RapidKnowHow: STRATEGY CONSULTING Leadership Delivered

RapidKnowHow: AI-TRANSFORMATION Leadership Delivered
Drive results with Use-Case Discipline, Data & Governance, and MLOps at Scale. Includes tools for readiness, prioritization, ROI/payback, data governance, build-vs-buy, and MLOps planning. Informational only — not legal/compliance advice.
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Contents 1) Model & Principles 2) Diagnostic Rubric (0–10) 3) 12-Month Roadmap 4) 90-Day Sprint 5) Operating System (weekly) 6) Metrics That Matter 7) Scripts & Templates 8) Interactive Tools 9) Risks & Safeguards 10) Next Steps & CTA

1) Model & Principles

AI Transformation = Strategy × (Use-Cases + Data + MLOps + Change)

  • Use-Cases — start with revenue/cost outcomes and winnable pilots
  • Data — quality, access, security & ownership
  • MLOps — deploy, monitor, and iterate safely
  • Change — upskill, comms, incentives, governance
Ship small, prove value in weeks, codify learnings into playbooks.

2) Diagnostic Rubric (score 0–10)

Strategy & Alignment

  • 0–2: Tools without outcomes
  • 3–4: Themes; loose targets
  • 5–6: 2–3 outcomes with owners
  • 7–8: Roadmap w/ gates
  • 9–10: Company-wide with scorecards

Data & Governance

  • 0–2: Unknown sources; ad-hoc access
  • 3–4: Some catalogs; basic PII flags
  • 5–6: Owners, SLAs, role-based access
  • 7–8: Lineage, retention, audits
  • 9–10: Automated controls & alerts

MLOps & Platforms

  • 0–2: Notebooks only
  • 3–4: Manual deploys
  • 5–6: CI/CD & model registry
  • 7–8: Monitoring & rollback
  • 9–10: Multi-tenant, auditable, scalable

People & Change

  • 0–2: Lone champions
  • 3–4: Pockets of skill
  • 5–6: Training paths & communities
  • 7–8: Roles, incentives, comms
  • 9–10: Org-wide adoption & governance

3) 12-Month Roadmap

Q1 — Baseline & Pilot

  • Pick 2 use-cases; define KPIs
  • Data access & privacy basics
  • Pilot infra (tracking, alerts)

Q2 — Prove & Package

  • Deliver 1–2 measurable wins
  • Document playbooks & guardrails
  • Build-vs-buy decisions

Q3 — Scale & Automate

  • Model registry, CI/CD, observability
  • Role-based access; secrets mgmt
  • Training & change program

Q4 — Institutionalize

  • Scorecards; budget integration
  • Risk & compliance audits
  • Plan next FY

4) 90-Day Sprint

Days 1–30

  • Select use-case & KPI
  • Access data; define privacy
  • Baseline & design experiment

Days 31–60

  • Ship v1; monitor quality
  • Measure uplift; fix blockers
  • Draft playbook

Days 61–90

  • Scale or kill; decide build/buy
  • Train users; publish case note
  • Prep next use-case

5) Operating System (weekly)

  • Mon: use-case board & risks
  • Wed: ship improvement or data fix
  • Fri: metrics & decision log (kill/scale)
Done = shipped change, not a meeting.

6) Metrics That Matter

  • Value: € impact / month (savings or revenue)
  • Time-to-first-value (days)
  • Adoption (% target users using weekly)
  • Model health (drift, latency, errors)
  • Data quality (freshness, completeness)

7) Scripts & Templates

Exec one-liner

We’re targeting {{OUTCOME}} by {{DATE}} with {{USE-CASE}}. Data is ready, privacy covered, and success = {{KPI}}. We’ll ship v1 in {{WEEKS}} weeks.

Use-Case brief (1-pager)

Hypothesis • KPI & baseline • Users • Data sources • Privacy notes • Experiment design • Decision rule (ship/kill) • Owner • Date

8) Interactive Tools

🧭 AI Readiness Score & 90-Day Plan
🧮 Use-Case Prioritizer (RICE)
💶 ROI & Payback Estimator
🛡️ Data Governance Snapshot
🧩 Build vs Buy Decision Helper
⚙️ MLOps Planner — Release & Monitoring
If outputs don’t appear: ensure JavaScript is allowed for this page or switch to “Custom HTML” (frontend view executes JS).

