「research-ops」の検索結果

Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).

日本語の概要は準備中です。原文の説明を表示しています。

Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.

日本語の概要は準備中です。原文の説明を表示しています。

最新の公開情報と手元の資料を照合し、事実・推測・提案を分けて調査結果をまとめます。単発の確認、選択肢の比較、人物や企業の調査に合わせて調べ方を選ぶスキルです。

• 手元の資料を最新情報で検証したいとき
• 意思決定のために候補を比較したいとき
• 相談先の人物や企業を調べたいとき

Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission (ISO 13485, EU MDR, FDA 510(k)/PMA/QSR), not the study design.

日本語の概要は準備中です。原文の説明を表示しています。

Use when doing upstream market-research methodology — sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single unsourced number), planning a survey sample size with finite-population correction and per-segment minimums, or scoring candidate market segments against Kotler's measurable/substantial/accessible/differentiable/actionable criteria. Outputs always show the method and the assumptions. For market-research analysts and product-marketing at the sizing/survey/segmentation moment. Distinct from marketing-skill (campaign analytics, attribution, demand-gen) — this is the evidence-building methodology, not live-campaign optimization.

日本語の概要は準備中です。原文の説明を表示しています。

Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this manages money already won).

日本語の概要は準備中です。原文の説明を表示しています。

Continuous product discovery research operations — picking the method that fits the question, recruiting and screening participants, building interview guides, and scoring evidence into insights. Use when planning or running discovery.

日本語の概要は準備中です。原文の説明を表示しています。