Data and knowledge fitness as a transformation enabler 

Or the opposite, and perhaps worse: we delay necessary initiatives because our data house isn’t in order. “We’re not ready” is often a reflection of data integrity and resource readiness.

Individual initiatives and larger transformation programmes require data and knowledge fitness, not as a “later” thing and not as a checkbox, sprint, or cosmetic dashboard project. It’s not even “done” once it’s cleaned up for go-live.

Data is fitness. Knowledge is fitness.

And fitness is never one-and-done.

If you’ve ever trained for anything — a race, a recovery, a reinvention — you know this: you don’t show up cold and expect to perform. You build strength, develop habits, and live the discipline. You sweat the small stuff so your body (or business) doesn’t break when the pressure is on.

The world of work is increasingly digital, distributed, and global. Whether your business is big or small, the expectations of the workforce are higher than ever and always evolving — consumer experiences set the bar high for frictionless and intuitive work experiences, personalisation is table stakes, and generational shifts in the workforce mean different value systems must be considered. 

The opportunity to build systems and experiences to expectation is about more than serving stakeholders. The evolution of HR shared services, AI-first and agent-supported workflows, and direct access to employee services means we’re creating capacity for focused and strategic work, empathy, and more relational interactions. 

Data and knowledge fitness can also reduce enterprise and people risk by ensuring that the content, insights, and decisions generated — especially by AI — are grounded in accurate, current, and contextually relevant information. Without it, you risk misinformation, eroded trust, and actions that amplify bias, inequity, or legal exposure.

Most executives agree that their best competitive and strategic advantage lies in how they maximise and optimise their most valuable assets: people being your top one. For example, many employees hold institutional knowledge of the enterprise.

Mismanaged, redundant or trivial, conflicting or outdated knowledge is said to cost a business an average of 25% of its annual revenue, according to Bloomfire’s Value of Enterprise Intelligence 2025 report. Treating knowledge as both evolving and revenue-driving leads to 47% higher success in achieving objectives and key results (OKRs), 39% improvement in the speed and efficiency of teams, and 23% lift in productivity as measured by revenue per employee. 

So yes, fitness pays.

Mercer supports thousands of transformation and technology initiatives, so we know: we rarely start with the raw materials we need to succeed. It’s easy to think of change as design, tech, timelines, communications, and training. But the real foundation is data and knowledge by design — how it's collected, governed, used, and whether it's fit for purpose.

And right now, that purpose is evolving faster than ever.

We’re rethinking how work gets done. What it means to be productive. How humans and machines co-create. We’re shifting from rigid hierarchies to dynamic skills ecosystems. From manual workflows to automated, AI-augmented value streams. From generic experiences to personalised, meaningful ones.

Fitness isn't a one-time activity — a single workout. It's a lifestyle change, a set of habits you form to stay healthy and ready for the future. You can start by learning more about your body, nutrition, different exercises and workout styles, but at some point, you need to just jump in. Start exercising within some reasonable limits to prevent accidentally tearing a muscle or overworking yourself.

Then, you can tweak your routine, choosing the right exercises and number of sets and reps to reach your goals, or modify your diet, consuming more or less calories and increasing or decreasing your macros based on what's going to be the healthiest and most effective based on your goals. You can optimise all of that further as your goals change — and they will change as you move forward. 

It's an interesting parallel because in fitness, exercise is the thrilling part, the part that gives you the adrenaline rush or the dopamine high and makes you feel good. Diet, on the other hand, is the part a lot of people struggle with — counting calories can be problematic, adjusting macros feels like work, and doing all of that while eating food that tastes good can seem difficult. But diet is 80% (or more) of the equation with fitness. What you put into your body is absolutely essential to fuel what you want to get out of it.

When preparing to deploy new technology or use AI, setting up dashboards and workflows, building custom generative pre-trained transformers (GPTs) and releasing bots is a lot like exercise. You need to work your way up to it, but it's the part that's thrilling and exciting, like hitting a new personal record (PR). The data, both structured and unstructured, that you analyse and train models on is much more like nutrition. 

If you don't count your calories and monitor your macros — like having the right fields and valid inputs in your organisation and people data, and ensuring your knowledge content is up-to-date, accurate, and useful — then you're not going to hit that PR, and you might even get hurt trying.

Together, they drive engagement, unlock capacity and key capabilities, and lead to material ROI on labour and technology investments.

Here’s the thing: when data is an afterthought, everything downstream suffers. AI models hallucinate. Automation triggers the wrong workflows. Compensation decisions miss the equity mark. Talent strategies collapse under false assumptions. And employees disengage because their lived experience doesn’t match the promises we made.

This isn’t just about efficiency — it’s about trust, ethics, and risk mitigation. A workforce that doesn’t believe the system “sees” them accurately will never lean in. A system that operates on outdated, inaccurate, or biased data will never be fair. And an enterprise that can’t trust its insights will never move fast enough to compete.

Together, they drive engagement, unlock capacity and key capabilities, and lead to material ROI on labour and technology investments.

This isn’t about hygiene for hygiene’s sake. It’s about designing and maintaining data systems that can keep up with the velocity and complexity of modern work.

So how do you build real data and knowledge fitness into your transformation agenda?

If your organisation is serious about scaling AI, delivering personalisation, redesigning work, or building trust in a fast-changing environment, your data and knowledge can’t just be available — it must be accurate, agile, and alive. Treat it like the muscle it is: build it, train it, and keep it fit.