To support their global business strategy, our client (a prominent Belgian energy producer and supplier) has a clear ambition to become a data-driven organization. More than ever, data plays a crucial role in many of their business processes. Whether we are talking about an up-to-date view of the amount of energy produced, a solid forecast of energy production and consumption, or accurate and reliable financial reporting, … all depend on data. Moreover, with energy prices hitting all-time highs, the 2022 energy crisis further underscored the urgency for our client to achieve their ambition.
Our client realized that concrete steps were required to increase data maturity and focus on embedding data governance practices into their day-to-day processes. They selected Datashift as their guide to take the proper steps to meet those challenges and pave the path for the years to come.
We started our five-step data governance journey with 20+ interviews involving stakeholders from all our client's departments. The output of those interviews, facilitated by well-structured questionnaires, enabled us to jointly shape a vision of the data-driven organization to be developed and assess our client's current and target data maturity.
Next, we worked with all relevant stakeholders in 10 thematic workshops. The objective of those workshops, which were guided by the vision and maturity assessment, was to build data governance awareness on the one hand and define use cases on the other hand. The outcome of those workshops was a backlog of 60 use cases that can generate medium- or long-term business value for various stakeholders.
We then retained 15 use cases to co-create a first-year data governance roadmap with all key stakeholders. For each use case, the objective was to demonstrate the business value that data governance brings and to gradually embed data governance capabilities (including roles and responsibilities) into our client’s organization.
This use-case-driven roadmap enabled us to formalize the required data governance operating model in a non-invasive way and design a first blueprint. In parallel, a selection of data governance tools was recommended based on the high-level requirements captured during the interviews and workshops. Our client was not yet using a data governance tool, so we recommended to start with an open-source ecosystem strongly interconnected with their cloud data architecture (AWS, Snowflake, DBT, …). Datahub (https://datahubproject.io/) was selected as the business glossary and data catalog, while Great Expectations (https://greatexpectations.io/) was chosen as the data quality framework. As soon as business value from the use cases has been proven, an evaluation of the needed tooling will be performed.
The approval of this first-year data governance roadmap kicked off the implementation phase. The implementation itself was supported by a persona-based change management plan, enabling everyone involved to grow into new data governance roles and inspire buy-in from the various stakeholders.
By focusing on implementing data documentation, data quality, and data lineage capabilities for the specific use cases included in the data governance roadmap, we demonstrated the business value that data governance brings to our client’s stakeholders. Examples include revenue loss prevention thanks to a data quality cycle on contract data, increased accessibility and efficiency towards customers as a result of data documentation and a data quality cycle on contact data, and optimized hedging at lower costs thanks to the implementation of data documentation and a data quality cycle to increase the accuracy of the forecast model, …
In addition to those tangible business benefits, we helped increase data governance awareness and formalize roles and responsibilities linked to the implemented use cases. Throughout the entire process, the persona-based change management plan proved to be an essential lever to achieve this outcome.