必須項目と任意項目
10ステップはすべての採用で必須です。3は任意で、他では得られない根拠が必要なときに使います。ステップを選ぶと開きます。
- すべての採用で必須
- 任意 — 根拠を補いたいときに使用
- AIブースト — 作成を大きく効率化
- 色=フェーズ
フェーズ 1
Plan
フェーズ 2
Attract
フェーズ 3
Select
フェーズ 4
Decide
フェーズ 5
Onboard & learn
すべてのステップに共通する3つのルール
- Agree the criteria before you meet anyone — Competencies, weights and must-haves are fixed at intake, so the bar can't move from one candidate to the next.
- Collect the same evidence from everyone — Same knockouts, same task, same questions, in the same order — so candidates are compared on equal terms.
- Score alone, then decide together — Each interviewer scores against written anchors before the debrief, and the decision is recorded against the evidence.
採用の13ステップ
各ステップで、やること・担当者・完了の基準を示します。ステップを開くと、その背景にある手法が分かります。
AIが下書きし、人が決める: Use AI to draft, rewrite and summarise your own material — never to rank, score, screen out or decide on candidates, and never with a candidate's personal data.
フェーズ 1
Plan
Agree why you are hiring and what good looks like.
01Plan the role必須Workforce planning and requisition approvalWrite the business case and decide whether to build, borrow or buy before a role is opened.担当者: Hiring manager + finance / HR business partner完了の基準: An approved requisition with a written business case, budget and a named decision-maker.
フレームワーク
Build · Borrow · Buy
使い方
- Write the problem the hire solves in one sentence, in business terms — not the job title.
- Test Build: could an existing person grow into this within the time you have?
- Test Borrow: is the need time-boxed, or does it end once a system is shipped?
詳しく:残りの手順と効果の理由
Before opening a role, decide whether to build the capability in your current team, borrow it (contractor, agency, partner), or buy it (a permanent hire).
- Choose Buy only when the work is ongoing, core to the product and nobody inside can absorb it.
- Record the decision, the budget and the one person who signs off the final hire.
なぜ効果的か: Writing the build, borrow or buy decision down exposes a vague or temporary need before it becomes a permanent requisition — and gives every later stage an anchor to check against.
AIを強みにする4D framework
- 委任
- Hand AI the first draft of the business case and the build / borrow / buy comparison. The decision, the budget and the sign-off stay with people.
プロンプトとチェック項目を見る
- 記述
You are helping a hiring manager write a business case for a [役職名] role. Context: I will paste the problem the hire solves, the work it involves, the capacity we already have and the time we have. Produce: (1) a one-sentence problem statement in business terms; (2) a build / borrow / buy comparison with the strongest argument for each; (3) the questions a finance partner would ask; and (4) a short recommendation with the evidence it rests on. Use British English and plain language. Do not invent figures — leave [brackets] where I need to supply numbers. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check every number and claim against your own notes and strike anything the draft assumed. Make sure 'buy' is argued from ongoing work, not from a job title.
- 誠実さ
- The hiring manager owns the final case and the budget request. No candidate information belongs here; AI drafts the case, people decide whether to open the role.
02Agree success必須AIブーストIntake meeting and competency modelMeet the hiring manager and agree 5–7 competencies, which are must-haves, and how each is weighted.担当者: Recruiter + hiring manager完了の基準: A signed-off competency model: 5–7 competencies, each marked must-have or trainable, with weights.
フレームワーク
Competency model (must-have vs trainable)
使い方
- Start from the 12-month outcomes, then ask which capabilities produce them.
- Keep 5–7 competencies. With more, interviewers struggle to score each one separately.
- Mark each must-have or trainable. Only must-haves can count against a candidate.
詳しく:残りの手順と効果の理由
A short list of the observable capabilities the job needs, split into what the hire must bring on day one and what you will teach.
- Give each a weight so they sum to 100, agreed before anyone meets a candidate.
- Write what evidence of each looks like, so interviewers know what they are listening for.
