The holistic financial model approach to scenario planning and common pitfalls
Any views or opinions expressed are solely those of the author and do not represent those of any companies that the author is or has been working for.
The importance of scenario planning during times of uncertainty
The COVID pandemic and record inflation has highlighted the importance of agile scenario planning. This technique of scenario planning gives businesses a competitive advantage since they are proactively looking at growth opportunities or tackling controllable risk. In its basic form, a financial plan is the financial representation of an organization’s strategy. It is a way to financially demonstrate how the company’s strategy will generate the most return from limited resources in the most effective and efficient way. This applies to all organizations, including small and medium enterprises (SME), public sector bodies, non-profit organizations and commercial corporates. Scenario planning allows businesses to calculate and evaluate different situations. The key change during the pandemic for many businesses was a shift in focus away from growth towards survival or solvency. The ability to evaluate how actions will impact cashflow enables a business to manage its resources more effectively and recover from the pandemic quickly.
Holistic financial modelling
Scenario planning can be considered as a form of contingency planning. It is an integral part of the business decision making process because businesses can use it to assess the outcome of their decisions through playing with scenarios.
Successful financial modelling is an iterative process. Results are measured against a model’s output so that businesses can investigate the root cause and make more informed decisions. This iterative process serves two purposes:
- An indication of how “accurate” the model is in projecting the future.
- It reinforces the idea that business planning is a continuous process of improvement.
A holistic approach links what happens in the top line (sales and revenue) to the bottom line (profit) whilst spelling out the investment and resources (capital investment and cash) that are needed to support top line evolution. This means any plans made using this approach will impact the cashflow, the balance sheet and the profit and loss (P&L).
Using sales as an example, the top line of revenue is typically the first focus. A holistic approach considers how the change in sales impacts cash collection (cashflow), inventory
(balance sheet) and the manufacturing or supply chain (cashflow and balance sheet and P&L).
This approach also promotes transparency. Where transparency exists, the stakeholders of the different departments can have an open and frank review of all risks and opportunities. This gives credibility to the simulation and ensures that financial planning is aligned with corporate strategies.
The importance of data integrity in financial modelling
Financial scenario planning can only contribute to business decision making if the results are generated from reliable and consistent data as well as augmented with human intelligence. The commonly acknowledged attributes of good data are timeliness, consistency and accuracy but in addition the data should be fit for purpose. Defining which data is fit for purpose is dependent upon which question the business is trying to answer. Time series data can provide a basis for any simulation, but teams need to look beyond traditional accounting if financial modelling is to encompass the whole financial lifecycles including cashflows, balance sheet and ultimately profit and loss.
For example, time series data may not be sufficient to simulate the impact of a business opening an online distribution channel if the business does not already have a good online presence. Non-traditional inputs will need to be integrated. For example:
- Consumer buying behavior
- Online presence and non-online presence
- Competitor analysis
- Production speed
- Costs to consumer online vs in-store
Some of these inputs may be available from data collected via customer relationship management (CRM) and enterprise resource planning (ERP) solutions but they may be used disparately in other models. Therefore, to ensure a coordinated approach, the custodian of the data should be involved in the planning process to ensure the right type of data is collected for any simulation.
The four common pitfalls in financial modelling
Given the importance of scenario planning as a tool to model and evaluate the financial impact of different situations, it is important to have an appropriate platform on which to deliver the simulation. Very often organizations focus on the speed and functionality of the tool rather than reviewing its operational and planning processes.
Financial modelling is a process and the financial model simply serves as a framework designed around this process. Therefore, inefficiencies in any part of the process should be weeded out. This will help to promote collaborative planning rather than allow planning to be a cumbersome task.
Other reasons why financial modelling fails to support predictive analytics include:
- Disconnected financial modelling
Working in silos is one of the biggest risks for financial modelling. It leads to multiple versions of the truth which distracts stakeholders from tackling the main question(s) at hand. It also leads to a lack of cashflows visibility throughout the plan. The reason for the disconnection is a lack of collaboration between the business and finance as well as a lack of finance leadership of the process. On top of this, on occasion different areas of the business, although connected, are not always coordinated at a planning level.
- Reliance on spreadsheets
Many organizations still use spreadsheets to prepare a financial plan. Although they are relatively inexpensive and readily available, spreadsheets simply do not have the capability to support complex scenario modelling. Spreadsheet tools are known to be error prone. For example, Tesco had an accounting error back in 2014 that overstated their profit by GBP 250m as a result of spreadsheets. Furthermore, these tools are not collaborative because they do not allow for simultaneous multi-user access.
Assumptions reflect business processes and form the basis of most model calculations. They represent the conditions in which the business operates. Ineffectual assumptions slow down the efficacy of the model and reduce the accuracy of each simulation.
- Lack of clarity
A common problem encountered by businesses during financial modelling is not clearly identifying the question they want their model to answer. This clarity is the cornerstone for effective financial modelling. Otherwise, the simulations will not provide any actionable insight to support business decisions. Lack of clarity can also result in endless changes to the scope and specification of the model and its simulations. Scenario planning is not meant to provide 100% accuracy. It is designed to provide actionable insights and enable business agility.
Here are four key takeaways for holistic financial modelling.
- It is an iterative process that encourages continuous business improvement.
- It encompasses the whole organization and all three financial statements.
- It requires a collaborative approach where finance and operations work together to find actionable insights.
- The goal needs to be clear in order to avoid endless modifications to the financial model or risk the model not fulfilling its core purpose.
Written by: Simone Collins, ACCA and FPAC
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