This is a question we are regularly asked and needs to be considered at the start of any modelling discussion.
The key aspects that we delve into between excel and software are:
- Stakeholders – who is going to be using the model?
- Functionality – what is the model being used for?
- Time scales – when is the model needed?
- Cost – how much will it cost, and what are you prepared to pay?
There is a separate topic on what constitutes a financial model, but for the purpose of this article, a financial model is forecasting all three financial statements (profit & loss, balance sheet and cash flow).
The different stakeholders of a model can be vast, ranging from the different internal users of a model (finance teams, sales & marketing, management and the Board) to a host of external users (banks, investors, shareholders). Both of these groups can be further subdivided and divided again; each stakeholder will have different objectives, access to software and knowledge.
This is where Excel-based financial models can be fairly robust. Most of us know how to use an Excel spreadsheet and find the fundamental information, and nearly all devices have an Excel programme or something that can read it. If you need to present the information in different formats for different groups, you can add a new tab.
Software is usually somewhat limited by who is trained to use it, the number of licences available and the different system requirements. This is improving as software tools move to a SaaS model with subscriptions to cloud platforms, but the number of licences then becomes a more significant challenge. Plus, from a data integrity point of view, do you really want third parties and untrained users accessing live data?
However, if the model only needs to be amended by a select few and the stakeholders are happy with a simple format (say a PDF view), a software-based model would be sufficient. A finance team can control access and reports can be exported to be reviewed and commented upon, for example, an annual budget or small loan application.
Functionality can have a big role to play in determining whether an Excel or software-based model is needed. This is also the area where financial models evolve most over time. Once you have an end goal, the stakeholders are unlikely to change, but additional areas might need to be included as a model is developed. For example, if you are working on the sales forecast the inclusion of a new product line, or a new geographical area can have a key impact.
This is where planning is key, and the best way we have found to achieve this is by putting pen to paper (or whiteboard) and tracing each item’s journey through the financial statements, before returning to the start and checking through again. However, at each stage, you need to consider whether the complexity matches the objective (i.e. is the assumption material to the business?). The more straightforward the process, the more standard the assumptions, the more likely software will do this quicker and more efficiently than Excel.
If the model is being used to support the normal budgeting process, and there are no significant changes year-on-year, software can handle this with ease. In fact, many of the growing cloud platforms have different applications that can plug into your existing information and extrapolate with some high-level input from you. This then creates something that is live and agile to your business. It also provides an easy way for you to improve management reporting and your relationship with key financial stakeholders.
If you are considering a financial transaction (which could range from an acquisition of another business, a sale of your own business through to taking on private equity or complex debt) than a bespoke Excel model becomes more attractive.
One of the key issues we have faced on a financial transaction is that some software applications do not have great functionality for a reviewer to carry out due diligence and manipulate the model to test different scenarios. Assumptions can be hard to determine, and calculations cannot be viewed in a “black box” of pre-coded calculations. Furthermore, running various scenarios can quickly be overwhelmed on a software-based model when the variables are complex or multiple; potentially leading to oversimplification or a larger margin for error.
Within Excel, the builder has the opportunity to create a detailed narrative, directly alongside the calculations and include additional calculations for scenarios with the addition of new rows, rather than having to potentially remove or rebuild portions of the software inputs.
There is also a perception within the market that an Excel model is more attractive to Investors. They can take it away and play with it themselves; it can be plugged into their own templates and analytics much easier than a PDF export.
Once a software-based model has been set up and integrated with your normal accounts software, running a forecast report is very quick. Depending on the assumptions being changed, these can be processed quickly or dynamically based on historical information.
Excel models can be more varied. In some cases, a template financial model can be used, which cuts down significantly on the build time, but can mean that certain functionality or detail in the assumptions is lost.
The more complex the assumptions, and the scenario the forecast is being built to address, the longer it takes to build in Excel. Our preference is to start from a blank or nearly blank Excel sheet, as the wrapper for a model is always somewhat similar. This means that we are forced to consider each section in turn and identify what mechanics work best in this particular situation, rather than applying a one size fits all approach.
In most cases, a software-based financial model will be cheaper to set up and amend than an Excel-based model, unless using a simple template. The reason for this is that the software can interrogate your data much more easily and has a pre-set directory of calculations and assumption types. We implicitly trust technology to perform calculations, and the lack of human intervention generally means errors are likely to be reduced. However, as with most things, cheaper does not always mean better – the right option will be determined by the model’s requirements and purpose.
Alternatively, an Excel model requires the hours to be put in by the model builder to understand the business, understand the model’s scope and objective, build the model, test and review the model, and then present it to you and gather feedback.
In most cases where we are building a financial model in Excel, we are also providing advice on the wider scenario or transaction. Consequently, the goal or understanding might change as the model is being developed, and further changes are needed. This might take additional time, but it is normally far more efficient to implement within Excel than it would be in a software-based model.
Ultimately the choice of whether to use Excel or software is up to you and dependent on the purpose of the model itself. A software-based model is ideal for businesses seeking a tool to help with budgeting, rolling forecasts and small loan or funding applications. It can become part of a business’s normal financial fabric and act as a sense check and monitor. Where a transaction is involved, or the stakeholders have vastly different objectives, an Excel model becomes more robust and beneficial.
However, there is an ease and familiarity to Excel that can be navigated quickly and adding new elements (if built correctly) can be straightforward. That’s not to say how we use Excel for modelling has remained the same from the start, it has evolved over time, each new model providing a new challenge and a new iteration of your approach or thinking.
If you’re unsure of which approach is right for you, then discuss it with your financial advisor (be that your accountant or a corporate finance advisor) and they will be able to help you identify the right way forward.
This article was written by Nathan Young, Strategic Corporate Finance Manager at Price Bailey. If there is anything in this article that you would like to discuss or find out more about, please contact Nathan on the form below.
Alternatively, if you would like to try Excel modelling yourself, we would recommend the ICAEW’s Financial Modelling Code and their Twenty Principles for Good Spreadsheet Practice – which should be mandatory reading for anyone using Excel, in my opinion.
We always recommend that you seek advice from a suitably qualified adviser before taking any action. The information in this article only serves as a guide and no responsibility for loss occasioned by any person acting or refraining from action as a result of this material can be accepted by the authors or the firm.