なぜ効果的か: Agreeing the criteria before meeting candidates stops the bar moving from one candidate to the next, and makes it harder for 'I'll know it when I see it' to decide the hire.
AIを強みにするAIブースト4D framework
- 委任
- Hand AI your raw intake notes to turn into a draft competency model. Choosing the must-haves and the weights stays with the hiring manager and recruiter.
プロンプトとチェック項目を見る
- 記述
You are helping a recruiter and a hiring manager build a competency model for a [役職名] role. Context: I will paste the notes from our intake meeting, including the 12-month outcomes and what the hiring manager worries about most. Produce a table of 5–7 observable competencies with, for each: a one-line definition; whether it is a must-have or trainable, with the reason; what evidence of it looks like in real work; and a suggested weight so the weights total 100. Use British English and inclusive wording, avoid years-of-experience or named employers as evidence, and keep every competency job-related. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that each competency is observable and job-related, that nothing describes a type of person rather than the work, and that trainable items haven't been marked must-have.
- 誠実さ
- The hiring manager signs off the final model and weights before anyone meets a candidate. No candidate data goes into the prompt; AI drafts, people decide.
フェーズ 2
Attract
Describe the job honestly and reach the right people.
03Write the job必須AIブーストJob description and pay bandWrite the job around outcomes and genuine must-haves, and publish the pay range.担当者: Hiring manager (content) + recruiter (publishing)完了の基準: A published job description that states outcomes, the must-haves, how AI tools are used and the pay information the law requires.
フレームワーク
Outcome-based job description
使い方
- Lead with the problem the team is solving and what the hire will own.
- Limit must-haves to the must-have competencies from intake. Everything else is 'nice to have'.
- Replace 'X years of experience' with the capability those years were meant to prove.
詳しく:残りの手順と効果の理由
Describe what the person will achieve and the few requirements that truly gate the job, instead of a wish list of tools and years.
- State how the team expects AI tools to be used in the work.
- For each work location, publish the pay range and any benefits or other pay information the law requires. A genuine range in every advert is a sound default.
なぜ効果的か: An outcome-based description states the work and selection criteria directly.
AIを強みにするAIブースト4D framework
- 委任
- Hand AI the first draft of the job description from your signed-off competency model. The must-haves, the pay range and the final wording stay with people.
プロンプトとチェック項目を見る
- 記述
You are helping write an outcome-based job description for a [役職名] role. Context: I will paste the competency model (must-have and trainable, with evidence), the 12-month outcomes, how the team uses AI tools, the location and working pattern, and the pay range. Produce: a summary paragraph that leads with the problem and what the hire will own; 'What you'll do' as outcomes, not tasks; 'What you need' containing only the must-haves; 'Nice to have' for the trainable items; 'How we use AI tools'; and a pay section that states the range. Use British English and inclusive, gender-neutral wording, avoid hype, and replace any 'X years' with the capability it stands for. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that 'What you need' contains only the must-haves, that no degree, employer or years requirement crept in, and that the pay range and location are exactly what was approved.
- 誠実さ
- The hiring manager owns the content and the recruiter owns publishing, including the pay information the law requires for each location. AI drafts the advert; people decide what it says.
04Find candidates任意AIブーストSourcing strategySearch at least three channels where candidates' work is visible, and personalise every first message.担当者: Recruiter / sourcer完了の基準: A shortlist-ready pipeline from at least three channels, with outreach tracked.使うとき: Inbound applications won't give you enough qualified candidates.省略するとき: Your shortlist already comes from inbound applications or referrals.
フレームワーク
Channel mix + evidence-first outreach
使い方
- Pick channels where candidates show their work, not only where they list job titles.
- Write one search query per channel. OR joins alternatives, AND joins things that must all appear, NOT excludes. Keep the version that works best.
- Personalise the first line to something the candidate actually built or wrote.
詳しく:残りの手順と効果の理由
Spread sourcing across channels where the work is visible, and open outreach with the problem, not the perks.
- Lead with the problem and the pay range. Save the perks for later.
