What problem are we solving?
This is probably the most frequently unasked question, when preparing a data governance program.
Besides being a critical and strategic asset for any organization, data has become also highly fashionable buzzword, and its true purpose is often overlooked. As any other asset in an organization, data’s purpose is to create business value, so any data strategy must be oriented towards the organization’s strategic priorities and key business objectives.
It is essential for any organization to assure that the get the right information is available at the right time to the right people to enable it to gain the necessary edge when facing incredibly competitive markets.
The first step in this direction is to embark on implementation of data governance program, with the purpose of assuring that timely, consistent, and trusted data is provided business to support critical decisions.
However, these are usually overwhelming challenges, highly disruptive and prone to failure.
These failures are usually attributed to a few causes, that can be easily identified during the development of these initiatives:
- Lack of leadership buy-in and commitment: Data governance is a process that needs buy-in from every level of an organization, and it starts with strong executive sponsorship but also from every other stakeholder in the organization, which need to be aligned and committed to the program.
- Lack alignment with business goals and benefits: There is a principle that needs to be respected and seen as a goal: “Data exists to serve the business”. This means that any data governance process must be supported on a strong business case, their objectives anchored on business objectives.
- Lack of focus on strategic data: At an operational level, most of the organizations rely on dozens of different systems, which handle massive volumes of data of every kind of typology daily. Approaching data governance in a global perspective will inevitably lead to a lack of focus, resulting on a misalignment with the business objectives and incapability to deliver value.
- Lack of cross organization involvement: As mentioned above, data governance is a process that needs buy-in from every level and area of an organization and failing to clearly transmit the objectives and benefits of data governance, while inevitably lead to a lack of commitment and involvement.
- Focus on a technological approach: Technology itself will not govern data, technology is but one of the components that supports a data governance program, and often proves useless if seen as an end in itself.
- Time to deliver results: When we look at the characteristics of a data governance program implementation strategy in an organization some characteristics are easily identified, these are expensive, time and resource consuming and span through long time frames, take a sometime to deliver ROI, making it hard, even with a strong sponsorship, to keep the necessary traction to complete all the necessary changes.
Once here, there is still no answer to the question that titles this article: What problem are we solving?
In the previous list there is one critical point missing — Creating value, business value — And this the issue that needs to be addressed from the first moment.
I’m often asked about use cases for data governance — I always have the same answer, there are none, there are no use cases for data governance.
There are business cases.
Repurposing data governance to support business cases, with clear, achievable objectives and stakeholders that are aware of the importance and impact of data, will enable data to be used to deliver those business priorities and objectives.
Data governance is about people, processes, and technology. Is about combining these factors to create business value from data.
As any other asset in the organization data’s purpose is to create value, so any data strategy must be oriented towards the organization’s strategic priorities and key business objectives — Data strategy is business strategy.
All the program and initiatives must be driven and oriented by the business units.
Allowing business to be on the driver seat will enable the creation of effective business value, and it’s compounding the value generated by each of these initiatives, that will enable the success and adoption of data governance organization wide. Solving some of the issues mentioned above and softening or minimizing others.
It’s not about data, it’s about business.
Business is the driver, data and what it produces is the enabler.
The success of any data related initiative is measured on how it impacts business performance. It is measured on how it impacts customer and experience loyalty, offer and innovation, operation efficiency, on how it impacts processes, minimizing inefficiencies and reducing costs, on how in impacts risk and compliance.
The transformation process that leads to a data driven organization must be wholeheartedly supported on the business strategy and objectives, with a strong leadership and business focus, data initiatives will pay for themselves by adding real ROI to business initiatives.
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