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49 posts tagged with "Business"

Vision, GTM, customer acquisition and operating a company

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High Output Management — Grove’s Production System for Managers

· 23 min read
AI Playbook author

A manager’s output is not the hours they personally work. It is the output of the organisation under their influence or control. That single redefinition—Grove’s central move—turns management from a status role into a production problem: identify the limiting step, raise leverage, design the factory of work so the whole system produces more.

Business Administration Reading Map: Core Books for Strategy, Finance, Leadership, Sales and Operations

· 13 min read
AI Playbook author

Business Administration is a set of durable mental models—how value is created, how numbers tell the truth, how strategy concentrates power, how managers raise output, how capital is allocated, how people work across cultures, and how ventures sell, negotiate, position and communicate. This series turns core books into expanded, chapter-depth practitioner guides (frameworks, tables, negative cases, consulting translation and capstone sheets)—not skim summaries—so you can use them on pursuits, product bets, operating reviews and board conversations.

The Outsiders: Unconventional CEOs and the Capital Allocation Blueprint

· 19 min read
AI Playbook author

Most CEO scorecards still celebrate growth theatre: bigger revenue, bigger headcount, bigger deal announcements, bigger headquarters. William Thorndike’s The Outsiders tells a different story. The best long-term value creators were often unfashionable capital allocators—operators who treated the CEO job less like a celebrity general and more like an investor with operating control. They obsessively asked one question: What action most increases per-share intrinsic value? Everything else was noise.

The Personal MBA — Josh Kaufman’s Mental Models for Business

· 29 min read
AI Playbook author

Business school sells credentials, networks, and a structured map of how organisations work. The Personal MBA sells something different: a portable lattice of mental models—reusable concepts you can apply to any offer, market, team, or system without waiting three years or spending six figures. Kaufman’s claim is blunt: if your goal is to understand how businesses create and capture value, you do not need an MBA. You need the models—and deliberate practice applying them.

The Visual MBA — Jason Barron’s Course-by-Course Practitioner Notes

· 15 min read
AI Playbook author

Most MBA value is not the diploma—it is a shared visual language for decisions: 2×2s, process flows, simple equations, and rules of thumb you can sketch on a whiteboard under time pressure. Jason Barron’s The Visual MBA compresses that language from a full MBA experience into picture-first notes. This article turns those course chapters into practitioner frameworks you can reuse in consulting, product, and general management.

Valuation: Measuring and Managing the Value of Companies — A Complete Practitioner Synthesis

· 20 min read
AI Playbook author

Companies are not worth their logo, their last earnings print, or the story that fits this quarter’s narrative. They are worth the cash flows they can generate for capital providers, discounted for risk and timed correctly—subject to a small set of economic laws that survive every market fashion. Valuation is the operating manual for those laws.

AI-Focused MBA: Complete Curriculum and Resource Guide

· 32 min read
AI Playbook author

A strong AI-focused MBA should not replace traditional management education with technical AI training. It should combine four pillars:

  1. MBA fundamentals — economics, finance, accounting, strategy, marketing and operations.
  2. Leadership and organisational capability — communication, negotiation, change, culture and mindful management.
  3. AI and data literacy — machine learning, generative AI, analytics, experimentation and AI product management.
  4. Responsible execution — governance, risk, regulation, cybersecurity, operating models and financial value.

This resembles the direction taken by programmes such as Wharton’s AI for Business major, Kellogg’s MBAi and NYU Stern’s Tech MBA. Wharton separates AI education into technical foundations and societal/ethical impact; Kellogg combines MBA, technical and integrated AI cores; NYU combines a business core, technology core and experiential projects. (Wharton OID)

The Consulting Handbook Learning Map: Templates, Path, and Best Resources for Technical Consultants

· 14 min read
AI Playbook author

Technical specialists who want to consult rarely lack skills. They lack a commercial operating system: niche, offers, discovery, proposals, pricing, delivery rhythm, and a pipeline that does not depend on luck.

This page is that map. It expands the open Consulting Handbook (MIT) curated for data engineers, software engineers, analysts, and data scientists—then layers a recommended study order, Free/Paid labels, and deep links into this playbook’s consulting articles.

How to Generate Leads in Consulting: An End-to-End, Practical Guide

· 44 min read
AI Playbook author

Consulting lead generation is the process of identifying organisations with important problems, earning their attention, starting credible conversations, and converting those conversations into qualified consulting opportunities.

It is not simply:

  • Posting frequently on LinkedIn.
  • Sending hundreds of cold emails.
  • Attending networking events.
  • Asking everyone whether they “need consulting.”
  • Offering a free call without a clear reason.
  • Producing generic reports about popular topics.

Those activities may create visibility, but visibility alone does not create a consulting pipeline.

A consulting lead is generated when five conditions come together:

Relevant problem × credible expertise × access to the buyer × commercial urgency × clear next step

Consulting is also different from selling a standard product. The client is usually buying an uncertain future outcome rather than a predefined object. Before engaging a consultant, buyers often need to believe that:

  1. The problem is significant enough to address.
  2. The consultant understands the problem.
  3. The consultant can navigate the organisation.
  4. The consultant can reduce delivery and political risk.
  5. The expected benefit is greater than the cost.
  6. The consultant will not create additional problems.
  7. The consultant is more suitable than internal delivery, another consultancy, or doing nothing.

This means consulting lead generation is fundamentally a trust-building and problem-development process.

Designing an EMEA Go-to-Market Strategy and Roadmap for an AI Solution

· 37 min read
AI Playbook author

A go-to-market strategy for an AI solution is not simply a marketing plan. It is the coordinated design of:

GTM=Target market×Urgent problem×Differentiated solution×Commercial model×Trust×Distribution×Adoption\text{GTM} = \text{Target market} \times \text{Urgent problem} \times \text{Differentiated solution} \times \text{Commercial model} \times \text{Trust} \times \text{Distribution} \times \text{Adoption}

For AI products, the “trust” component is particularly important. A technically impressive solution can still fail because the buyer cannot establish:

  • Who is accountable for its outputs.
  • Where customer data is processed.
  • Whether the model can hallucinate.
  • Whether regulators will accept it.
  • Whether employees and customers will use it.
  • Whether its financial benefits exceed implementation and operating costs.

In EMEA, the challenge is greater because EMEA is not one market. An AI solution sold in the UK, Germany, the UAE, Saudi Arabia and South Africa may require different hosting, contracting, languages, regulatory controls, partner models and sales motions.

This guide explains the complete process and then applies it to a detailed hypothetical case study: an AI customer-service platform for regulated banks.