9) Risks & Safeguards

  • Shadow AI & data leakage — set policies, RBAC, and red-team prompts
  • Over-automation — keep humans in the loop for material decisions
  • Model drift — monitor, retrain cadence, rollback
  • Regulatory — privacy, IP, model transparency
  • Change fatigue — show wins fast; train & support users

10) Next Steps & CTA

Now: Run the tools (Readiness, Prioritizer, ROI, Data, Build-vs-Buy, MLOps).

Then: Launch one 30-day pilot and publish a case note.

Privacy: This demo runs locally in your browser.
RapidKnowHow + ChatGPT | AI-TRANSFORMATION Leadership Delivered
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The RapidKnowHow + ChatGPT – LEADERSHIP DELIVERED SYSTEM – compresses time-to-insight to minutes, aligns teams on what to do next, and scales your competitiveness via licensable, partner-ready action-guides across sectors and regions. – Josef David

Strategy & Positioning

  • ICP — Ideal Customer Profile: the type of company or buyer you serve best (e.g., “mid-market industrials in EU”).
  • GTM — Go-to-Market: how you win customers (channels, funnel, coverage).
  • CTA — Call to Action: the concrete next step you ask for (e.g., “Book a 30-min fit call”).
  • NPS — Net Promoter Score: loyalty metric from −100 to +100 based on “recommend?” survey.

Problem-Solving & Prioritization

  • MECE — Mutually Exclusive, Collectively Exhaustive: structure issues so items don’t overlap and cover the whole problem.
  • ICE — Impact × Confidence ÷ Effort: quick way to rank initiatives by payoff versus difficulty.
  • RICE — Reach × Impact × Confidence ÷ Effort: prioritization adding “how many affected” (Reach).
  • H1 / H2 / H3 — Hypotheses 1/2/3: statements you test to explain the outcome gap.
  • A/B — A/B Test: run version A vs B to see which performs better, statistically.

Finance & Economics

  • ROI — Return on Investment: (benefit − cost) ÷ cost; we also use “12-month ROI”.
  • EV — Expected Value: price or fee × win probability (used in proposal economics).
  • EBIT — Earnings Before Interest & Taxes: operating profit measure; often a target KPI.
  • TCO — Total Cost of Ownership: full cost to build or buy (setup + run + maintenance).
  • KPI — Key Performance Indicator: the success metric you’re aiming to move (e.g., “gross margin +3 pts”).

AI, Data & Platforms

  • MLOps — Machine-Learning Operations: deploy, monitor, retrain and govern models safely.
  • CI/CD — Continuous Integration / Continuous Delivery: automated build, test and deploy pipeline.
  • PII — Personally Identifiable Information: data that can identify a person; needs special handling.
  • RBAC — Role-Based Access Control: users only see data and tools allowed by their role.
  • Model Registry — System of record for model versions and approvals.
  • Drift — Model/data performance shift over time; requires monitoring and retraining.
  • GenAI — Generative AI: systems that create text, images, code, etc., from prompts.

Sales, Pipeline & Delivery

  • CRM — Customer Relationship Management: system to track contacts, deals and activities.
  • Win Rate — % of qualified opportunities you close (not an acronym, but core metric).
  • PMO — Project Management Office: function that governs large projects and portfolios.

Planning & Cadence

  • Q1 / Q2 / Q3 / Q4 — Calendar or fiscal quarters (3-month blocks).
  • FY — Fiscal Year: your accounting year (e.g., FY2026).
  • v1 — Version 1: first working release you ship to users (“prove value fast”).
  • Sprint — Fixed timebox (often 1–2 weeks) to build and ship increments.

Commercial Packaging & Offers

  • Pilot — Small, time-boxed engagement to prove value and de-risk a larger rollout.
  • Tiered Offer — Three options (e.g., Pilot / Core / Flagship) to match scope and price to value.
  • Risk Reversal — Mechanism that reduces buyer risk (e.g., milestone-based fees or opt-out gates).

Governance & Compliance

  • SLA — Service-Level Agreement: commitments on availability, quality or timeliness.
  • Audit Trail — Record of who changed what and when (models, data, access).
  • Guardrails — Technical and policy limits that keep AI use safe and compliant.
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