reduced risk of being fined for improper data usage
- Improved compliance and risk management
- Facilitated communication and collaboration with direct team members as well as across departments
- Improved data transparency
- Elimination of redundant research work and reduction of error rates
Designing and implementing a working data governance framework certainly needs a lot of planning involving the right people, tools and technologies. However, keep in mind that usually, you don’t need to start from scratch completely. Most companies already have some kind of rules that are applied to the collection of and work with data. On top of that, the benefits of a data governance framework shouldn’t be neglected. Once it’s been successfully put into place, it resolves a number of data issues, enables everybody using your data to make informed decisions and reduces the chance of you running into legal problems.
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