- Track reply rates by channel each week and drop the channel that isn't working.
なぜ効果的か: Searching for evidence of the work can surface candidates whose current title differs from the vacancy, or whose CV undersells what they have done.
AIを強みにするAIブースト4D framework
- 委任
- Hand AI the search queries and the first draft of the outreach template. Choosing channels, personalising to a candidate's public work and sending stay with the recruiter.
プロンプトとチェック項目を見る
- 記述
You are helping a recruiter source candidates for a [役職名] role. Context: I will paste the must-have competencies, the kind of work we want evidence of, the channels we are using and the pay range. Produce: (1) one search query per channel, using OR for alternatives, AND for things that must all appear and NOT to exclude, with a one-line note on what each query looks for; and (2) a first-outreach template of under 120 words that opens with a [placeholder for something the candidate built], states the problem we are hiring to solve and the pay range, and ends with a low-pressure question. Use British English and inclusive wording. Do not refer to any specific person. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that the queries search for evidence of the work rather than job titles alone, and that the template claims nothing about the role or the pay you can't back up.
- 誠実さ
- The recruiter personalises every message to something the candidate actually built, and sends it. No names or profile data go into the prompt; AI drafts, people decide whom to contact.
フェーズ 3
Select
Collect the same evidence from every candidate.
05Check applications必須Application screeningCheck every application against the same written knockouts — when unsure, get a second review or move the candidate to the skills stage.担当者: Recruiter完了の基準: Every application reviewed against the same written knockouts within five working days.
フレームワーク
Knockout criteria
使い方
- Derive knockouts only from must-have competencies and genuine legal requirements.
- Keep them binary and answerable from the application itself.
- Apply them in the same order to every application and log the reason for each rejection.
詳しく:残りの手順と効果の理由
A small set of yes/no requirements, written in advance, applied to every applicant the same way.
- Do not use proxies such as university, employer brand or employment gaps as knockouts.
- Anything ambiguous gets a second review or moves forward to the skills stage.
なぜ効果的か: Early screening rejects people before richer evidence exists, so its criteria need the most care. Written criteria make decisions reviewable — but each one must also be job-related, applied consistently and checked for unjustified adverse impact.
AIを強みにする4D framework
- 委任
- Hand AI the job of turning your written knockouts into a consistent checklist with reason codes. Reviewing each application stays with the recruiter.
プロンプトとチェック項目を見る
- 記述
You are helping a recruiter prepare an application-screening checklist for a [役職名] role. Context: I will paste the must-have competencies and our written knockout criteria. Produce: (1) each knockout as a yes/no question answerable from an application alone; (2) a short list of reason codes for a 'no'; and (3) a note of any criterion that looks like a proxy — a degree, employer brand or employment gap — rather than a job-related requirement, with a suggested rewrite. Use British English. Do not evaluate any applicant and do not ask for applicant details. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that each question is binary and job-related, and that every flagged proxy has been removed or justified in writing.
- 誠実さ
- A person reviews every application against the checklist and records the reason. Never paste CVs or applicant details into an AI tool, and never let a tool screen anyone out — in New York City and the EU that can bring automated-decision rules into play.
06Recruiter call任意Recruiter screenHold a 20–30 minute call with the same questions for everyone, and confirm the pay range works.担当者: Recruiter完了の基準: A 20–30 minute call that confirms logistics, motivation and one or two must-have signals.使うとき: You are hiring at volume, or pay and logistics need confirming early.省略するとき: You have only a handful of applicants — fold the pay and logistics questions into application screening instead.
フレームワーク
Structured screening call
使い方
- Open by explaining the process, timeline and pay range. No surprises later.
- Confirm logistics: location, working pattern, notice period and whether the range works for them.
- Ask the same 4–6 questions in the same order, and note evidence, not impressions.
詳しく:残りの手順と効果の理由
The same short set of questions for every candidate, with notes taken against what a strong answer contains.
- Leave time for the candidate's questions. Don't score their questions unless they test a written, job-related competency.
