Using Excel for Business Analysis. Fairhurst Danielle Stein
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Название: Using Excel for Business Analysis
Автор: Fairhurst Danielle Stein
Издательство: Автор
Жанр: Зарубежная образовательная литература
isbn: 9781119062448
isbn:
Let me make one thing very clear: I am not partial to the use of the word spreadsheet; in fact, you’ll hardly find it used at all in this book.
I’ve often been asked the difference between the two, and there is a fine line of definition between them. In a nutshell, an Excel spreadsheet is simply the medium that we can use to create a financial model.
At the most basic level, a financial model that has been built in Excel is simply a complex spreadsheet. By definition, a financial model is a structure that contains input data and supplies outputs. By changing the input data, we can test the results of these changes on the output results, and this sort of sensitivity analysis is most easily done in an Excel spreadsheet.
One could argue then, that they are in fact the same thing; there is really no difference between a spreadsheet and a financial model. Others question if it really matters what we call them as long as they do the job. After all, both involve putting data into Excel, organising it, formatting, adding some formulas, and creating some usable output. There are, however, some subtle differences to note:
1. “Spreadsheet” is a catch-all term for any type of information stored in Excel, including a financial model. Therefore, a spreadsheet could really be anything – a checklist, a raw data output from an accounting system, a beautifully laid out management report, or a financial model used to evaluate a new investment.
2. A financial model is more structured. A model contains a set of variable assumptions, inputs, outputs, calculations, scenarios, and often includes a set of standard financial forecasts such as a profit and loss, balance sheet, and cash flow, which are based on those assumptions.
3. A financial model is dynamic. A model contains variable inputs, which, when changed, impact the output results. A spreadsheet might be simply a report that aggregates information from other sources and assembles it into a useful presentation. It may contain a few formulas, such as a total at the bottom of a list of expenses or average cash spent over 12 months, but the results will depend on direct inputs into those columns and rows. A financial model will always have built-in flexibility to explore different outcomes in all financial reports based on changing a few key inputs.
4. A spreadsheet is usually static. Once a spreadsheet is complete, it often becomes a stand-alone report, and no further changes are made. A financial model, on the other hand, will always allow a user to change input variables and see the impact of these assumptions on the output.
5. A financial model will use relationships between several variables to create the financial report, and changing any or all of them will affect the output. For example, Revenue in Month 4 could be a result of Sales Price × Quantity Sold Prior Month × Monthly Growth in Quantities Sold. In this example, three factors come into play, and the end user can explore different mixes of all three to see the results and decide which reflects his or her business model best.
6. A spreadsheet shows actual historical data, whereas a financial model contains hypothetical outcomes. A by-product of a well-built financial model is that we can easily use it to perform scenario and sensitivity analysis. This is an important outcome of a financial model. What would happen if interest rates increase by half a basis point? How much can we discount before we start making a loss?
In conclusion, a financial model is a complex type of spreadsheet, whilst a spreadsheet is a tool that can fulfill a variety of purposes – financial models being one. The list of attributes above can identify the spreadsheet as a financial model, but in some cases, we really are talking about the same thing. Take a look at the Excel files you are using. Are they dynamic, structured, and flexible, or have you simply created a static, direct-input spreadsheet?
TYPES AND PURPOSES OF FINANCIAL MODELS
Models in Excel can be built for virtually any purpose – financial and nonfinancial, business-related or non-business-related – although the majority of models will be financial and business-related. The following are some examples of models that do not capture financial information:
■ Risk management: A model that captures, tracks, and reports on project risks, status, likelihood, impact, and mitigation. Conditional formatting is often integrated to make a colorful, interactive report.
■ Project planning: Models may be built to monitor progress on projects, including critical path schedules and even Gantt charts. (See the next section in this chapter, “Tool Selection,” for an analysis of whether Microsoft Project or Excel should be used for building this type of project plan.)
■ Key performance indicators (KPIs) and benchmarking: Excel is the best tool for pulling together KPI and metrics reporting. These sorts of statistics are often pulled from many different systems and sources, and Excel is often the common denominator between different systems.
■ Dashboards: Popularity in dashboards has increased in recent years. The dashboard is a conglomeration of different measures (sometimes financial but often not), which are also often conveniently collated and displayed as charts and tables using Excel.
■ Balanced scorecards: These help provide a more comprehensive view of a business by focusing on the operational, marketing, and developmental performance of the organisation as well as financial measures. A scorecard will display measures such as process performance, market share or penetration, and learning and skills development, all of which are easily collated and displayed in Excel.
As with many Excel models, most of these could be more accurately created and maintained in a purpose-built piece of software, but quite often the data for these kinds of reports is stored in different systems, and the most practical tool for pulling the data together and displaying it in a dynamic monthly report is Excel.
Although purists would not classify these as financial models, the way that they have been built should still follow the fundamentals of financial modelling best practices, such as linking and assumptions documentation. How we classify these models is therefore simply a matter of semantics, and quite frankly I don’t think what we call them is particularly important! Going back to our original definition of financial modelling, it is a structure (usually in Excel) that contains inputs and outputs, and is flexible and dynamic.
TOOL SELECTION
In this book we will use Excel exclusively, as that is most appropriate for the kind of financial analysis we are performing when creating financial models. We often hear it said that Excel is the “second-best solution” to a problem. There is usually a better, more efficient piece of software that will also provide a solution, but we often default to the “Swiss army knife” of software, Excel, to get the job done. Why do many financial modelling analysts use Excel almost exclusively, when they know that better solutions exist? At Plum Solutions, our philosophy is also one of using only “plain-vanilla” Excel, without relying on any other third-party software, for several reasons:
■ No extra licences, costly implementation, or software download is required.
■ The software can be installed on almost any computer.
■ Little training is needed, as most users have some familiarity with the product – which means other people will be able to drive and understand your model.
■ It is a very flexible tool. If you can imagine it, you can probably do it in Excel (within reason, of course).
■ Excel can report, model, and contrast virtually any data, from any source, all in one report.
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