Research Planning SKILL.md

This is the exact file agents read, including the credit header and licence notice. Save it as research-planning/SKILL.md.

---
name: research-planning
description: "Plan research before searching: the decision it serves, a sharp bounded question, an issue tree of sub-questions, hypotheses, depth matched to stakes, methods from desk research to interviews, surveys and experiments, sources, evidence standards, confidence labels, time plans and agreed outputs. Use whenever someone needs to research something, gets a vague research request, plans a study, market or competitor research, wants to scope how deep to go or needs a research plan before starting."
license: CC-BY-4.0
metadata:
  author: Afeez Adebayo
  author_url: https://afeezadebayo.com
  author_linkedin: https://www.linkedin.com/in/afeez-adebayo/
  author_x: https://x.com/za_icon
  source: https://afeezadebayo.com/skills-md/productivity/research-learning/research-planning/
  category: productivity
  subcategory: research-learning
  version: "1.0.0"
  created: "2026-10-14"
  updated: "2026-10-14"
---

# Research Planning

Most research goes wrong before the first search. The question is vague ("look into competitors"), the decision it should inform is unclear, nobody agreed how deep to go, and the researcher collects everything interesting instead of what matters. Days later there is a long document that answers a slightly different question. Good research starts with a sharp question tied to a decision, a scope that fits the time available, the right methods and sources, and a plan for what "done" looks like.

This skill plans research of any kind, from a two-hour desk scan to a multi-week study: framing the decision and research question, breaking it into sub-questions, setting scope and depth, choosing methods (desk research, data analysis, interviews, surveys, experiments), selecting sources, defining evidence standards, planning time, and agreeing the output format before work begins. It is the entry point for the Research and Learning set.

## Operating principles
1. **Decision first.** Every research question serves a decision or a clear need to understand.
2. **Sharp questions.** Specific, answerable and bounded in time, place and population.
3. **Depth matches stakes.** A quick decision gets a quick scan; a costly, hard-to-reverse decision gets deeper work.
4. **Mixed methods where useful.** Combine sources so weaknesses in one are covered by another.
5. **Agree the output before starting.** Format, length, confidence levels and deadline.
6. **Track sources from minute one.** Every claim needs a source you can find again.

## Question framing
| Weak question | Sharp question |
|---|---|
| Look into competitors | Which three competitors win most deals against us in UK mid-market, and why do buyers choose them? |
| Research AI tools | Which AI meeting-notes tools meet our security requirements and cost under £20 per user per month? |
| Is remote work productive? | What does recent research say about productivity in hybrid versus fully remote software teams? |
| Find out about the Nigerian edtech market | How many secondary schools in Lagos use paid digital learning tools, and what do they pay? |

A useful test: could two people independently tell whether the question has been answered?

## Research depth levels
| Level | Time | Methods | Use for |
|---|---|---|---|
| Quick scan | 30 minutes to 2 hours | Desk research, a few trusted sources | Low-stakes, reversible decisions, background |
| Standard | 1 to 3 days | Desk research, data, a few expert conversations | Most business decisions |
| Deep study | 1 to 6 weeks | Mixed methods: interviews, surveys, data, literature review | High-stakes or strategic decisions |

## Methods
| Method | Best for | Watch for |
|---|---|---|
| Desk research | Existing facts, markets, regulations, prior studies | Outdated or low-quality sources |
| Data analysis | Patterns in your own or public data | Biased samples, tracking changes |
| Literature review | What research says on a topic | Cherry-picking studies |
| Expert interviews | Context, judgement, hidden knowledge | Individual bias; few voices |
| User or customer interviews | Needs, behaviours, reasons | Leading questions; small samples |
| Surveys | How common something is | Poor questions; low response rates |
| Experiments | Cause and effect | Time, design quality, sample size |

## When to use, and when not to
Use it before any research task longer than an hour, when a request is vague, when several people will research together, or when research must inform an important decision.

Don't use it for a quick factual lookup; just search. For specific methods, hand off to the specialist skills.

## Inputs
- The decision or need, and who will use the research.
- What is already known (and assumed).
- Time, budget and access (data, people, paid sources).
- Required output and deadline.
- Any constraints: confidentiality, regions, languages.

## Workflow

### Step 1. Clarify the decision
Who decides what, by when, and what would change their mind? Write it in one sentence.

### Step 2. Write the main question
Specific, bounded and answerable. Note what is out of scope.

### Step 3. Break it into sub-questions
Three to seven sub-questions that together answer the main question, using an issue tree: each branch is distinct and together they cover the question.

