Data Governance Challenges

There is 2.5 quintillion bytes of data created each day. With such vast amounts of data being created every day and new data regulations being implemented around the world, data governance is a process that every organization must manage. However, data governance challenges can stifle implementation and uptake. With the right framework, people and practices, your organization can implement a strategy and process to overcome data governance challenges.


Key challenges for data governance

Creating and enforcing data governance can seem like a daunting and overwhelming task.

Without the proper planning and ownership of data governance as a company wide strategy, efforts can fall flat. The biggest hurdles for data governance can be managed with the right processes. Here are some common data governance challenges:


Roles and accountability

It can be difficult to set roles and built accountability for data in an organization that is siloed and has never had a company wide strategy before. Communication, or a lack thereof, can also stifle new processes succeeding.

Building data governance processes should include managing people, their roles in governance, their access to data and determining who is accountable for implementing and maintaining the strategy overtime. It is now becoming more common for businesses to have a Chief Data Officer, with data governance their mandate.



One of the biggest problems businesses face when establishing a council to oversee data operations is that raw facts and figures are rarely analysis-ready. The information is often painstakingly generated and then held in numerous disjointed databases with no structure; bits and pieces are missing, and there’s no collection protocol in place.

Data governance can’t progress easily without the data being cleansed and normalised. This can be a hugely manual job, but by setting rules and adopting a uniform system across the organization, new data should be manageable.


Silos of data and departments

A huge hurdle to data governance is how data and departments are structured. Often datasets are locked away, only accessible by certain teams. Different departments also operate in entirely different ways and may have no knowledge of the available data and potential value it holds.

Data governance can provide a framework to unlock datasets and break down those silos. Of course, it relies on having strong communication and processes to help teams work together.


Internal blindness

If your organization is only at the start of data governance, another challenge is internal blindness. Internal data governance should be a focus, but if the strategy doesn’t include external data collaboration then your organization is missing out on a big opportunity. Managing external data projects with partners, including legal negotiations, user access and the technical mechanism for data collaboration can be overlooked in data governance strategy. This sets you up for failure in the long term and limits the opportunity of data as an asset.


Benefits of data governance

The nature of today’s world is that every business is a data business. Data governance enables organizations to take hold of data and gain maximum benefit from it, while protecting sensitive information.

Building and implementing a strong data governance strategy has many tangible benefits:

  • Improving data management and valuation
  • Cross department alignment on data processes
  • Enforcing roles and accountability for data management
  • Enabling external data sharing projects
  • Maintaining regulatory compliance
  • Standardising data management and utilisation
  • Reducing inefficiencies and costs for data management


Data governance best practice

Data governance best practice can be broken down into four areas:

  1. Defining people and roles
  2. Overall framework for data management
  3. Framework for data projects
  4. Framework for external data collaboration

Data governance best practice starts with people. Many organizations are creating a Data Governance Council. This team has a mandate to set up the processes and structure for how data is mined, stored, shared and analysed. To be effective, the Data Governance Council should be a cross-functional team with representatives from all relevant areas of the business. It must also be afforded as much influence on the business as a human resources team would have, defining how every branch of the company approaches data and its analysis. This cultural shift requires executive buy-in and support for data governance initiatives.


Once the team is formed, the overall data governance framework can be developed. Your data governance framework should be created with these questions in mind:

  • What is the business’s purpose in collecting data?
  • What are the goals for any use of data?
  • How does the use of data align with the organization’s overarching goals and mission?
  • What policies will be in place for how data is collected and used?


Creating a framework for how data projects should be run will instil an internal process. The Five Safes model from the UK has been touted as an industry standard for internal data management and is a strong baseline for data governance. This model ensures that every data project has five safes considered before analysis starts:

  • Safe projects: Is this use of the data appropriate?
  • Safe people: Can the users be trusted to use it in an appropriate manner?
  • Safe settings: Does the access facility limit unauthorized use?
  • Safe data: Is there a disclosure risk in the data itself?
  • Safe outputs: Are the statistical results non-disclosive?

This is a great starting point for building your own data governance framework. However, for inter-organizational data exchange you also need to consider additional safes to manage external data collaboration: legal and audits.

Creating an external data governance framework will unlock datasets and help drive innovation. Datasets are opened up to external experts and organizations for new insights to be derived with the proper data governance processes in place.


Overcoming data governance challenges

Data governance is a process that requires buy-in from every facet of your organization. There are many challenges that can stall data governance, but you can overcome these challenges with the right team in place and the vision of how your organization can benefit from this process.

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