The power of Data Governance for Business Transformation

Data is everywhere. Over the last twenty years, the sheer volume of data we capture, process and store from different sources has continued to multiply at a staggering rate. Data is not just about the operational transactions that keep our business running or something we need to store, mask or delete to comply with regulations. Data informs our decision making. Data can help our business to grow, pivot or surge ahead of the competition.

To ensure that we make the right business decisions, understanding and managing our data is imperative, and that’s where data governance comes in.

What is data governance?

Data governance is, at its core, knowing your data and how you use it. While this sounds pretty fundamental, a surprising number of businesses don’t feel confident that they have this knowledge of how data is used by their people, processes and systems.

In 2020, Capgemini’s Data Powered Enterprise Digital Report found that only 25% of business executives surveyed said that their organisation had a complete picture of all the data inventory.

It’s a bit like managing your money. You need to know where it’s coming from (to ensure that you’re not getting it from the “wrong” places), how you’re looking after it and whether you’re using it to invest in the right things to be confident that your money is working for you.

Similarly, data governance is about knowing where your data has come from, how you’re maintaining it and how you’re harnessing its power to help your business thrive.

Do businesses understand their data?

There are a number of reasons why businesses might lose control of their data over time:

• Mergers and acquisitions might not take full account of the data that exists in the organisations being merged and can lead to data duplication, inconsistencies or gaps.
• Lack of control or documentation of IT systems can lead to systems being developed in isolation in an inconsistent way, without knowledge of the wider picture of data inputs and outputs.
• Business reorganisations and restructuring can create gaps in the business or the data. Removing roles might mean that you inadvertently remove processes and data, leaving gaps that need to be filled.
• A silo mentality within organisations can lead to a lack of overall visibility of the data in the organisation as a whole.

Why do we need data governance?

Through the eighties and nineties, data governance was conceptually separate from business operations.

Since the start of the millennium and with the advent of social media and lower connection costs, data is now all around us and data governance has therefore taken on a whole new significance.

As well as capturing data and storing it as part of our operational processes, data is also bought, sold and generated automatically by human activity and machines in huge volumes, including of course data produced and used by artificial intelligence and machine learning. It has become preferable to take a horizontal view of our data rather than the previous vertical model.

As well as changes within organisations and the external evolution of the data landscape, there are regulatory and compliance reasons for understanding and managing our data effectively. GDPR (the EU General Data Protection Regulation) is probably the most well-known example of a regulation that has defined rules for sourcing, storing and processing data, but it’s by no means the only one. Many regulations are sector-specific, such as within the pharmaceutical industry where data is exchanged between organisations and must be structured and transferred in a pre-defined way.

While the data within operational systems such as ERPs is more or less stable, the evolution of the data landscape outside of an organisation increases the complexity and therefore the need for control.

What are the benefits of data governance?

As well as complying with regulations and ensuring that your data is producing accurate insights, the benefits of having a deep understanding of your data landscape include:

• Increased capability to change the business model at enterprise or local level
• Decreased time to market for new initiatives
• Reduced cost of fixing “bad” data, some of which are hidden costs
• Competitive advantage over similar organisations that do not have accurate insights and/or the same agility for change
• Avoidance of fines from regulators
• Use of data as a predictive rather than a reactive force

According to Gartner’s 2019 report “Augmented Data Catalogs: Now an Enterprise Must-Have for Data and Analytics Leaders”:

“Organizations that offer a curated catalog of internal and external data to diverse users will realise twice the business value from their data and analytics investments than those that do not.”

And in their 2021 report entitled “Market Guide for Active Metadata Management”, they state:

“Through 2024, organizations that adopt aggressive metadata analysis across their complete data management environment will decrease time to delivery of new data assets to users by as much as 70%.”

What are the different elements of data governance?

Data governance is a broad concept, but it can be broken down into the following topics:

• Data discovery and lineage
• Data catalogue
• Business glossary
• Data quality
• Master data management
• Data lifecycle management
• Data protection.

A more recent concept that has entered the sphere of data governance is data mesh. This is an architecture that decentralises data to enable more specialised, domain-based ownership and insights, moving away from a centralised approach.

Which tools can help us govern our data?

It’s no longer possible for humans to manage all aspects of the data within an organisation, so data governance requires tools to help with this significant task.

At the foundation of effective data governance is the data catalogue, which brings together a comprehensive view of the data within an organisation through multiple lenses.

There’s a wide range of data governance tools available, some of which are highly specific (e.g. data catalogue creation) while others are modules within larger applications (such as master data management within an ERP).

Some of the major vendors in the data management tool space are:

• Informatica
• Alation
• Collibra
• Purview
• Semarchy
• Profisee

Some of these solutions started out with very specific, standalone functionality, such as data quality, but over time evolved to encompass a wider remit as the concept of data governance gained ground. Most of these are provided as SaaS (Software as a Service) or PaaS (Platform as a Service) solutions.

How do we know which tools to use?

Capgemini has been helping businesses with their data governance for many years and has partnerships with over ten industry-leading vendors. With its centre of excellence providing consultation, implementation and operational support, Capgemini offers the competency and experience to help your business select the right combination of tools to meet your data governance needs.

How do we implement data governance?

Data governance is an organisational problem rather than a technical problem, making it a journey rather than a one-time implementation.

A data-savvy, forward-looking entrepreneur starting a brand-new company could put all the right pieces of the puzzle in place at outset, and this will stand them in good stead for a while. However, the continuously evolving data landscape means that a business must have the right methodologies and assumptions available to maintain governance over time and continue to use data to their advantage.

A phased approach to data governance is often recommended, starting with one tool and moving to others as needs evolve. There’s no one-size-fits-all solution, and Capgemini always tailors its recommendations to suit the client based on country, business sector, applicable regulations and data complexity.

Conclusion

By gaining a comprehensive understanding of their data, business leaders can benefit from accurate insights, improved business agility, reduced time to market and significant cost savings through not having to fix bad data.

Given that only 25% of businesses are estimated to have a comprehensive understanding of their data, this means that there’s a huge opportunity for companies who manage to master data governance to gain a competitive advantage.

In an ever-evolving world, effective data governance helps companies to harness the power within their data and change their business at the flick of a switch.