Leading With Data· a Bicycle Guide

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Mathematical programming optimization models for business and management decision-making

Wisniewski, Mik, Dacre, Tony, 1946-

A practical guide for managers and students on using mathematical programming models to find optimal solutions for business problems involving scarce resources, focusing on application and interpretation over complex theory.

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What it’s about

Managers and business students are constantly faced with complex decisions that involve allocating scarce resources like manpower, finance, and materials to achieve specific objectives. The field of management science, specifically mathematical programming, offers powerful models to find the 'best' or optimal solution in these situations. This book serves as a practical guide to mastering these techniques—from transportation and assignment models to linear, integer, goal, and dynamic programming. Unlike other texts that are either too theoretical for managers or too simplistic for practical use, this book bridges the gap by focusing on problem formulation, solution interpretation, and the real-world management information these models provide. Accompanied by PC software, it empowers readers to not only understand the concepts but also apply them to solve a wide range of business problems, from production scheduling and financial portfolio management to marketing mix and distribution logistics, ultimately enabling more rational and effective decision-making.

The through-line

Who it’s for
The reader is a manager, business professional, or student who needs to make effective, data-driven decisions in complex situations. They want to find the 'best' or most efficient way to use limited resources to achieve their organization's goals, such as maximizing profit or minimizing costs.
The problem
They face complex business problems involving the allocation of scarce resources (manpower, finance, materials, time) among competing activities, and they lack a systematic method for determining the optimal course of action. This makes them feel uncertain, overwhelmed by complexity, and worried that they are making suboptimal decisions, leaving money on the table, or failing to operate as efficiently as possible. They feel a gap exists between their business knowledge and the quantitative tools that could help them.
The plan
  1. Learn to formulate business problems as mathematical programming models by defining objectives, variables, and constraints.
  2. Master the solution methods for key models, starting with Transportation and Assignment, then progressing to the powerful Simplex method for Linear Programming.
  3. Learn to interpret the results, including sensitivity analysis and shadow prices, to derive actionable management insights and answer 'what-if' questions.
  4. Explore advanced models like Integer, Goal, and Non-linear programming to handle even more complex real-world scenarios.
The payoff
You will be able to confidently translate complex business challenges into clear, solvable models. · You will make more profitable, efficient, and data-driven decisions. · You will gain a critical awareness of the role of quantitative models and be able to bridge the gap between business management and technical specialists.

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