Written by: David Carneal – Digital Efficiency Consulting Group – DECG
Read Time: 3 min
Good automation isn’t complicated. It’s disciplined. The best designs follow a predictable flow: clean inputs, validate, flag exceptions, approve, and generate the work.
Step 1: Download and quick review
Do a fast scan for obvious issues before the file hits the system. This is cheap insurance.
Step 2: Upload
Provide a simple interface (web upload, shared folder, or integration). Reduce friction so people actually use it.
Step 3: Automated analysis
- Check required fields
- Validate allowed values and ranges
- Detect duplicates and conflicts
- Apply business rules (customer requirements, materials, lead times)
Step 4: Review and adjust
Humans handle the exceptions. Everything else should be one-click approval.
Step 5: Auto-build the orders
Generate production-ready records directly into your system. No retyping, no guessing, no ‘I swear I entered that right.’
Design guardrails (so you don’t automate chaos)
- Audit trail: Log what changed, who approved, and why.
- Fail safely: If something doesn’t validate, stop it and show the reason.
- Start small: Automate one workflow end-to-end before you expand.
- Measure: Track cycle time, error rate, and rework before and after.
A quick scoring rubric
Rate each workflow 1-5 on these. Anything scoring 16+ is a strong automation candidate.
- Volume: How often does it happen?
- Repetition: How standardized are the steps?
- Error cost: What happens when it’s wrong?
- Wait time: How much time is spent waiting vs. doing?
- Rework: How often does it loop back?
Make it survivable: inputs and rules
Most automation projects fail because the rules were never written down. Fix that early: define required fields, allowed values, and what counts as an exception.
- Required: what must be present to proceed
- Allowed: what values are acceptable (lists, ranges, formats)
- Derived: what the system can calculate automatically
- Escalate: what requires approval
The handoff you must eliminate: copy/paste
Copy/paste feels fast until you price in rework. If data moves between systems by human hands, you’re paying for the transfer and the mistakes.
A mini implementation plan (two weeks, not two quarters)
- Week 1: map the workflow, write the rules, define the exception queue.
- Week 2: build upload + validations, then auto-create records for happy-path items.
- Add later: integrations, dashboards, and alerts once the core flow is stable.
What to build first (hint: not everything)
Your MVP should only do two things extremely well: validate inputs and create clean records for happy-path items. Integrations, dashboards, and fancy UI can come after the core is stable.
- MVP: upload, validations, exception queue, create records
- Next: role-based approvals and audit trail improvements
- Later: deeper integrations, auto-scheduling, KPI triggers
Common failure modes (and how to avoid them)
- Too many exceptions: tighten input standards, add drop-downs/lists, improve templates.
- Rule ambiguity: assign an owner to make final calls on edge cases.
- Shadow workarounds: remove the manual path once the automated path is stable
CTA: Choose one process and score it today. If it scores high, don’t buy software yet. Map the rules first.