Manufacturing
How manufacturing works, and the finance, marketing, data and AI that run it.
The programs
Five programs, one per domain of the Manufacturing sector. Every one is readable straight away, without an account, and you can gauge your level on any of them whenever you want.
Manufacturing
Manufacturing runs on tightly linked operational and financial mechanics: raw materials flow through suppliers, plants, and distribution networks under constant pressure from cost, quality, and throughput targets.
18 lessons · about 4h
- Map a manufacturing value chain end to end and identify where value and margin concentrate
- Assess competitive position and power balance among OEMs, suppliers, distributors, and regulators in a given sub-sector
- Identify which regulations and compliance requirements apply to a manufacturing operation and their practical impact
Finance for Manufacturing
Manufacturing finance runs on capital intensity, working capital discipline, and margin control across long production cycles.
31 lessons · about 6h
- Map a manufacturing value chain end to end and identify where value and margin concentrate
- Assess competitive position and power balance among OEMs, suppliers, distributors, and regulators in a given sub-sector
- Identify which regulations and compliance requirements apply to a manufacturing operation and their practical impact
Marketing for Manufacturing
Manufacturing marketing operates in a B2B, long-cycle, multi-stakeholder environment where buying committees, technical specifications, and distributor networks shape demand far more than mass advertising.
31 lessons · about 6h
- Map a manufacturing value chain end to end and identify where value and margin concentrate
- Assess competitive position and power balance among OEMs, suppliers, distributors, and regulators in a given sub-sector
- Identify which regulations and compliance requirements apply to a manufacturing operation and their practical impact
Data for Manufacturing
Manufacturing runs on data that spans the plant floor and the boardroom: sensor streams from PLCs and SCADA systems, MES production records, quality inspection logs, supply chain and inventory feeds, and equipment maintenance histories.
31 lessons · about 6h
- Map a manufacturing value chain end to end and identify where value and margin concentrate
- Assess competitive position and power balance among OEMs, suppliers, distributors, and regulators in a given sub-sector
- Identify which regulations and compliance requirements apply to a manufacturing operation and their practical impact
AI for Manufacturing
AI is reshaping manufacturing across the value chain, from predictive maintenance and quality inspection to demand forecasting and generative design.
31 lessons · about 6h
- Map a manufacturing value chain end to end and identify where value and margin concentrate
- Assess competitive position and power balance among OEMs, suppliers, distributors, and regulators in a given sub-sector
- Identify which regulations and compliance requirements apply to a manufacturing operation and their practical impact
Manufacturing turns materials into products through capital-heavy operations where efficiency, quality and the supply chain decide who wins. This vertical gives you the big picture, then finance, marketing, data and AI applied inside it.
Key terms
Why specialize in Manufacturing?
Cross-cutting skills are not enough in the Manufacturing sector. It plays by its own rules: a distinct value chain, specific players and balance of power, dense regulation, and key figures you won't find anywhere else. This vertical gives you that sector fluency: first the big picture, then finance, marketing, data and AI applied concretely to Manufacturing, with the calculations, benchmarks and checklists you actually need on the ground.
What you'll be able to do
- Understand how the Manufacturing sector works: value chain, key players and balance of power
- Know the major regulations and laws, the sector's acronyms and vocabulary
- Run the key calculations and read the benchmarks specific to Manufacturing (US and Europe markets)
- Apply finance, marketing, data and AI to the realities of Manufacturing
- Gauge your level with 5 sector assessments and a competency radar
70 lessons across 16 modules and 5 blocks, with a test per lens and a sector competency radar. Free to read, no account required.
The curriculum in detail
Manufacturing: how the sector works
Generalhow manufacturing works: the plant-to-product flow, lean and quality, capacity and utilization, and the supply chain that feeds it.
4 Modules · 18 Lessons
Finance in manufacturing
Financemanufacturing finance: COGS and cost accounting, capacity and fixed-cost absorption, capex and asset utilization, and working capital in inventory.
3 Modules · 13 Lessons
Marketing in manufacturing
Marketingindustrial/B2B marketing: long buying cycles and technical selling, distribution and channel, servitization, and account-based marketing.
3 Modules · 13 Lessons
Data in manufacturing
Datamanufacturing data: sensor and machine data (IoT), OEE and quality metrics, supply-chain and traceability data, and MES/ERP integration.
