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The Founder's Desk Decision Intensive · Case Study 02
Decision Intensive Field Operations / Cleaning

Case Study 02

Proof
Before
Purchase

A cleaning business was being sold a $60,000 automation platform. The pitch was compelling, the ROI wasn't clear, and implementation would fall entirely on the founder. We stress-tested the numbers and built a staged rollout — savings had to be proven in real operations before the full commitment was made.

Service
Decision Intensive
Decision at stake
$60,000 + $7,200/yr
Approach
Gated rollout
ROI scenarios modelled
Best case
14 months
Full admin automation achieved. All promised hours recovered. Clean adoption with no edge-case exceptions.
Base case
22 months
Partial automation. Some manual overrides required. Adoption friction adds 3–4 months to payback.
Worst case
38+ months
Poor adoption. Platform doesn't map to business edge cases. Founder time cost exceeds admin savings.
Go/no-go thresholds built in

The Situation

A compelling pitch.
An unclear ROI.

The platform promised to remove the workload of a part-time admin role — invoicing, ordering, customer service. The annual subscription added another $7,200 on top. There was no implementation vendor. Setup and adoption would fall entirely on the founder.

The numbers looked good in the sales deck. They looked less certain when we stress-tested them. 'Remove an FTE' is a different statement to 'save these specific hours, on these specific tasks, at this specific cost' — and only one of those statements is something you can build a business case around.

"We don't want to spend $60k on hope. We want to spend it on something we can prove."

The founder, at the start of the engagement

The Actual Question

Not: is automation
a good idea?

The surface question was whether the platform was worth buying. The actual decision was different: do we commit $60k now, or stage the rollout so savings are proven in real operations before we're fully in?

That reframe opened a third path that the sales conversation had never offered — one where the commitment became contingent on proof rather than promise. That's where the work started.

What We Explored Together

Four paths.
One staged plan.

Considered
Buy upfront. Roll out immediately.
Full commitment, full deployment across the whole business from day one. Fastest path to the claimed savings.
⚠ High risk — sunk cost if adoption fails
Chosen path
Stage the rollout — baseline, pilot, expand.
Proof required at each gate before the next phase is triggered. Commitment becomes conditional on real evidence.
✓ Evidence-triggered expansion
Considered
Delay the purchase entirely.
Tighten manual processes first. Understand the true cost of the status quo before committing to a solution.
~ Medium — slower but lower exposure
Considered
Smaller, cheaper tool stack.
Partial automation with lower upfront cost. Lower ceiling but proportionally lower risk.
~ Medium — reduces scope and ambition

The Gated Rollout Plan

Evidence triggers
the next phase.

A staged plan replaced a binary purchase decision. Each phase had to be proven before the next was activated. Optimism was not a sufficient trigger — evidence was.

Phase 1 · Baseline
01
Establish the baseline
Map the actual time spent on each admin task. Invoice cycle time, error rates, customer response time — measured, not estimated.
Gate to proceed
Baseline data captured across 30 days. Real task-hour data confirmed.
Phase 2 · Pilot
02
Pilot one workflow
Automate invoicing only. Measure the actual hours saved against the baseline. Map exception handling and adoption friction before full deployment.
Gate to proceed
Hours saved ≥ 60% of projected. Exception rate ≤ 15%. Founder time cost within forecast.
Phase 3 · Expand
03
Expand to full platform
Only if gate 2 is cleared. Full platform deployment with the benefit of pilot learnings. ROI now based on real operating data, not vendor projections.
Decision rule
Continue / Pause / Stop thresholds set before a dollar of full commitment is released.

What Was Delivered

Five documents.
One staged commitment.

Decision Brief
One page. The four options, the trade-offs between them, the ROI range under real operating conditions, and a clear recommendation with the staged plan to execute it.
ROI Scenarios
Best, base, and worst-case payback periods — modelled using actual task-hour estimates, not vendor claims. Subscription costs included. Founder time cost included.
Gated Rollout Plan
Three phases, each triggered by evidence. The plan was designed so that the worst-case scenario — failed adoption — would be discovered on $0 of additional commitment, not $60k.
Risk & Unknowns Register
Adoption risk, exception handling, platform lock-in, founder time cost — mapped explicitly before commitment. The things most likely to make the ROI model fall apart, identified in advance.
Measurement Scorecard
Hours saved by task bucket. Invoice cycle time. Error rate. Customer response times. The signals that would tell the founder whether to continue, pause, or stop — set before a single workflow was automated.
Signals tracked across the rollout
Admin hours by task bucket
Weekly
Invoice cycle time
Per invoice run
Error rate by workflow
Weekly
Customer response times
Weekly

What Changed

From a binary decision
to a staged plan.

Before the engagement
A binary 'buy or don't buy' decision. $60k committed at once. ROI based on the vendor's projections. No visibility into what happened if adoption stalled.
→
After the engagement
A staged plan with a clear go/no-go rule. The $60k commitment became contingent on proof, not promise. A controlled rollout replaced a hope-based purchase — with thresholds for continue, pause, or stop.

The founder went from a vendor's sales deck to a business case built on real operating data. The decision didn't change — automation was still the right direction. But the terms changed completely. Evidence had to do the work that optimism shouldn't.

If this sounds familiar

Before you commit — let's pressure-test it.

If you're being sold a significant technology investment and want a decision you can defend with numbers — not just a vendor's projections — a Decision Intensive is where to start.

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