Secondary data assessment and use plan
Organize questions and information needs before searching. Once scope is known, reconsider answerability and record reasons for changes.
Secondary data assessment and use plan
Step 1: questions and necessary variables
Specify necessary variables or indicators first
Completed example for this section (fictional)
This fictional example is for explanation. Adapt it to your own program. Your entries will not change.
Scroll horizontally to view the table
| Evaluation questions | Necessary variables or indicators | Required period and geographic scope | Priority: high / medium / low |
|---|---|---|---|
| Were new users reached? | First use, identifiability and period | First half of fiscal 2026, City A (fictional) | High |
Reason for this entry: Distinguish total visits and unique people.
Scroll horizontally to view the table
| Evaluation questions | Necessary variables or indicators | Required period and geographic scope | Priority: high / medium / low |
|---|---|---|---|
Writing tips and explanation for this section
About this section
Specify necessary variables or indicators first
Distinguish total visits and unique people.
View the method explanationWriting tips
Keep the information in each row aligned. Scroll wide tables horizontally to see every column.
Read the full fictional exampleStep 2: source search and quality
Assess each candidate source
Completed example for this section (fictional)
This fictional example is for explanation. Adapt it to your own program. Your entries will not change.
Scroll horizontally to view the table
| Dataset and provider | Collection purpose and targets | Timing and update frequency | Available variables | Fit to purpose: ○ / △ / × | Terms and access |
|---|---|---|---|---|---|
| Consultation register (fictional) | Operational management; service users | Monthly entries | Date, user ID and first-use classification | △: some IDs missing | Plan to check permitted use with manager |
Reason for this entry: Do not imply permission already obtained.
Scroll horizontally to view the table
| Dataset and provider | Collection purpose and targets | Timing and update frequency | Available variables | Fit to purpose: ○ / △ / × | Terms and access |
|---|---|---|---|---|---|
Writing tips and explanation for this section
About this section
Assess each candidate source
Do not imply permission already obtained.
View the method explanationWriting tips
Keep the information in each row aligned. Scroll wide tables horizontally to see every column.
Read the full fictional exampleStep 3: data limitations
Describe mismatches for every selected source
Completed example for this section (fictional)
This fictional example is for explanation. Adapt it to your own program. Your entries will not change.
Reason for this entry: Attend to people outside records' scope.
Writing tips and explanation for this section
About this section
Describe mismatches for every selected source
Attend to people outside records' scope.
View the method explanationWriting tips
Use the example as a reference and record what you have established about your own program. Distinguish assumptions and unchecked matters from confirmed facts.
Read the full fictional exampleStep 4: analysis plan
Map datasets to questions
Completed example for this section (fictional)
This fictional example is for explanation. Adapt it to your own program. Your entries will not change.
Scroll horizontally to view the table
| Evaluation questions | Data used | Analysis method | Interpretive limitations |
|---|---|---|---|
| Were new users reached? | Consultation register after permission | Aggregate first-time users and missingness monthly | Cannot generalize to people not visiting |
Reason for this entry: State the answerable scope.
Scroll horizontally to view the table
| Evaluation questions | Data used | Analysis method | Interpretive limitations |
|---|---|---|---|
Writing tips and explanation for this section
About this section
Map datasets to questions
State the answerable scope.
View the method explanationWriting tips
Keep the information in each row aligned. Scroll wide tables horizontally to see every column.
Read the full fictional exampleQuality checks
Check before analysis/reporting
Completed example for this section (fictional)
This fictional example is for explanation. Adapt it to your own program. Your entries will not change.
- ☑ Checked: Set questions before searching
- ☑ Checked: Checked metadata: purpose, time and methods
- ☐ Not checked: Checked definition/method changes in annual reports or similar sources
- ☐ Not checked: Checked terms and secondary-use permission
- ☑ Checked: Recorded preprocessing and analysis as scripts or documents
- ☑ Checked: Stated limitations alongside results and conclusions
Reason for this entry: Definition-change checks and permission remain incomplete. No individual-record analysis before permission.
Writing tips and explanation for this section
About this section
Check before analysis/reporting
Definition-change checks and permission remain incomplete. No individual-record analysis before permission.
View the method explanationWriting tips
Read each item and check those you have confirmed. Do not use the fictional example’s checkbox states as findings about your own program.
