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80 Fundamental Models for Business Analysts Descriptive, Predictive, and Prescriptive Analytics Models with Ready-to-Use Excel…

Alberto Scappini

A practical, Excel-ready reference compiling 80 analytical models across strategic analysis, pricing, customer analytics, statistics, forecasting, and optimization that business analysts need to make better decisions.

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What it’s about

80 Fundamental Models for Business Analysts is a comprehensive, practitioner-oriented toolkit that organizes the full breadth of quantitative and qualitative models a modern business analyst needs—from PEST and SWOT through conjoint analysis, customer lifetime value, hypothesis testing, time series forecasting, and Monte Carlo simulation—into one structured reference. Each model is explained with its objective, a plain-English description, worked examples, and a link to a downloadable Excel template, making the book simultaneously a learning resource and an on-the-job guide. The author's philosophy of radical simplicity—start with a clear question, choose the right model, validate the data, communicate the results—runs throughout, ensuring that even non-specialists can implement sophisticated analyses without specialized software. Whether you need to set the right price, segment your customers, test a hypothesis, forecast next quarter's demand, or optimize a marketing budget, this book provides a decision-relevant model and the practical steps to apply it.

The through-line

Who it’s for
A practicing business analyst or analytically-minded manager who wants a single, organized reference of proven models to support faster, better-evidenced decisions across strategy, pricing, customers, statistics, forecasting, and optimization.
The problem
Business analysts must draw on dozens of disparate models spread across multiple specialized sources, with no unified, practical toolkit that covers both strategic and quantitative methods. They feel overwhelmed and uncertain about which technique to choose, lack confidence in their ability to implement advanced methods without specialized software, and worry they are missing important tools.
The plan
  1. Understand the book's organizing principle: classify every analytical need as descriptive, diagnostic, predictive, or prescriptive, then navigate to the relevant section.
  2. Use the strategic analysis models (PEST through Ansoff) to frame the business context and identify key questions.
  3. Apply pricing and demand models to estimate willingness to pay and set revenue-maximizing prices.
  4. Deploy customer analytics models to segment customers, estimate lifetime value, and prioritize marketing investment.
  5. Select and execute the appropriate statistical test or regression by following the decision guide on variable type and distribution.
The payoff
Analysts can quickly select the right model for any business question without consulting multiple sources. · Decisions about pricing, customer investment, strategy, and resource allocation are grounded in quantified evidence rather than intuition alone. · Forecasts are more accurate, better calibrated, and accompanied by honest uncertainty estimates.

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