- Decide within 48 hours and tell the candidate either way.
なぜ効果的か: Using the same questions and written evidence anchors makes answers easier to compare, and a short, predictable call respects the candidate's time.
AIを強みにする4D framework
- 委任
- Hand AI the first draft of the screening-call script and its evidence anchors. Running the call and taking the notes stay with the recruiter.
プロンプトとチェック項目を見る
- 記述
You are helping a recruiter write a 20–30 minute structured screening call for a [役職名] role. Context: I will paste the must-have competencies, the logistics we need to confirm (location, working pattern, notice period) and the pay range. Produce: an opening that explains the process, the timeline and the pay range; 4–6 questions in a fixed order, each with one line on what a strong answer contains; and a closing that asks whether the published range works. Use British English and inclusive wording. Do not include questions about salary history, age, family, health or any other protected characteristic. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that every question is job-related and lawful, that the pay question asks whether the range works rather than for history, and that the anchors describe evidence, not impressions.
- 誠実さ
- The recruiter asks the same questions of everyone and writes the notes. No candidate details go into the prompt; AI drafts the script, people run the call and decide.
07Work sample必須Skills assessment / work sampleGive every shortlisted candidate the same timed, job-like task, marked against criteria written in advance.担当者: Hiring manager (design) + recruiter (logistics)完了の基準: Every shortlisted candidate completes the same job-shaped task, marked against criteria written in advance.
フレームワーク
Work-sample test
使い方
- Take a real problem the team solved recently and shrink it to fit the timebox.
- Write the marking criteria first, tied to the competency model.
- Timebox honestly — for take-home work, a few hours at most — and say so in the brief.
詳しく:残りの手順と効果の理由
A small, realistic slice of the job, marked against criteria written in advance. Give candidates equivalent materials and arrange reasonable adjustments where required.
- State the AI-tool policy in writing. Where the job permits these tools, use equivalent conditions in the assessment and evaluate how candidates verify their output.
- Mark without CV details where you can, and have two people mark borderline submissions.
なぜ効果的か: A well-designed work sample gives direct evidence of job-relevant skill rather than a proxy for it, and gives candidates a realistic preview of the work.
AIを強みにする4D framework
- 委任
- Hand AI the first draft of the work-sample brief and its marking sheet. Choosing the task, setting the timebox and marking stay with the hiring manager.
プロンプトとチェック項目を見る
- 記述
You are helping a hiring manager design a work sample for a [役職名] role. Context: I will paste the competency model, a real problem the team solved recently with anything confidential removed, the timebox, and our AI-tool policy for candidates. Produce: a candidate-facing brief (what to do, what to hand in, the time cap, how to request an adjustment, which AI tools are allowed and how to report their use); and a marking sheet with 4–6 criteria tied to named competencies, each with what a 1, a 3 and a 5 look like. Use British English and plain, inclusive wording. Do not design anything that needs more than the stated time. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that the task fits the timebox, that every criterion maps to a competency, and that the brief gives all candidates the same starting materials.
- 誠実さ
- The hiring manager owns the task and the criteria, and people mark every submission. Do not paste candidate submissions into an AI tool for scoring; AI drafts the brief, people mark and decide.
08Structured interviews必須AIブーストStructured interview loopRun structured technical interviews — the same job-specific questions for everyone, each competency led by one interviewer.担当者: Interview panel (named in advance)完了の基準: Every competency has a lead interviewer and at least one second source of evidence, with the same questions for every candidate.
フレームワーク
Structured technical interview
使い方
- Give each competency a lead interviewer, plus a second source of evidence — the work sample, another round or an independent marker. Avoid asking the same thing twice, but never let one person's view be the only evidence for a critical competency.
- Ask the three core questions for your round, in order, for every candidate. Use an optional follow-up only if there is time.
- Probe each answer: why that choice, what else they considered, and how they would know it worked — until you hear the candidate's own technical decision.
詳しく:残りの手順と効果の理由
Every candidate gets the same job-specific questions, each interviewer leads on specific competencies, and every answer is probed with the same four follow-ups: what would you do, why, what else did you consider, and how would you know it worked.