Read the full fictional exampleBefore writing, check when to use the worksheet and what completion involves
Secondary data assessment and use plan is a worksheet for applying Secondary Data Analysis in meetings or individual work. For the overall duration of the method, use “Illustrative planning durations, not common standards: finding/acquiring data 1–2 weeks, quality/preprocessing 1–2 weeks, analysis 2–4 weeks” as a reference, adjusting for scale and resources. Fill in what you know provisionally and leave unresolved matters as questions to check next.
When this worksheet is useful
- Understand target-area/group backgrounds and trends without new collection
- Supplement outcomes using municipal records or statistics
- Build long-term trends or comparison-group baselines
Participants and preparation
1–2 data analysts; acquisition may require coordination with administration
Bring the materials used for decisions, existing data, and differing stakeholder views to help complete the worksheet.
Suggested order
- 1. Step 1: questions and necessary variablesSpecify necessary variables or indicators first
- 2. Step 2: source search and qualityAssess each candidate source
- 3. Step 3: data limitationsDescribe mismatches for every selected source
- 4. Step 4: analysis planMap datasets to questions
- 5. Quality checksCheck before analysis/reporting
Signs the worksheet is ready for review
- Source list with metadata assessments
- Clean analytical dataset with code and procedures
- Quantitative report with limitations
Cautions for review
- Do not derive questions from available data. Set questions first, then seek necessary data.
- Provider definition changes can distort trends. Always check metadata and annual reports' methodological-change sections.
- Do not hide limitations only at the end. State collection-purpose, definition, target differences and missingness relevant to conclusions alongside results.
Read a completed fictional example (your entries will not change)
A fictional illustration examining reach using a fictional consultation register.
Step 1: questions and necessary variables
Scroll horizontally to view the table
| Evaluation questions | Necessary variables or indicators | Required period and geographic scope | Priority: high / medium / low |
|---|---|---|---|
| Were new users reached? | First use, identifiability and period | First half of fiscal 2026, City A (fictional) | High |
Reason for this entry: Distinguish total visits and unique people.
Step 2: source search and quality
Scroll horizontally to view the table
| Dataset and provider | Collection purpose and targets | Timing and update frequency | Available variables | Fit to purpose: ○ / △ / × | Terms and access |
|---|---|---|---|---|---|
| Consultation register (fictional) | Operational management; service users | Monthly entries | Date, user ID and first-use classification | △: some IDs missing | Plan to check permitted use with manager |
Reason for this entry: Do not imply permission already obtained.
Step 3: data limitations
Reason for this entry: Attend to people outside records' scope.
Step 4: analysis plan
Scroll horizontally to view the table
| Evaluation questions | Data used | Analysis method | Interpretive limitations |
|---|---|---|---|
| Were new users reached? | Consultation register after permission | Aggregate first-time users and missingness monthly | Cannot generalize to people not visiting |
Reason for this entry: State the answerable scope.
Quality checks
- ☑ Checked: Set questions before searching
- ☑ Checked: Checked metadata: purpose, time and methods
- ☐ Not checked: Checked definition/method changes in annual reports or similar sources
- ☐ Not checked: Checked terms and secondary-use permission
- ☑ Checked: Recorded preprocessing and analysis as scripts or documents
- ☑ Checked: Stated limitations alongside results and conclusions
Reason for this entry: Definition-change checks and permission remain incomplete. No individual-record analysis before permission.
Common errors in judgment
Compare years without checking definitions
How to revise: Check aggregation and recording changes
Reason: Apparent trends may arise from institutional or recording changes.
Freely join individual records because data are public
How to revise: Check terms and re-identification risks
Reason: Anonymous datasets may identify people when joined.
References and checked sections
- Existing documentsBetterEvaluation
- Section consulted
- Types of existing documents / Advice for using this method
- How it relates to the text
- Judge fit to purpose considering record gaps and post-creation changes.
How to cite this page
Change history
- — Checked sources for definitions and conditions and added fictional examples, judgment rationales and completed entries for every field. Revised unsupported historical or uptake claims. Reviewed procedures and cautions, adjusting fixed counts, thresholds and institutional generalizations. Preserved field positions, types and counts while revising fixed conditions and thresholds.


