Speaking one language across a big organisation

By Merel Bulder


All over the world, organisations are swimming in data that is growing exponentially every day. Data is often created and used in different locations, departments and systems, without any alignment at all. But a lack of shared standard, policies and processes leads to siloed ways of working and inconsistencies – this all conspires to erode the value of data.

Good data governance – the planning, oversight and control of data management and uses of data – is the foundation for a data driven organisation, so is a priority for many organisations. It ensures that data can be trusted, is of good quality and can be used consistently across the organisation.

A large brewing company wants to be the best-connected brewery in the world and run its business in the best possible way – to do this the brewer needed to create data consistency so one data language could be used across its organisation. This was proving to be a challenge as it is an international company with locations across multiple jurisdictions, all with different systems and processes. Having one voice requires standardisation in data categorisation, systems and processes, but a nuanced approach was required to understand which data could be used centrally across the business and which local data was required to allow the business to continue to operate efficiently.


Valcon was chosen to partner the brewing company to support the implementation of a data management solution that would enable the firm to speak ‘one language’ due to its deep data experience and expertise.

To do this in a structured way – the team, comprising Valcon data experts and the client’s own data professionals – started with the development of an integrated framework to organise the information, bringing together data from disparate sources. The framework also covers the people, processes and technology needed to facilitate data modelling, the development of business definitions, data quality, data standards and policies and master data management (MDM).

Within the framework, the team standardised definitions across the business to ensure consistency. The framework also mapped out ‘rules’ – for example, deciding the different variables needed for customer data (buying patterns, products purchased etc.) – and defined the inter-relationships between data. This framework helped to establish a common business language.

Data governance is a continuous process, where new guidelines are documented and existing guidelines are changed or removed as needed.  The data governance team established a way for data users to raise new requests and make changes to the business language. After a request was raised, the data was mapped against the guidelines, exploring the definitions and business rules to identify areas that were weak or missing.

When gaps were found, it was decided if the change would be made and if guidelines needed to be created. This decision was made based on factors such as added business value, and assessments to gauge the impact any change would have for stakeholders. This helped to ascertain the consequences on the business if a specific standard was implemented.

Ultimately, the team is the central point, responsible for everything being updated and documented, fielding questions from users and systems and making decisions that will influence the common business language.


  • One voice: people across the organisation now have the same understanding of what data means and how they can use it, which makes communication and collaboration between projects and countries much smoother. It ensures everyone is singing from the same hymn sheet.
  • Improved data quality: as the common business language is the basis for assessing the quality of data across the organisation, it has been easier to assess the quality of the data available. But also, the developed guidelines have helped to clean data and improve business processes. Improved data quality has led to more trustworthy data.
  • Insightful management information (MI): without standardisation, it was extremely difficult for the company to derive MI as without standardisation, a lot of the inferences from the data were meaningless. With a common business language established across the organisation and the framework in place, it is much easier to pull meaningful reports and make informed decisions.
  • Scalability: having standards on how to use data makes it easier for tools and departments to work together and lift and shift tools and processes to optimise the way of working and be able to better serve customers. It also helps improve business agility and helps on strategic business activities, such as acquisitions.
  • Agree business goals: it was difficult to have common goals previously as data was so fragmented before – but data governance has facilitated that process. Standardisation has enabled the business to think more strategically.

If you want to speak to someone at Valcon about how your organisation can start to speak one language using data, please get in touch [email protected]

Case Studies