In times of rapidly changing trading environments, it is more important than ever that business decisions are based on reliable data. Clearwater International’s Financial Modelling team discuss the benefits of financial modelling in today’s new world of data.

Imagine a manufacturing business which services customers globally that is suffering from a shortage of HGV drivers and hold-ups at ports resulting in unpredictable delivery times, delays, and unknown shipment amounts. This could easily result in delayed or even cancelled sales and lost customers. Would the cost of hiring ten new HGV drivers at a premium price be worth it?

In such situations, the business needs to know the impact of their key ‘what if’ questions on its top line and cash. So where exactly should it turn? The answer is data-driven financial modelling.

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Financial modelling is particularly useful in M&A transactions.

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The importance of financial modelling and data

Our scenario is just one example of how financial modelling at a granular level is becoming increasingly important to businesses and investors. Indeed, we at Clearwater International see this daily as clients grapple with how to best utilise the ever-increasing amounts of data available to decision makers.

In particular, a focus on how data can be used effectively is becoming more and more common among our private equity (PE) clients looking to translate historical data into improved future performance for their portfolio companies. In the past it might have taken weeks to investigate the root cause of unexpected business performance, potentially delaying all important actions being taken. Today, data-driven, dynamic financial models can yield results in real-time.

Utilising historical data to inform decision making

Today, virtually every business collects and owns information across a vast range of data points, covering all aspects of the business.

Through data analysis this information can be used to provide additional insights, such as product-level profitability, which can in turn substantiate business planning assumptions and be used as an effective tool, transforming the vast quantity of data into actionable insights.

Data can also be integrated with other KPIs across the business. For instance, should the manufacturing business decide to produce and store additional product to safeguard its supply given a shortage in delivery capacity? It would need to consider many practical and financial aspects, covering: production schedules, storage, working capital, and even potential stock obsolescence. In this situation it becomes even more important to understand exactly what might happen on a given day and how this could impact the wider business.


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Rather than being forced onto the back foot by external pressures, investors want to proactively construct scenarios that can be run through their portfolio companies’ financial models to immediately evaluate the impact. In short, they want answers to the key questions impacting the growth of a business.

  • Will we have enough free cash to launch a new product?
  • What could be the impact on sales if we open stores at ten new locations over the next twelve months?
  • Should we hire more staff; what will be in the impact on profitability and cash generation?

A focus on how data can be used effectively is becoming more and more common among PE clients looking to translate historical data.

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Tom Barnwell, Director, Clearwater, says:

“Data-driven financial modelling is a great way of both safeguarding your business against risks and preparing for a sale event or refinance. A well designed and constructed model provides high quality and reliable information on which to base key decisions for the benefit of all stakeholders. Clearwater International’s financial modelling team are experienced in working with clients across the spectrum and can work with entrepreneurs to create these solutions before they may need them.”

Financial modelling analytics and M&A

Financial modelling is particularly useful in M&A transactions. Well-constructed, user-friendly models which clearly set out forecast performance, along with the key drivers of this performance, are much easier for external advisors and investors to understand than an internal spreadsheet. Models like this also allow future buyers to place greater confidence in the forecast and in management’s ability to deliver, leading to a more attractive investment proposition.

At Clearwater our broad client base means we have extensive experience building models across a range of clients, industries, and situations, for use by both management teams and potential buyers. Crucially, during a deal process we combine this experience with our extensive understanding of due diligence requirements and our oversight of the wider context of a transaction, meaning we are able to save valuable time for investors and management teams that are going through the demands of the due diligence process.

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Talk to the author

Tom Barnwell


I have been working in Debt Advisory since 2008, having previously trained as an accountant within the big 4. I am now one the Partners in our European Debt Advisory team here at Clearwater and have led more than 100 debt raise and refinance transactions across multiple funding structures for my clients.


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