- Take notes on evidence during the interview. Don't rate until it's over.
- Fill in your interviewer sheet and submit it before you talk to any other interviewer.
なぜ効果的か: Structured interviews make answers comparable: every candidate faces the same job-related questions and is scored against the same anchors.
AIを強みにするAIブースト4D framework
- 委任
- Hand AI the drafting of probe questions and strong / weak anchors for one competency. Asking, listening and scoring stay with the interviewer.
プロンプトとチェック項目を見る
- 記述
You are helping an interviewer prepare a structured technical interview for a [役職名] role. Context: I will paste one competency, its evidence description and the core question we ask every candidate. Produce: four probes in this fixed order — what would you do, why that choice, what else did you consider, how would you know it worked — tailored to the question; a one-line description of a strong answer and of a weak answer; and two follow-ups to use only if time allows. Use British English and inclusive wording. Keep everything about the work, nothing about the person. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that the probes test the named competency rather than trivia, that the anchors describe observable evidence, and that no question touches a protected characteristic.
- 誠実さ
- Interviewers ask the same core questions of every candidate and score alone against the rubric. Interview notes and candidate names never go into an AI tool; AI drafts the questions, people interview and decide.
フェーズ 4
Decide
Weigh the evidence, check it, and make the offer.
09Compare evidence必須Scoring, calibration and debriefScore alone against the rubric, reveal scores together, discuss the evidence, then decide.担当者: Hiring manager (chairs) + panel完了の基準: A documented hire / no-hire decision traceable to scored evidence against the competency model.
フレームワーク
BARS rubric + independent scoring
使い方
- Every interviewer scores against the anchors and submits before the debrief starts.
- The chair reveals scores together, then discusses the biggest disagreements first.
- Discuss evidence, not adjectives. 'Strong communicator' isn't evidence; what the candidate said is.
詳しく:残りの手順と効果の理由
A behaviourally anchored rating scale (BARS) describes what a 1, 3 and 5 look like for each competency. Interviewers score alone before the debrief.
- Treat a 1 on a must-have as a stop-and-review trigger: check the criterion is job-related, look at the evidence and settle big disagreements before deciding.
- Record the decision and the reasons against each competency.
なぜ効果的か: Independent scoring reduces the risk that discussion or seniority changes an interviewer's initial judgement before the evidence is reviewed. Behavioural anchors help a '4' mean the same thing to every interviewer.
AIを強みにする4D framework
- 委任
- Hand AI the drafting of a blank debrief worksheet and agenda from the competency rubric alone. People add the evidence locally; the scores and the decision stay with the panel.
プロンプトとチェック項目を見る
- 記述
You are helping a hiring manager prepare a debrief for a [役職名] role. Context: I will paste the competency rubric only — the competencies, their weights and their 1, 3 and 5 anchors. Produce: (1) a blank debrief worksheet with one row per competency and empty columns for each interviewer's independent score, the evidence they cite, the spread of scores and an 'evidence gap?' box; (2) a 45-minute agenda: confirm every scorecard is in and reveal all scores at once, discuss the widest spreads using evidence only, review any must-have scored 1, then look at the weighted total and decide (hire, no hire or one targeted follow-up), and record the reasons; and (3) neutral questions the chair can ask to draw out evidence rather than adjectives. Leave every evidence and score cell empty. Do not suggest a score, a rating or a recommendation. Use British English. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that the worksheet follows your rubric exactly — same competencies, weights and anchors — and that the agenda keeps independent scores hidden until the reveal.
- 誠実さ
- Interviewers fill in the evidence and scores locally, alone, before the debrief, and the panel decides together. Candidate notes and personal data never go into an AI tool; AI never scores, ranks or compares candidates.
10Check references任意References and background checksAsk two people who saw the candidate's work for specific examples; run only lawful, relevant checks.担当者: Recruiter (references) + HR (checks)完了の基準: At least two references that test specific competencies, plus only the checks that are lawful and relevant to the role.使うとき: It is lawful where you hire, and specific evidence from a referee would change the decision.省略するとき: Local law or company policy rules it out.
