How to run a scheduling software proof of concept on your own data
How to run a scheduling software proof of concept on your own data: what to share, a two-week timeline, success criteria and how to judge the result.
Key takeaways
- A proof of concept on your own data beats any demo on sample data.
- You need an extract, not an integration: auditors, competences, availability and one or two months of audits.
- Agree success criteria before the run, so the result can't be argued afterwards.
- Judge the plan side by side with reality, and involve the planners who built it.
A scheduling software proof of concept runs the vendor's engine on an extract of your own auditors, competences and audits, then compares its plan with how your planners built the same period. It typically takes two weeks, needs no integration, and should be judged on time taken, share auto-allocated, rule compliance, internal utilisation and travel.
Why sample-data demos mislead
Every scheduling tool looks good on its vendor's sample data. The data is clean, the rules are simple and the edge cases have been designed out. Your programme is different: half-maintained competence records, clients with unusual windows, integrated audits that need a team, auditors who can only work certain days.
A proof of concept removes the guesswork. The vendor runs the engine on your data and shows you the result next to how your planners actually scheduled the same period. If it can't handle your edge cases, you find out before you sign, not after.
If a vendor won't run on your data, that tells you something.
For the bigger picture, see our complete guide to audit scheduling software.
What data to share
| Data | What it includes | Tip |
|---|---|---|
| Auditors | Name or ID, location, internal or external, day rate | Pseudonymise names if you prefer |
| Competences | Standard, technical area, role and validity dates per auditor | Include expired entries; they test the rules |
| Availability | Leave, training and known unavailability | A simple list of blocked dates is enough |
| Audits | Client, site, standards, codes, duration, window | One or two months of real audits |
| Rules | Rotation, conflicts, travel limits, internal-first | Write them as plain sentences |
The extract usually comes from your certification platform or planning spreadsheet. No integration is needed at this stage, and data can be shared under an NDA and deleted afterwards.
A typical two-week timeline
- Day 1Kick-offAgree scope, rules and success criteria; share the extract.
- Days 2–5Data reviewThe vendor checks the data and flags gaps such as missing competences or windows.
- Days 6–9Engine runsThe period is allocated, re-run with corrections and tested with changes.
- Day 10Side-by-side reviewYour planners compare the engine's plan with the real one, audit by audit.
Who to involve
A senior planner
Knows the rules and the edge cases, and judges whether the engine's plan is realistic.
An operations lead
Owns the success criteria and the business case.
A data contact
Produces the extract, answers questions about gaps and spends about a day on it.
IT or security
Reviews how data is shared, processed and deleted.
Keep the group small. The planner's verdict matters most: if the people who build the plan today trust the engine's result, adoption follows.
Success criteria to agree up front
- ✓Time to allocate the period, compared with your current process.
- ✓Share of audits allocated automatically without planner intervention.
- ✓Allocations that break a competence, accreditation, rotation or conflict rule: target zero.
- ✓Internal utilisation and subcontracted days compared with reality.
- ✓Travel distance compared with reality.
- ✓Time to re-plan a realistic change, such as an auditor off sick for three days.
Write the targets down before the run. It keeps the evaluation honest on both sides and gives you the numbers for your business case.
Proof of concept, pilot or trial?
Keeping the stages separate protects you. Each ends with a clear decision, and you only move on when the previous question has a good answer.
| Stage | Question it answers | Typical length |
|---|---|---|
| Proof of concept | Can the engine plan our real audits within our rules? | Two weeks |
| Scoping and integration | How will it connect to our systems and procedures? | Four weeks |
| Pilot | Does it work in production for one division? | Eight weeks |
Mistakes to avoid
MythWe should clean all our data before starting.
RealityShare it as it is. Finding the gaps is part of the value, and the vendor should help fix them.
MythA free trial login is the same thing.
RealityClicking around an empty tool tells you little. A proof of concept runs your real programme.
MythThe engine must match our current plan exactly.
RealityYour current plan contains compromises and errors. Judge whether the engine's plan is valid and better, not identical.
Find out how TIC scheduling software handles this, or see audit scheduling software for certification bodies.
What did customers learn from theirs?
One global assurance provider's proof of concept scheduled 305 largely integrated audits in 11 min 24 s, formed 22 teams where no single auditor was qualified, and found 46 historical audits allocated without the required competence.
ScheduleAI starts every engagement with a free two-week custom demo on your own data: your audits planned by the engine and compared with how they were planned in reality, before any licence.
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What is a scheduling software proof of concept?
A short evaluation where the vendor runs its engine on an extract of your real data and compares the result with your actual plan.
How long does a proof of concept take?
Typically two weeks, with no integration needed.
What data is needed?
Auditors, competences with validity dates, availability, one or two months of audits and your scheduling rules.
Is our data safe during a proof of concept?
It should be shared under an NDA, processed on certified infrastructure and deleted afterwards. Ask the vendor to confirm in writing.