This article, 1 of 5, will be focussing on the points of the process where data is created. The most important unit of measurement that we have is time, it is our most precious resource, yet something we waste constantly within business. Within these next 5 articles I will explore how you can reduce the time spent from creating data through to using it to drive value, effectively improving what I have named your Cycle Time to Value.

Using the 5S methodology we will be focussing on the first 3. What can we stop, How can we simplify and which owner takes charge to standardise for the group. Finally once all three are complete you can look at automation through things like RPA and AI Agents.

Why process matters

Is your process in the mind of your employees, if the answer is yes then it is more than likely to be broken and inconsistent. Every broken or inconsistent process costs time. That time loss delays insight, blocks decisions and inflates delivery effort. You can guarantee that these processes are create bad or very low quality data.

You can’t fix poor quality data downstream if it’s created badly at the source. Rework becomes routine. Trust in the data erodes. People export to Excel “just to check,” and the whole cycle of trust breaks down.

If you care about reducing time-to-value, start at the source. Look hard at the process. If it doesn’t work cleanly, nothing else will.

Simplify before you standardise

Don’t throw automation at a complex, non-standardised process. It just creates faster failure.

Strip it back. Get clear on the actual outcome. Remove steps that don’t add value. Cut pointless approvals. Eliminate duplication.

If a process takes hours because it’s unclear or bloated, automating it will just replicate the waste at speed.

Get to a point where the process is clean. Only then is it ready for standardisation.

How to standardise effectively for automation

If ten people do the same task ten different ways, you don’t have a process. You’ve got inefficiency.

Start with templates. Build checklists. Turn repeatable tasks into known routines. If a task happens more than twice, it should be documented.

Pull knowledge out of people’s heads. Tribal knowledge creates single points of failure. Document it. Share it. Make it usable by others. You don’t need a manual. Just clarity on how things get done. Especially if you want to automate it for the future.

Where automation fits

Once you’ve simplified and standardised, automation becomes a time-saver.

Look for predictable, repeatable tasks. Data entry. Copy-paste. File formatting. Status updates. These don’t need people. They need structure and rules.

RPA is good for the repetitive tasks. AI agents can handle simple triage. Use them to move work forward faster, and free up your team to focus on things that need human judgement.

Automation works best when the process is tight. If it isn’t, fix the process first.

Data-quality by design

Data quality starts with capture. If the input is messy, the outcome will be worse.

Structure is key. Use digital forms, dropdowns and validation to create reliable data at the source. Avoid free text where possible. Use API submissions instead of manual uploads.

Every time someone “cleans data” later on, it’s a sign the process wasn’t built properly. Get it right from the start, and you save time at every step that follows.

Governance and ownership

If no one owns the process, no one is responsible when it fails. If the process is in the head of the employee and they leave, what are you left with?

Governance doesn’t need to be heavy, but it does need to be clear. Who owns the process? Who approves changes? Who decides if it’s ready for automation? Who monitors performance?

Trust in a process comes from clarity. If people can’t see how something works, they won’t rely on it. Assign ownership, agree the rules and maintain it with purpose.

Conclusion

Process is not administration or unimportant, it’s critical. It’s where value starts. If the process is slow, inconsistent or poorly defined, the rest of your data ecosystem will follow the same pattern.

Want to improve your Cycle Value of Time? Start here.

Stop what doesn’t serve the outcome. Simplify what’s left. Standardise how it’s done. Only then should you automate.

That’s how you build a process that creates value. Making sure you do these things to improve your process is simply not a waste of time.