フレームワーク
Competency-based referencing
使い方
- With the candidate's consent, ask for two people who saw their relevant work directly — ideally a former manager and a peer.
- Accept suitable alternatives if a manager or peer isn't available, and never penalise a candidate for a former employer's no-reference policy.
- Aim your questions at the one or two competencies the debrief was least sure about.
詳しく:残りの手順と効果の理由
Treat references as a last structured conversation about the candidate's work, aimed at the competencies where your evidence is thinnest.
- Ask for examples, not ratings. 'Tell me about a time they…' works here too.
- Set the timing of each background check by the law and policy that apply.
なぜ効果的か: Generic reference questions tend to produce little job-related evidence. Asking for specific examples tied to the role's competencies turns referencing into something you can use.
AIを強みにする4D framework
- 委任
- Hand AI the drafting of reference questions aimed at the competency the panel was least sure about. Choosing referees, making the calls and interpreting the answers stay with the recruiter.
プロンプトとチェック項目を見る
- 記述
You are helping a recruiter write competency-based reference questions for a [役職名] role. Context: I will paste the competency model and the one or two competencies where our evidence is thinnest — no candidate details. Produce: 3–4 questions per competency that ask for specific examples ('tell me about a time…') rather than ratings; an opening question about how the referee worked with the person and for how long; and a closing question about what their next manager could do to help them do their best work. Use British English and inclusive wording. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that the questions ask for examples rather than opinions, that they stay on job-related competencies, and that none asks about health, family or other protected matters.
- 誠実さ
- References are taken with the candidate's consent and interpreted by people. Referee answers and candidate details never go into an AI tool; AI drafts the questions, people decide.
11Agree the offer必須Offer, negotiation and closeMake the offer within the approved band, built around what the candidate said matters to them.担当者: Hiring manager + recruiter完了の基準: An accepted written offer within the approved band, with a start date.
フレームワーク
Close plan (motivators → offer → objections)
使い方
- List the candidate's top three motivators from your notes at every stage.
- Make the verbal offer personally, and link each part of it to a motivator.
- Ask what else they are weighing and when they have to decide.
詳しく:残りの手順と効果の理由
Build the offer around what the candidate told you they care about, anticipate their objections, and make sure the verbal and written offers match.
- Place the offer in the band using the same pre-set, job-related factors for everyone, and record why.
- Send the written offer promptly after the verbal one.
なぜ効果的か: A close plan ties the offer to the candidate's stated priorities and makes approvals explicit before the final interview.
AIを強みにする4D framework
- 委任
- Hand AI the first draft of the offer message built around what the candidate said matters to them. The figure, the approval and the conversation stay with the hiring manager.
プロンプトとチェック項目を見る
- 記述
You are helping a hiring manager draft an offer message for a [役職名] role. Context: I will paste three general priority categories (for example: learning, flexibility, scope) — not the candidate's words, notes or personal details; the parts of the offer; and the start-date options — without the salary figure. Produce: a warm, plain-English message that links each part of the offer to one of their priorities, says what happens next and when the written offer follows, and invites questions. Use British English and inclusive wording, and leave [brackets] for figures and names. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that nothing promised is outside policy or the approved band, that every claim about the role is true, and that the message reads as personal rather than templated.
- 誠実さ
- The hiring manager places the offer in the band using the same pre-set factors for everyone and makes the verbal offer personally. Figures and personal details are filled in by people, never pasted into AI.
フェーズ 5
Onboard & learn
Set the hire up to succeed, then measure and improve the process.
12Help them settle in必須Pre-boarding and 30-60-90 onboardingHave access and a buddy ready on day one, agree a written 30-60-90 plan in week one, and check progress at days 30, 60 and 90.担当者: Hiring manager + buddy + HR完了の基準: A new hire who has worked through a written 30-60-90 plan tied to the 12-month outcomes, with a check-in at each milestone.
