Data transformation projects Vs Digital transformation projects: What’s the difference?

Most organisations are being asked to change how they work, whether that’s modernising services, adopting AI or making better use of the information that they already hold. “Digital transformation” and “data transformation” are often used interchangeably in these conversations, however they aren’t the same thing.

Digital transformation projects change how your organisation works and delivers services using technology, whilst data transformation projects change how it manages, governs and uses its data.

The two are closely linked. Digital changes work best when the data underneath them is in good shape, so the first often depends on the second. This blog explains what each term means, how they differ and connect, and how exactly to decide which one to start with.

What is a digital transformation project?

A Digital transformation project is the process of using technology to change how your organisation works and delivers services to the people it serves, whether those are customers, citizens, patients or staff.

A digital transformation project involves:

• Introducing new systems, or replacing outdated ones.
• Moving services online or into new digital channels.
• Modernising processes so that they are faster and less manual.
• Changing how teams work, through new tools, skills and ways of collaborating.

Digital transformation aims to provide a better experience for the people in your organisation. That could mean quicker responses, fewer manual steps, or services that are easier to access. All of this depends on the information flowing through those new systems and services. That is where data transformation comes in.

What is a data transformation project?

A Data transformation project is the process of changing how an organisation manages, governs and uses its data, so that it becomes something people can trust, access and act on.

A data transformation project involves:

• Setting a clear data strategy, so the work is tied to what the organisation is trying to achieve.
• Putting governance, security and compliance in place, so data is owned, protected and defensible.
• Modernising the platform where data is stored and accessed.
• Improving data quality, so reports and decisions rest on accurate information.
• Preparing data so it can support AI safely and effectively.

The aim is data your organisation can rely on. Teams spend less time searching for information or double-checking it, and more time using it to make decisions, improve services and put new technology to work. It’s the thinking behind being data confident: knowing what data you have, who owns it and whether you can trust it.

Where digital transformation changes how an organisation works, data transformation changes what sits underneath it. The next section looks at how the two compare.

How do they differ?

Here’s how a digital transformation project differs from a data transformation project:

	Digital transformation project	Data transformation project
Focus	How the organisation works and delivers services.	How the organisation manages, governs and uses its data.
Activities	New systems, online services, modernised processes, new ways of working.	Data strategy, governance, platform modernisation, data quality, preparing for AI.
Who uses it	A digital, operations or IT lead, working with service owners.	A data or analytics lead, working with the people who own the data.
Success Metrics	Services that are easier to use and processes that are faster and less manual.	Data people trust, can find and can act on, with reports that agree with each other.
Example	Launching an online portal so residents can make requests without phoning.	Bringing records held across several systems into one governed platform, so teams work from the same trusted view.

Data governance is where the two differ most. Without it, new systems and platforms can inherit the same unclear ownership and inconsistent data as the ones they replace. With it, everyone knows who is responsible for the data, how it should be used and how it is protected. That is what builds trusted data and, increasingly, use it for AI.

Neither type of project is better than the other, but data governance is what allows digital changes to keep delivering once they go live and allows your organisation to focus on AI readiness.

The connection between digital and data transformation projects

Every digital service runs on data. A new portal, app or workflow takes in information, stores it, shares it and reports on it, so how well it performs depends on how good and how well governed that information is. That’s why the two work best side by side. When data is owned, protected and consistent, digital changes are quicker to deliver and easier to trust.

A data transformation project delivers more when it’s tied to the digital changes already under way. A new system is the ideal moment to agree who owns the data, set the standards and put the right controls in place, rather than adding them later. Governance is the thread between the two. When they are planned together, organisations get services that work well from day one, and data they can rely on as those services grow, including as AI is introduced.

Which one should you start with?

It depends on where the biggest pain is today. Starting with data transformation usually makes sense if:

• Reports from different teams don’t agree, or people double-check figures before using them.
• It’s unclear who owns the data or who can access it.
• Plans for AI have stalled because nobody is sure the data is ready.

For example, imagine a council that launches a new online portal for residents, only to find the records behind it sit across several systems and don’t match. The portal works, but staff can’t rely on what it shows. Agreeing who owns the data and bringing it into one governed place first would have made the portal worth far more from day one.

Digital transformation can lead if your data is already owned, governed and trusted, and the pain is in your processes or in how people access your services. A housing association with well-governed tenant records, for instance, might start by moving repair requests online, because the data behind the service is already in good shape.

Conclusion

Digital transformation projects change how an organisation works and delivers services. Data transformation changes how it governs, manages and uses its data. They aren’t alternatives, and they work best together.

Governance is what ties them together. When ownership, security and compliance are agreed early, digital changes deliver more, and the data behind them can be trusted and used with confidence, including for AI. Knowing which transformation project your organisation needs first is the practical starting point. If you’re not sure, a clear view of how well governed your data is today is usually the quickest way to find out.

How can Simpson Associates help you?

Simpson Associates is a UK data transformation consultancy with 30 years of experience across the public and private sector, including policing, healthcare, charities, local government, financial services and social housing. Whether your organisation is planning digital changes, data changes or both, we can help you work out where to start and what to put in place first.

Our experience sits in industries where trust in data is paramount, so governance is part of everything we do, from ownership and strategy through to platform modernisation, AI and managed services. Our data governance maturity assessment gives you a clear view of your current position and a practical roadmap, so you can plan each change with confidence.

If you’re not sure whether data or digital should come first, we’d love to talk it through. Get in touch with us via email or live chat.

Blog Author: Mehal Patel, Presales consultant at Simpson Associates