Using Excel for Business Analysis by Danielle Stein
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Using Excel for Business Analysis by Danielle Stein

Using Excel for Business Analysis A Guide to Financial Modelling Fundamentals by Danielle Stein Fairhurst | PDF Free Download.

Author of Using Excel for Business Analysis PDF 

Danielle Stein Fairhurst

Fairhurst is the principal of Plum Solutions, a Sydney-based financial modeling consultancy. With her talent for analytical modeling and professional approach, Danielle helps her clients create meaningful financial models for business analysis.

Over the past decades, she has worked in a number of industry sectors, including telecoms, information systems, manufacturing, and financial services, with solutions such as business cases, pricing models, and management reports.

She is regularly engaged as a speaker, facilitator, and consultant around Australia and globally. She holds a master of business administration (MBA) from Macquarie Graduate School of Management and has taught management accounting subjects at Sydney University.

Danielle lives in Sydney with her husband and two children, but travels widely and enjoys the challenge of balancing a healthy family lifestyle with her passion for financial modeling pedagogy.

Excel for Business Analysis Contents

  • Chapter  1 What Is Financial Modelling?
  • Chapter 2 Building A Model 
  • Chapter 3 Best Practice Principles Of Modelling 
  • Chapter 4 Financial Modelling Techniques 
  • Chapter 5 Using Excel In Financial Modelling 
  • Chapter 6 Functions For Financial Modelling 
  • Chapter 7 Tools For Model Display 
  • Chapter 8 Tools For Financial Modelling 
  • Chapter 9 Common Uses Of Tools In Financial Modelling 
  • Chapter 10 Model Review 
  • Chapter 11 Stress-Testing, Scenarios, and Sensitivity Analysis In Financial Modelling 
  • Chapter 12 Presenting Model Output

Preface to Using Excel for Business Analysis

This book was written from my course materials compiled over many years of training in analytical courses in Australia and globally most frequently courses such as Financial Modelling in Excel, Data Analysis & Reporting in Excel, and Budgeting & Forecasting in Excel, both as face-to-face workshops and online courses.

The common theme is the use of Microsoft Excel, and I’ve refined the content to suit the hundreds of participants and their questions over the years.

This content has been honed and refined by the many participants on these courses, who are my intended readers.

This book is aimed at you, the many people who seek financial analysis training (either by attending a seminar or self-paced by reading this book) because you are seeking to improve your skills to perform better in your current role, or get a new and better job.

When I started financial modeling in the early nineties, it was not called financial modeling it was just “Using Excel for Business Analysis,” and this is what I’ve called this book.

It was only just after the new millennium that the term financial modeling gained popularity in its own right and became a required skill often listed on analytical job descriptions.

This book spends quite a bit of time in Chapter 1 defining the meaning of a financial model as it’s often thought to be something that is far more complicated than it actually is.

Many analysts I’ve met are building financial models already without realizing it, but they do themselves a disservice by not calling their models, “models”! However, those who are already building financial models are not necessarily following good modeling practices as they do so.

Chapter 3 is dedicated to the principles of best modeling practice, which will save you a lot of time, effort, and anguish in the long run. Many of the principles of best practice are for the purpose of reducing the possibility of error in your model, and there is a whole section on strategies for reducing error in Chapter 4.

The majority of Excel users are self-taught, and therefore many users will often know highly advanced Excel tools, yet fail to understand how to use them in the context of building a financial model.

This book is very detailed, so feel free to skip sections you already know. Because of the comprehensive nature of the book, much of the detailed but less commonly used content, such as instructions for the older Excel 2003 users, has been moved to the companion website at steinfairhurst.

References to the content on the website, and many cross-references to other sections of the book, can be found throughout the manuscript. 

Using Excel for Business Analysis Overview

This book has 12 chapters, but these can be grouped into three parts. Whilst they do follow on from each other with the most basic concepts at the beginning, feel free to jump directly to any of the parts.

The first section Chapters 1 to 3 addresses the least technical topics about financial modeling in general, such as tool selection, model design, and best practice. The second section Chapters 4 to 8—is extremely practical and hands-on.

Here I have outlined all of the tools, techniques, and functions in Excel that are commonly used in financial modeling. Of course, it does not cover everything Excel can do, but it covers the “must-know” tools. The third section Chapters 9 to 12 is the most important in my view.

This covers the use of Excel in financial modeling and analysis. This is really where the book differs from other “how-two” Excel books.

Chapter 9 covers some commonly used techniques in modeling, such as escalation, tiering tables, and depreciation how to actually use Excel tools for something useful!

Chapter 11 covers the several different methods of performing scenarios and sensitivity analysis (basically the whole point of financial modeling to my mind!).

Lastly, Chapter 12 covers the often-neglected task of presenting model output. Many modelers spend days or weeks on the calculations and functionality but fail to spend just a few minutes

Or hours on charts, formatting, and layout at the end of the process, even though this is what the user will see, interact with, and eventually use to judge the usefulness of the model.

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