フレームワーク
30-60-90 day plan
使い方
- Before day one: equipment, access, a named buddy and a first-week schedule.
- Days 1–30, learn: systems, people and the current state of the work.
- Days 31–60, contribute: a first scoped piece of work shipped with support.
詳しく:残りの手順と効果の理由
Three phases — learn, contribute, own — with written expectations for each, agreed with the new hire in week one.
- Days 61–90, own: an area of responsibility with clear outcomes.
- Hold a check-in at each milestone against the written plan.
なぜ効果的か: Hiring doesn't end at the signature. A written onboarding plan makes expectations and support visible to the new hire and their manager.
AIを強みにする4D framework
- 委任
- Hand AI the first draft of the 30-60-90 plan from the 12-month outcomes. Agreeing the plan with the new hire stays with the manager.
プロンプトとチェック項目を見る
- 記述
You are helping a hiring manager draft a 30-60-90 day onboarding plan for a new [役職名]. Context: I will paste the 12-month outcomes from the intake meeting, the systems and people the hire will work with, and anything they will need before day one. Produce: a pre-boarding checklist (equipment, access, a named buddy, a first-week schedule); then three sections — days 1–30 learn, days 31–60 contribute, days 61–90 own — each with 3–4 concrete, checkable expectations and one milestone check-in question. Use British English and plain wording. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that each expectation is realistic for a new starter, ties back to a 12-month outcome, and offers the hire support rather than a test.
- 誠実さ
- The manager agrees the plan with the new hire in week one and owns the check-ins. The new hire's personal details stay out of the prompt.
13Measure time to hire必須AIブーストMeasure the process: mean time to hireWhen the hire accepts, record how many days each step took, find where time was lost, and fix one thing before the next hire.担当者: Recruiter / talent lead + hiring manager完了の基準: A stage-by-stage timing record for this hire, the slowest step named, and one change agreed before the next requisition opens.
フレームワーク
Mean time to hire, by stage
使い方
- When the hire accepts, write down the date each stage started and ended, and the day the successful candidate entered the pipeline.
- Work out the days per stage, the time to hire and the time to fill, and mark the slowest stage.
- Note the offer-acceptance rate and the stage where most candidates dropped out.
詳しく:残りの手順と効果の理由
Time to hire is the number of days from the successful candidate entering your pipeline (their application or your first contact) to their accepted offer; mean time to hire is that figure averaged across hires. Time to fill — requisition approval to acceptance — is a separate measure. Record both per stage, so you can see where the time went rather than only the total.
- Separate waiting time (scheduling, approvals, silence) from working time, and decide which one to shorten.
- Fix one thing before the next hire, and write down what you changed.
なぜ効果的か: A single total hides where the delay sits. Per-stage timing points at the one step to fix, and the acceptance rate and drop-out points show whether candidates kept pace with the process.
AIを強みにするAIブースト4D framework
- 委任
- Hand AI the job of building a blank timing worksheet and the instructions for reading it. Entering dates, working out the timings and deciding what to change stay with the recruiter and the hiring manager.
プロンプトとチェック項目を見る
- 記述
You are helping a recruiter and a hiring manager set up a timing review for a [役職名] hire. Context: I will list the stage names we used, in order (for example requisition approved, sourcing, screening, recruiter call, work sample, interviews, debrief, references, offer accepted). Produce: (1) a blank worksheet with one row per stage and columns for start date, end date, days in stage, days spent waiting (scheduling, approvals, no reply) and number of candidates who entered and left; (2) step-by-step instructions for us to work out, from our own records, time to hire (the successful candidate's entry to the pipeline, by application or first contact, to the accepted offer; average it across hires for mean time to hire) and, separately, time to fill (requisition approval to the accepted offer); (3) five questions we should ask about the slowest stage, separating waiting from working; (4) a short template for recording one change to make before the next hire. Use British English. Do not include benchmarks or example figures. Ask me questions if anything is missing. Rule: do not ask for, and I will not paste, candidate names, interview notes, CVs, submissions or any other personal data. If any appears, stop and tell me to remove it.
