Data Collection Plan guide & examples

What is it, and why use it?

A Data Collection Plan specifies what will be measured, how, where, by whom and over which cases and period.

It makes data reproducible and useful before a team invests effort in collecting it.

Explore the Data Collection Plan features and local-file workflow

When to use it

Use it when establishing a baseline, testing a change or resolving inconsistent measurement definitions.

When another tool fits better

Use CTQC first if the requirement is still vague. Use Time Study for timed observations or Control Chart for subsequent time-ordered analysis.

Before you start

An improvement question and candidate metric.
A source that can be used with appropriate permission and privacy controls.
A practical sampling period, owner and data-quality checks.

Use fictional or approved non-sensitive information. Do not include patient details or proprietary records in practice worksheets.

Step-by-step in CI Tools

Define the metric objective, operational definition and unit. Include numerator/denominator and inclusion/exclusion rules for rates.
Specify source, measurement method, sample size or period, frequency and responsible role.
Add data-quality checks and measurement limitations; test the plan with a small set of fictional records.
Import reviewed CTQC definitions as copies without replacing existing measures. Review definition-check warnings, units and formula grammar.
Collect observations through the agreed process outside this planning worksheet, then save the plan and retain editable copies for future reviews.

Write the measure before collecting records

State exactly what counts, the eligible population, timing boundaries, source and unit. Arithmetic-only formula checks do not execute imported spreadsheet or JavaScript expressions, and they do not verify whether the definition answers the improvement question.

Completed worked examples

Demonstrations only: all organizations, observations, targets and results below are fictional. They are not clinical instructions or universal performance standards.

Healthcare operations — fictional

Referral completeness baseline

Starting information: A fictional office plans a five-day baseline review.

Completed demonstration: Referral completeness baseline
Population	All eligible referrals received during staffed hours
Metric	Referrals requiring missing information / eligible referrals × 100
Quality check	Two reviewers independently apply the definition to ten fictional records before collection

What the result means: Agreement on borderline cases improves reproducibility. The plan does not itself collect records or establish a valid baseline.

General business — fictional

Dispatch correction measurement

Starting information: A fictional supplier plans a sample of dispatched orders.

Completed demonstration: Dispatch correction measurement
Definition	Any correction to the approved dispatch label before release
Collection	Daily sample, agreed size and source; operations analyst responsible
Limitations	Sample excludes a separate overseas workflow; report that boundary

What the result means: The exclusions limit what can be concluded. Do not report the result as the performance of workflows that were never observed.

Practise in a separate worksheet

Open the tool’s built-in synthetic sample as a new editable worksheet. It may differ from the worked demonstrations above. It never replaces an existing worksheet. Save any work you want to retain to your computer.

Open built-in practice worksheet

You’ll be asked to log in if needed. No worksheet is created just by reading this page.

Common mistakes and how to avoid them

Choosing a sample before defining eligibility: specify the population first.
Treating a valid formula as valid data: check the records and method too.
Collecting identifiers unnecessarily: use approved non-sensitive data and minimal fields.

Interpret the result

Assess whether another observer could collect the same measure under the same rules. Definition warnings help identify gaps but cannot verify source accuracy, representative sampling or organizational approval.

Record the assumptions and unanswered questions alongside the result. Use the relevant local review process before making operational decisions.

Credible further learning

These independent educational resources explain the methods. They do not endorse CI Tools Suite. Some external resources have their own access requirements.

Resource links reviewed 29 October 2026. Our interface instructions and fictional examples are original CI Tools learning material.

Put the method into practice

Start a new worksheet, use the guide beside your work and keep an editable .citools copy on your computer.

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