Pilot Planning & Evaluation Scorecard

A practical, structured scorecard template to design pilots, capture evidence, and make objective scale/stop decisions. Includes hypothesis framing, success metrics, data collection plan, risk register, weighted evaluation sheet, and a clear scaling checklist with go/stop thresholds.

Purpose

This Scorecard helps teams run pilots that produce comparable, evidence-based outcomes and enable objective decisions about scaling. Use it to clarify the hypothesis, define success metrics, plan how you will collect trustworthy data, log risks and dependencies, and evaluate results using a weighted scoring approach and clear go/stop criteria.

How to use this template

  1. Complete the planning sections before the pilot starts. Be specific about metrics, data sources, timing, and responsibilities.
  2. Collect data consistently during the pilot according to the Data Collection Plan.
  3. Populate the Final Evaluation Scoring Sheet at the pre-defined evaluation point and apply the decision rule.
  4. Document lessons, next steps, and responsibilities for scale, iteration, or close-out.

1. Pilot Hypothesis

Write a concise, testable hypothesis describing the expected outcome and who benefits.

Format: "If we <change> for <scope>, then <measurable outcome> will change by <amount/target> for <stakeholders> within <timeframe>."

2. Scope & Duration

  • Locations / processes included
  • Start date / end date / evaluation date
  • In-scope vs out-of-scope items

3. Stakeholders & Roles (RACI)

List stakeholders and responsibilities (Responsible, Accountable, Consulted, Informed).

  • Pilot Sponsor (A):
  • Pilot Lead (R):
  • Data Owner (R/C):
  • Operations (R):
  • IT/Integration (C):
  • Quality/Safety (C):

4. Success Metrics & Targets

Define 3–6 primary metrics that will determine success. For each metric, declare the target, baseline, measurement frequency, and data source.

Metric Baseline Target Frequency Data Source
Example: On-time delivery 85% 92% Weekly Order system reports

5. Data Collection Plan

Document exactly who collects what, where it is stored, how it is validated, and how missing or inconsistent data will be handled.

  • Data fields to collect
  • Collection method (manual, automated, integration)
  • Owner of collection and validation checks
  • Storage location and access rights
  • Reporting cadence and format

6. Required Integrations, Systems, and Tools

List systems that must be connected or configured for the pilot and their owners (e.g., MES, CRM, ERP, monitoring sensors, dashboards).

7. Training & Standard Work

Summary of training content, trainees, schedule, and where standard operating procedures will be stored.

8. Risk Register

Record known risks, impact, likelihood, mitigation plans, and owners.

Risk Impact Likelihood Mitigation Owner
Data integration delay High Medium Fallback manual collection; escalate to IT IT Lead

9. Resource Estimate

Summarize expected resource needs (FTE-hours, tools, budget) and any dependencies required for scaling.

10. Scaling Checklist (readiness criteria)

Before scaling, confirm the following. Mark status and notes for each item.

  • Standard work documented and validated
  • Training materials and schedule prepared
  • Systems & integrations production-ready
  • Sustained benefit demonstrated over required period
  • Funding and staffing approved
  • Governance & KPIs assigned for steady-state
  • Risk mitigations in place

11. Final Evaluation Scoring Sheet (use at evaluation point)

This weighted scoring approach helps make objective decisions. Customize criteria and weights to fit your organization's priorities.

Criterion Weight (%) Target Actual (1–5) Weighted Score
Customer / service impact 25 +X%
Quality & safety improvement 20 Reduce defects by Y%
Cost / efficiency benefit 20 Save $Z per period
Scalability / technical fit 15 Integrations feasible
Data confidence 10 Reliable & auditable
Organizational readiness 10 Training & governance ready
Total 100 (sum of weighted scores)

Scoring guidance: For each criterion, assign 1 = far below target, 3 = meets minimum acceptable, 5 = exceeds target. Weighted Score = (Actual / 5) * Weight.

12. Decision Rules (example)

  • Scale (Go): Total weighted score ≥ 80% AND no single critical criterion below 60% of its weight.
  • Iterate / Extend Pilot: Total weighted score between 60% and 79% OR data quality issues that require more evidence.
  • Stop: Total weighted score < 60% OR unacceptable safety/quality risk.

13. Final Recommendations & Next Steps

Decision (Go / Iterate / Stop):

Summary of evidence supporting decision:

Assigned owners and deadlines for next actions (e.g., scale plan, further testing, or close-out):

Template Notes & Best Practices

  • Keep metrics few and meaningful; prioritize high-confidence measurements.
  • Pre-declare evaluation dates and decision rules to avoid biasing outcomes.
  • Record raw data and calculation methods so results are auditable and comparable across pilots.
  • Use the same scoring criteria across similar pilots to build organizational learning.

Discussion

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