### Step 4. State hypotheses (optional but powerful)
Your current best guesses, so research can test them rather than wander. Be ready to drop them.

### Step 5. Choose depth and methods
Use the tables above; match methods to each sub-question.

### Step 6. List sources
Primary sources (original data, laws, company filings, studies), secondary sources (reputable reports, journalism) and people to ask.

### Step 7. Set evidence standards
What counts as enough evidence for each sub-question; how recent sources must be; how to label confidence.

### Step 8. Plan time and output
Time per sub-question, checkpoints, the final format (one-page summary, report, deck) and deadline.

### Step 9. Run, then review the plan
At the halfway checkpoint, check whether the question or plan needs to change based on what you have learned.

## Research plan template
```
Decision: <who decides what, by when>
Main question: <specific, bounded>
Out of scope: <...>
Sub-questions:
1. <...> | Method: <...> | Sources: <...> | Time: <...>
2. <...>
Hypotheses: <current best guesses>
Evidence standard: <e.g. two independent reputable sources; data from last 2 years>
Confidence labels: high / medium / low with reasons
Output: <format, length> | Deadline: <date> | Checkpoint: <date>
```

## Issue tree example
```
Should we enter the Kenyan market in 2027?
  1. Is the market big enough? (size, growth, segments)
  2. Can we win? (competitors, our advantages, local needs)
  3. Can we operate there? (regulation, payments, hiring, partners)
  4. Is it worth it? (revenue potential, costs, payback, risks)
```

## Confidence labels
| Label | Meaning |
|---|---|
| High | Several independent reliable sources agree; recent data |
| Medium | Some good evidence, gaps or older data |
| Low | Limited, conflicting or indirect evidence; treat as a hypothesis |

## Edge cases and judgement calls
| Situation | What to do |
|---|---|
| Requester cannot state the decision | Ask what they would do differently depending on the answer |
| Very tight deadline | Quick scan; state confidence and gaps clearly |
| Answer may not exist | Say so early; propose a proxy or a way to generate the data |
| Conflicting stakeholder questions | Agree priority with the decider before starting |
| Sensitive or confidential topic | Limit sources and sharing; anonymise interview data |
| Research keeps expanding | Return to the decision and the sub-questions; cut the rest |

## Handoffs to related skills
- Web and desk research: `desk-research`
- Judging sources: `source-evaluation`
- Checking claims: `fact-checking`
- AI research tools: `ai-assisted-research`
- Academic literature: `literature-review`
- Interviews and surveys: `expert-user-interviews`, `survey-design`
- Turning findings into insights: `research-synthesis`
- Writing the report: the Workplace Writing `reports` and `executive-summaries` skills

## Worked example
A founder asked for "research on the Kenyan market". The plan clarified the decision (whether to launch a pilot in Nairobi in 2027), wrote a bounded main question, built a four-branch issue tree, chose a standard depth (three days), combined desk research, public data, five expert calls and a scan of regulation, and set a two-source evidence standard with confidence labels. At the halfway checkpoint, payment regulation emerged as the main risk, so time shifted from market sizing to regulation. The final two-page brief recommended a partner-led pilot, with confidence labelled for each finding, and the decision was made in one meeting.

## Common mistakes
- Starting to search before framing the question.
- Researching a topic instead of answering a question.
- Depth that does not match the stakes.
- No source tracking, so claims cannot be checked.
- Delivering everything found instead of what answers the question.

## Output format
```
1. Decision and main question
2. Sub-questions (issue tree)
3. Hypotheses
4. Methods and sources per sub-question
5. Evidence standards and confidence labels
6. Time plan, checkpoint and deadline
7. Output format
```

## Self-check before you answer
- Is the research tied to a specific decision or need?
- Is the main question specific and bounded?
- Do the sub-questions cover the question without overlap?
- Are depth, methods, evidence standards and output agreed?

---
Created by Afeez Adebayo, Marketing, SEO & Growth Expert
Website: https://afeezadebayo.com
LinkedIn: https://www.linkedin.com/in/afeez-adebayo/
X: https://x.com/za_icon
Source: https://afeezadebayo.com/skills-md/productivity/research-learning/research-planning/

Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). You may copy, share and adapt this skill, including for commercial use, as long as you credit Afeez Adebayo and link to the source URL above. Keep this notice in any copy or adapted version.