1,000 Small Business Operations Questions, Answered

Most operations advice starts with a tactic and works backward toward a reason. This book starts with the structure and works forward. Part one defines what an operation is made of. Part two applies that definition to 1,000 questions that small business owners actually face.

The result is a reference work rather than a how-to guide. Nothing in it needs to be read in order. An owner can open to their own industry and read how the model accounts for a familiar operating pattern.

Part One: The Operations Ontology

Part one builds the model in seventeen layers. Each layer defines a class of operational object and the relationships that constrain it. The layers are cumulative rather than parallel.

• Part 0 Formal Foundations
• Part 1 Strategy Layer
• Part 2 Demand Layer
• Part 3 Process Core
• Part 4 Resources
• Part 5 Inventory
• Part 6 Quality Management
• Part 7 Planning and Control Hierarchy
• Part 8 Service Operations
• Part 9 Project Management
• Part 10 Facility and Layout Design
• Part 11 Supply Chain and Sourcing
• Part 12 Digital Operations
• Part 13 Human and Behavioral Operations
• Part 14 Sustainability and Safety
• Part 15 Core Axioms
• Part 16 Improvement Philosophies

A question about inventory cannot be answered without the demand layer above it and the process core beneath it. That dependency is what makes the model diagnostic instead of descriptive. It also explains why two businesses with the same visible symptom often need opposite corrections.

Part Two: 1,000 Applied Diagnostics

Part two applies the model to 100 small business industries in the United States, at ten questions per industry. The questions describe common operating patterns rather than search terms. Each answer names the mechanism, then points back to the ontology section that governs it.

Five Examples From the Book

The questions are written the way the problem actually presents itself, not the way a category would describe it. Each answer names the mechanism, then cites the ontology sections behind it. Questions below are reproduced word for word. Answers are reproduced in substance, with punctuation set to house style.

• When the first heat wave hits, which fails first: phones, techs, or warehouse?

  Whichever has the lowest series reliability. A surge exposes the weakest link in a serial system, and it is usually phones (unbuffered arrival spike) before techs. Compute each link's capacity against the surge rate and pre-position buffers deliberately: inventory, capacity, or time. You will pay one.

  §4.3 series reliability, A4 variability-buffer law, §8.1 Erlang C for phones

  HVAC

• When we bought CAD/CAM, which ROI assumption failed first: lab savings, crown volume, or same-day acceptance?

  Usually crown volume and acceptance. The machine's economics require routing eligible cases to same-day, but scheduling templates and habit keep sending them to the lab. The technology decision lacked the infrastructural change (template redesign, presentation scripting) that realizes it.

  §1.1 Structural vs Infrastructural decisions, §12 DigitalOps, A10

  Dental practices

• Why track billable hours to the tenth but never referral-source conversion by matter value?

  Because hours feed the invoice (cash) while referral analytics feed strategy (later). The measurement portfolio is all operations and no demand, and demand is the scarcer resource for a small firm. Instrument source to consult to engagement to value. It will reallocate your relationship time.

  §0.3 measuredBy, §13 Goodhart, §2.2

  Law firms (solo/small)

• Friday revenue grows while Friday profit shrinks. Which line item moves opposite sales?

  Labor and waste. Friday volume triggers overtime, extra prep (over-production for the rush), and expediting chaos. The incremental Friday dollar carries higher marginal cost than the average dollar. Compute marginal Friday profitability. The answer may be fewer covers, better sequenced.

  §1.3 marginal analysis, A4, §7 labor scheduling

  Restaurants (independent)

• At 90% occupancy, why do we discount to fill the last 10%. What does the rate-vs-occupancy curve maximize?

  Nothing. Discounting at high occupancy undercuts your own scarcity value. Revenue management in storage: raise street rates above roughly 85% occupancy, and let occupancy sit at 92% at higher rates rather than 98% at discounted ones.

  §2.3 revenue management, §1.3 marginal analysis

  Self-storage facilities

How the Answers Are Structured

Every answer follows the shape visible above. It names the mechanism the question is circling, explains why the obvious reading is incomplete, describes the structural change the model points to, and closes with the ontology sections and axioms behind it.

Those bracketed references are checkable inside part one. The HVAC answer rests on series reliability, buffer behavior under variability, and Erlang C for phone queues. Any of the 1,000 answers can be traced back to the model that generated it, which is the reason the ontology is written first.

Who This Is For

The book assumes an operator rather than an academic. It is written for owners and managers of businesses roughly between $500,000 and $50 million in revenue, in industries where the owner still sits close to daily operations. No prior background in operations theory is required.

Readers who prefer a structured read of a described situation rather than a reference to browse can try the free diagnostic tool on this site. The methodology page explains the six operational patterns that tool works from.

Read the Full Book

The complete book is embedded below and requires no download. It also reads directly in the browser at the PDF link.

How to Cite This Work

The book is free to read, quote, and link to. Attribution is appreciated and helps other operators find it.

Scope of This Material