3 Modules · 13 Lessons
AI in manufacturing
AIAI in manufacturing: predictive maintenance, quality inspection (vision), production and supply optimization, and the OT/safety constraints.
3 Modules · 13 Lessons
Prefer to place yourself first?
Five short assessments, one per domain of the Manufacturing sector. Ten questions each, three minutes, and a competency radar once you have taken more than one.
All sector assessmentsLatest articles
What the blog publishes on Manufacturing, across every discipline.
- Finance$100/kWh and falling: the battery cost math every automotive CFO must ownThe $100 per kilowatt-hour threshold has long been treated as the point at which electric vehicles become cost-competitive with internal combustion equivalents on a per-unit basis. But in a year when consumer confidence has hit a 12-year low and EV demand is softening across major markets, CFOs need to understand exactly what that number means for their break-even models, and where it breaks down.
- DataTrack Boeing's component data the way their regulators now demandWhen a 737 MAX fastener is installed without a traceable birth record, the liability lands on the assembler, not the tier-3 supplier who made it. Boeing's multi-year effort to close that gap shows what end-to-end traceability actually costs to build, and what it costs more to ignore.
- DataHow Siemens built a unified manufacturing data backbone by integrating MES and ERPWhen Siemens restructured its Amberg electronics plant around a tightly integrated MES and ERP stack, the payoff was not just faster reporting, it was a fundamental shift in how production decisions get made. Here is what they actually did, what the numbers show, and what CDOs in discrete manufacturing can take from it.
- FinanceWhen the activist already knows more than you do: lessons from Elliott at HoneywellAI-powered hedge funds can now build a detailed financial thesis on your company faster than your IR team can schedule a response meeting. The Honeywell-Elliott engagement shows what happens when a CFO is prepared for that reality, and what it costs when the board is not.
- MarketingModeling lifetime value across equipment, parts, and service contracts in capital manufacturingIn capital manufacturing, a single equipment sale can be the smallest margin event in a decade-long commercial relationship. CMOs who model customer lifetime value only at the point of iron sale are systematically undervaluing accounts and misprioritizing spend.
- FinanceHow Unilever rebuilt its planning architecture around xP&AUnilever spent years running finance, sales, and supply chain planning in parallel silos, each optimised locally but disconnected at the seams. Its shift toward extended planning and analysis shows what xP&A integration actually requires in a business of that complexity.
Frequently asked questions
What does the Manufacturing vertical cover?
It covers five blocks: how manufacturing works (plant-to-product flow, lean and quality, capacity, supply chain), then finance, marketing, data and AI applied inside the sector. The idea is to start with the big picture of a capital-heavy industry, then look at it through each functional lens.
Who is this for if I don't work in a factory?
It works for anyone who deals with manufacturers without running production: finance and controlling roles, B2B marketers selling into industry, data and IA teams, investors and consultants. The sector blocks explain the operational vocabulary (OEE, bill of materials, capacity) that the rest of the content assumes.
Where should I start?
Start with "Manufacturing: how the sector works" unless you already know the plant floor. Capacity, utilization and the supply chain drive the finance, the data and the AI use cases, so reading the functional blocks first tends to leave gaps.
Is there a certificate or diploma at the end?
No. There is no diploma, no state-recognised certification and no affiliation with a school or university. Reading is free and open; an account only saves your progress.
What makes manufacturing finance different from finance in general?
Fixed costs and capacity. In manufacturing, COGS depends on cost accounting choices, unit cost moves with fixed-cost absorption across volume, capex and asset utilization set the return, and working capital sits mostly in inventory. Those four mechanics are the content of the finance block.
What does industrial marketing look like compared with consumer marketing?
Long buying cycles, technical selling and few accounts. The marketing block covers exactly that: selling to engineers and procurement over months, managing distribution and channel partners, servitization (selling outcomes and service contracts rather than machines alone), and account-based marketing where a handful of clients carry the revenue.
What is OEE and why does it come up everywhere in manufacturing?
OEE (Overall Equipment Effectiveness) combines availability, performance and quality into one measure of how much of a machine's theoretical output you actually get. It shows up across finance, data and AI in manufacturing because a lost point of OEE is lost capacity on assets you have already paid for.
Which AI use cases actually work on a production line?
The AI block focuses on four: predictive maintenance, quality inspection by computer vision, production and supply optimization, plus the OT and safety constraints that decide whether any of them can be deployed. Industrial environments limit what you can connect and change, which is why the constraint is treated as part of the use case rather than an afterthought.