If You Counted the Hours, You’d Be Horrified.
Your production planner copies job data from the ERP into a scheduling spreadsheet every Monday. Your quality engineer transcribes test results from the machine display into a report template every shift. Your maintenance team logs work orders on paper forms that someone re-types into the CMMS every Friday. Nobody planned these rituals. They just accumulated. We eliminate them.
The Work Nobody Sees, That Everyone Pays For
There’s a category of work in every industrial operation that nobody talks about in strategy meetings. It doesn’t appear on the org chart. It isn’t tracked in any KPI dashboard. But it consumes thousands of hours every year from the people you can least afford to lose time from: your planners, your quality engineers, your maintenance leads, and your production supervisors.
It’s the work between the work. Copying data from one system to another. Assembling reports from three different sources. Manually formatting compliance documents. Entering the same information into two databases because they don’t talk to each other. Checking whether an email was sent, a form was signed, a file was uploaded.
None of these tasks are complex. Any individual one takes 5 or 10 minutes. But they happen hundreds of times a week, across every shift, in every department. And they never stop.
What this actually looks like:
“The Monday morning ritual”
Your production planner spends the first two hours of every week copying last week’s production data from the MES export into a management report template.
“The quality transcription loop”
Inspection results displayed on the machine screen, copied to a paper form, then typed into the database. Two manual steps. Two error opportunities. Every batch.
“The compliance assembly project”
Every quarter, someone assembles a compliance report by pulling data from five sources, formatting it, cross-checking, and producing a PDF. It takes a week. It should take five minutes.
“The maintenance paper trail”
Work orders written on paper, executed on the floor, entered into the CMMS days later. By the time the data is digital, it’s too late to use.
“The approval bottleneck”
A document needs three signatures. The chain is email-based. It sits in someone’s inbox for two days because they didn’t see it between 40 others.
First, We Find Where Your Time Actually Goes
Most companies dramatically underestimate the volume of manual work in their operations because nobody has ever measured it. Individual tasks feel small. It’s only when you map every manual handoff, every data transcription, and every paper-based workflow across the entire operation that the true cost becomes visible.
What our automation analysts do in the Analyze phase:
Process time mapping
We shadow your team’s workflows and document every manual step: what triggers it, how long it takes, how often it happens, what errors it introduces.
Automation opportunity scoring
We score each manual process by volume, effort, error rate, and complexity. High-volume, low-complexity tasks go first.
ROI modeling
For each automation candidate, we calculate hours recovered, error reduction, and downstream value unlocked.
What you walk away with:
Process Automation Map
Every manual process documented with frequency, duration, error rate, and owner.
€15–25k fixed fee (included in Discovery)
Priority Matrix
Processes ranked by automation ROI. Quick wins identified. Complex processes phased.
4 weeks (part of the standard Discovery scope)
ROI Forecast
Hours recovered per year. Error rate reduction. Payback period for each investment.
We don’t just list what could be automated. We quantify the ROI so you can decide with numbers, not intuition.
Then, We Eliminate the Work Your Team Shouldn’t Be Doing
Automation works differently from the other four disciplines. Engineering builds platforms. AI Agents provide intelligence. Integration connects systems. Automation sits on top of all of them and removes the human effort that shouldn’t exist. It’s the amplifier — the discipline that makes everything else faster, more reliable, and more scalable.
Automated Today. Still Automated Next Year.
An automation that saves 20 hours a week in January can save zero hours by June if nobody maintains it. Systems update. Forms change. Processes evolve. New edge cases appear that the original rules didn’t anticipate. The Operate phase ensures your automations stay current.
Performance Monitoring
Every automated workflow monitored for completion rates, exception rates, and processing times. Dashboards show which automations are performing and which need attention.
Continuous Improvement
Quarterly reviews that identify new automation candidates, optimize existing workflows, and adapt rules to changed processes. Your automation portfolio compounds in value over time.
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Change Management & Training
When an automation changes how someone does their job, we manage the transition. Training materials, process documentation updates, and hands-on support to ensure adoption.
The compounding effect: the best automation programs don’t stop after the first wave. Each round of automation frees up time that reveals the next round of manual work worth eliminating. Companies that stay in Operate typically automate 2–3 new processes per quarter.
The Tools Behind the Automation
We choose automation tools based on what’s already in your environment and what the process requires. No vendor lock-in. No forcing everything through one platform.