- 識別
- Check that the worksheet covers every stage you actually ran, that the two definitions are not mixed up, and that the questions point at the process rather than at any person.
- 誠実さ
- People fill in the dates and do the arithmetic from their own records, choose the one thing to fix and write it down. No dates, names or details about any candidate go into the prompt.
学んだことを次の採用に活かす
全体の流れをひと目で
5つのフェーズ、13のステップ。破線のステップは任意です。合わない候補者は4つのポイントで離脱できます — 速やかに、丁寧にお断りしましょう。
1 · Plan
- 01 Plan the role
- 02 Agree success ✦
2 · Attract
- 03 Write the job ✦
- 04 Find candidates ✦
3 · Select
- 05 Check applications↳ not a fit? close kindly
- 06 Recruiter call
- 07 Work sample↳ not a fit? close kindly
- 08 Structured interviews ✦↳ not a fit? close kindly
4 · Decide
- 09 Compare evidence↳ not a fit? close kindly
- 10 Check references
- 11 Agree the offer
5 · Onboard & learn
- 12 Help them settle in
- 13 Measure time to hire ✦
Not a fit at any of these points? Close kindly: tell the candidate promptly, with the reason you recorded.
Dashed = optional step · ✦ = AI boost, a big drafting win
Hanzomon H-Evaluate
キットを手作業で使う — あるいはH-Evaluateに根拠集めを任せる
このキットが採用プロセスそのものです。H-Evaluateは職種専用のアセスメントを生成し、受験した候補者について構造化された根拠をパネルに提供できます。採用の決定は人が行います。
手作業の場合
- 課題を作成
- すべての提出物を採点
- メモを集約
H-Evaluateを使う場合
- 職務に合わせたアセスメント
- 面接官向けの構造化された根拠
- 職種ごとにAI生成するため、固定の問題ライブラリに頼る必要がありません
- 設問は候補者の目に触れる前に2段階の品質ゲートを通過します
- 認知能力・状況判断・行動特性・AIフルエンシーにわたる職種専用のアセスメント根拠。結果はパネルが確認します
- コンプライアンスを優先した設計 — 根拠はパネル向けに整理され、判断するのはパネルです
職種のキットを入手する
各キットは、同じ13ステップを1つの職種に当てはめ、その職種向けの資料を揃えています。
- 求人票
- 検索クエリとスカウト文
- ワークサンプル
- 職種に合わせたドメイン面接質問と回答ガイド
- インタラクティブ評価シート
- 30-60-90日プラン
- ブランド入りPDF
- AIプロンプトパック(4D)
閲覧はすべて無料です。ダウンロードにはメールアドレスが必要です。
11件の採用キット
- AI Engineering
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Every step to hire the engineer who builds agents that plan, act and recover on their own — and can prove the loop is safe to run.
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Forward Deployed Engineer
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Every step to hire the engineer who makes your product work on a customer's own data and systems, and leaves it running safely after they go.
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MLOps Engineer
Machine Learning Operations Engineer · ML Platform Engineer · ML Infrastructure Engineer
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Machine Learning Engineer
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Every step to hire the engineer who trains, evaluates and ships models that hold up once real traffic hits them.
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ライフサイクル全体を開く - AI Research & Data
LLM Evaluation Engineer
AI Evaluation Engineer · LLM Evals Engineer · AI Evals Engineer
Every step to hire the engineer who proves a language-model feature works — and says plainly where the numbers stop meaning anything.
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AI Product Manager
AI PM · Product Manager, AI · AI Product Owner
Every step to hire the product manager who can hold a quality bar on a feature that won't behave the same way twice.
ライフサイクル全体を開く - AI Governance & Safety
AI Governance Lead
Responsible AI Officer · AI Compliance Manager · AI Compliance Lead
Every step to hire the person who tracks where your organisation actually uses AI, and can prove that use is responsible and lawful.
ライフサイクル全体を開く
