6. Model Planning, Structures and Best Practices

Model Planning, Structures and Calculations


  • Learn the main types of logic used and calculations needed in the majority of financial models.
  • Understand the key structures that are used in models to support these calculations.
  • Learn different approaches to the layout of a model and how to link components together in an optimal way.
  • Explore the variations and options that are available, and understand best practices.
  • Develop proficiency in reviewing and understanding models, such as those built by others.


  • Overview. The building of most models (Even for bespoke applications) typically involves using quite common or standard components. This course aims to cover the key logic and structures that form these. It aims to help participants not only to design and build models for themselves, but also to be able to more quickly understand models built by others. Part 1 covers the issues to consider when planning a model, so that it is designed and built in the most optimal way. Part 2 covers some important sub-structures that are often required for certain types of calculations, especially for allocation processes. Part 3 discusses the use of modular structures and the linking of these together, and Part 4 focusses on modelling best practices in an Excel context.
  • Practical Work and Exercises. Readers are expected to build simple examples for themselves as they follow the text. The course also contains downloadable data sets or simple models that allow a reader to do this practical work without having to enter large sets of data or repeat previous steps.
  • Quizzes and Exercises. There are many Quizzes, which are placed throughout the course. Some require the construction of small models or parts of models.


  • Model Planning and Objectives. Addressing the right decision · Context, objectives · Strategy analysis · Economic criteria · Ratio analysis · Decision criteria · Model variables · Flow and granularity · Horizontal or vertical time axis · Data sources and structures · Historical versus forecasted analysis · Logic reversals · Updating requirements · Structural limitations versus parameter flexibility.
  • Allocations, Triangles, Corkscrews, and Waterfalls. Allocations, linear and non-linear · Time allocation with triangles · Corkscrew structures · Waterfall allocations · Checking consistency and error-elimination.
  • Designing for Modularity. Benefits of modularity · Approaches to link modules · Selection and exclusion structures · Consolidation and inclusion structures· Appending data sets together (introduction) · Modelling sequences of decisions.
  • Best Practices in Excel Modelling. Choices of structure ;· Database approaches to modelling · Principles of transparency · Dealing with circularities · Complexity reduction and optimisation.


  • Many Quizzes!