Why Make is our primary platform: Make provides visual workflow design, 1,500+ pre-built connectors, and a pricing model that scales with usage. It’s powerful enough for complex multi-step automations but simple enough that your internal team can extend and maintain workflows after our Operate phase.
Case studies
Strategic Partnership
Since mid-2022, Cadran has been the strategic technology partner for HOMAG Group — the world’s leading provider of integrated solutions for woodworking production. We co-develop and maintain materialManager and materialManager Advanced, HOMAG’s web-based applications for centralized material data management, inventory control, and automated allocation across edgebanding and panel processing operations.
What we built together: seamless data import from Excel, ERP systems, and industry software; real-time inventory tracking with automated material allocation and booking; direct integration with HOMAG machines and production planning software to optimize cutting and nesting; and automatic saw parameter adjustment based on materials, tools, and quality requirements. The result: automated material allocation and optimized cutting reduced waste by up to 15%, while real-time inventory tracking eliminated manual errors and improved operational accuracy.
Homag
Read Case Study
Cadran co-develops Ceiton’s enterprise workflow and resource management platform, serving broadcasters from MDR to Red Bull Media House with scalable project management and scheduling automation.
Ceiton Technologies — CEITON Workflow & Resource Management Platform
Read Case Study
Outcome metrics
Waste reduction via automated material allocation (HOMAG)
broadcasters Using Cadran-built workflow automation (Ceiton)
Typical reduction inmanual processing time
End-to-end cycle reductionfor AI-driven BPA
Who Automates Your Operations
Automation Architect
Designs the automation strategy. Maps processes, identifies candidates, selects platforms, creates the implementation roadmap.
Process Analysts
Shadow your team’s workflows and document every manual step. Quantify time, frequency, and error rates.
Automation Engineers
Build the workflows, bots, and processing pipelines. Specialists in Make, UiPath, Power Automate, and custom automation development.
AI Engineers
Build the AI-driven BPA layer: LLM integration, agent orchestration, process mining, intelligent decision engines. Cross-disciplinary with the AI Agents team.
QA & Monitoring Engineers
Test automated workflows against edge cases. Build monitoring dashboards. Ensure that automations handle exceptions gracefully.
Cross-disciplinary by nature
Automation projects always involve Integration (to connect the systems being automated) and often Engineering (for custom development) and AI Agents (especially for the new AI-driven BPA category). The Automation team orchestrates across disciplines.
Questions We Get Asked About Automation
No. It replaces the tasks your people shouldn’t be doing. Your quality engineer didn’t study for four years to transcribe numbers from a screen to a spreadsheet. Automation gives these people their time back for the work that actually needs human judgment: investigating quality deviations, optimizing schedules, solving novel problems.
Most RPA failures come from automating on top of unstable processes. Our approach is different: we use API-based integrations wherever possible, we build exception handling into every workflow, and our Operate phase includes monitoring that catches breaks before they cause downstream problems. When a bot does break, it escalates to a human rather than failing silently.
Yes — fundamentally. RPA automates discrete tasks within an existing process by mimicking what a human user would do on a screen. AI-driven BPA goes further: it uses generative AI, agentic systems, and process mining to redesign the process itself. RPA asks “how do we automate this step?” AI-driven BPA asks “should this step even exist, and if so, what should it look like?” The two are complementary — RPA handles the deterministic work, AI-driven BPA handles the judgment work and the process design.
That’s more common than you’d think — and it’s actually the first thing we address. Discovery documents your processes as they actually are, not as they’re supposed to be. Often, the act of mapping a process reveals unnecessary variation that can be standardized before automation. We don’t automate chaos. We help you simplify first, then automate.
That’s what Discovery delivers. We score every manual process by volume, effort, error rate, and complexity. Quick wins (high volume, low complexity) go first. Complex, high-value processes get phased into later quarters.
Quick wins typically pay back within 2–3 months. A single RPA bot automating a 2-hour daily reporting task saves ~500 hours/year. At your fully loaded labor cost, that’s often €15–30k/year recovered from a single automation costing €5–10k to build. AI-driven BPA initiatives take longer to deploy (typically 3–6 months) but deliver larger end-to-end cycle reductions.
You should start small. Pick one high-frequency, low-complexity process from the Discovery matrix. Automate it. Measure the result. Show the before/after to your team and leadership. Then expand. We’ve seen clients go from one automated workflow to thirty within 18 months.
Ready to see what your data can do?
Start with a conversation. No pitch deck. No obligation. Just a focused discussion about your operations and where AI could make the biggest difference.