The cost of chaos and how to fix it

Roger Zouein at Mithryl explores why chaotic technology can have an adverse effect on productivity and what organisations can do to solve this problem

 

Walk into almost any workplace, a hospital, warehouse, or bank, and you will find the same thing: smart people, working hard, losing hours to nonsense. Reports that take all morning to compile. Meetings that should have been an email. Spreadsheets that need “one more tweak” because two systems refuse to agree on what reality looks like.

 

It’s the quiet drain of time and energy that happens when people cannot find what they need, when they need it.

 

 

The hidden epidemic

At Mithryl, we asked 1,000 manufacturing workers in the UK about their day. Ninety-one percent said large parts of it go on tasks that could have been avoided. Nearly half described those tasks as demotivating. A quarter said it makes them want to find another job.

 

People don’t struggle to do their jobs because they’re unskilled. They struggle because the information they need is scattered across half a dozen tools that don’t talk to each other. Forty-four percent of manufacturing workers told us they can’t easily find the right “how-to” or instruction when they need it. The same share said their company suffers from data and expertise silos.

 

Swap “operator” for “analyst” or “nurse,” and the picture barely changes. Most organisations have grown their digital footprint by necessity, not design. Layers of tools and file shares have piled up over the years, like silt. Each department runs its own stack. None of them speak the same language. That is how you end up with five versions of the truth and an hour of your life gone to reconciling them.

 

 

The real cost

When information is hard to find, decisions slow down. When teams can’t see what others are doing, problems get solved twice or not at all. And when knowledge lives only in people’s heads, it walks out the door every time someone changes jobs.

 

Across sectors, the pattern is identical: silos create delays; delays kill momentum; lost momentum erodes trust. The result is billions in wasted wages, missed opportunities, and frustrated employees who could have been doing work that matters.

 

 

Smarter processes start with simple rules

So how do you fix it? You don’t need a billion-dollar digital transformation - just a few consistent habits that make information flow.

 

Start by putting everything in one place. Choose a real hub, not another folder, and pull in what already exists: SOPs, inspection sheets, maintenance logs, contracts, approvals, key emails. Make it searchable and linkable so that if an incident note mentions Line 3, the line record should be one click away. That habit alone kills the “ten tabs open for one answer” routine.

 

Once it’s there, give it some order. Agree on a few categories everyone understands, for example: Machines, Processes, Documents, People, Activities, Customers. Tag what you collect with these labels. This gives structure to chaos. A PDF becomes a Document tied to a Project. A task becomes an Activity linked to a Client. Structure turns a dump of files into a system of meaning.

 

Next, connect the dots. Information isn’t useful in isolation. Link it so that every piece points to what it affects. A meeting note links to the contract it discussed. A maintenance log links to the equipment and operator involved. Those connections form a map of how your organisation actually works, not the idealised version drawn in PowerPoint.

 

Only then should you bring AI into the picture, with context and not in isolation. Generic chatbots don’t know what your data means, but when you feed them structured, linked information, they can reason across departments, spot trends, and recommend actions backed by evidence. Without context, it’s just confidently wrong text.

 

Finally, automate the boring stuff. Look for the repetitive jobs that add no value -report exports, manual re-typing, reconciling fields that already match somewhere else - and hand them off to simple no-code tools. A few seconds saved per action compounds into weeks across a year. In our survey, 62 percent said they would do key tasks better if reporting and manual data work were automated.

 

 

The moment data starts making sense

You might be wondering what kind of system can store, label, and connect all of this in one place. That is where knowledge graphs come in.

 

A knowledge graph maps the relationships between machines, materials, documents, people, and processes, creating a connected picture of how your factory truly works. At its simplest, it is made up of “nodes” (things) and “edges” (relationships). Those few labels you defined earlier become node types in the graph, helping define what each piece of data is and how it fits together.

 

The result is a living model of your knowledge, one that AI can understand, analyse, and learn from.

 

 

Why this matters now

Everyone is under pressure to do more with less. Before adding another dashboard, fix the foundations. Without structure, even great software becomes costly clutter. With structure, good tools pay for themselves.

 

In our data, workers asked for three things: less manual reporting, one place to find what they need, and fewer silos with leaders who act on sensible suggestions. 

 

---

 

Roger Zouein is Co-founder and CEO of industrial data platform Mithryl. Its product, Anvil, unifies system, machine, and document data into one connected knowledge graph, giving teams the context they need to work faster and smarter.

 

Main image courtesy of iStockPhoto.com and selimaksan