Financial data analysis: forecasting, budgeting and financial appraisal

Financial statements analysis tells you how a business has performed. Financial data analysis helps with what to do next. It usually centres on a current issue and an imminent decision, so it starts from forecasts, budgets and appraisals. This topic explains what financial data analysis is, how the tools are chosen, and how to handle forecasting, budgeting and financial appraisal in the Case Study.

What financial data analysis is

Financial data analysis is the identification and analysis of the financial data needed to evaluate an issue and reach a decision. It includes the process and the analytical tools you use. It also includes understanding what a request is asking and presenting the result briefly and clearly to the person who will use it.

You must understand the company and the audience. Telling a chief executive officer the trend in forecast sales, when the figures were already supplied, is not worth receiving. Explaining to a non-financial reader the difference between the cash flow and the contribution of a project, with a view on the assumptions behind it, is very good analysis.

Communication of the output, with judgements, conclusions and recommendations, is the heart of it.

The process has four parts:

1. use suitable analytical tools for the task;
2. calculate accurately and explain the results from the information and assumptions given;
3. evaluate all assumptions, flex the numbers and perform sensitivity analysis; and
4. interpret the results and reconcile them to reach a conclusion that supports recommendations.

Choosing the tool

The tools come from your earlier subjects. They include forecasting and budgeting, financial appraisal and reporting, breakeven and profit-volume analysis for pricing, product mix and profitability decisions, project appraisal, short-term and long-term decisions, risk in decision making, sensitivity analysis and business valuation. The Case Study assumes you know how to use each one. What it tests is whether you know which one fits.

You are not always told which tool to use. Often you must decide. The unifying feature is that financial data analysis tends to focus on a current issue and an imminent decision that will affect future operations. Sensitivity analysis applies to almost every case.

The case gives you information to sift, analyse and evaluate in the context of the business scenario. Be aware of the surrounding issues and the wider context. If information is incomplete, make your own sensible assumptions and complete the calculation. Never stop a calculation to advise the client to provide more complete information. Finishing the work with stated assumptions is how you show professional skill.

Financial forecasting

Financial forecasting is the management process that sets the future course of action towards the firm’s goals, given its economic, technical, competitive, financial and social setting. It is the base for operational, tactical and strategic plans. Because most financial data exercises concern a decision not yet made, a forecast of future results is almost always needed.

Keep these points in mind:

• the subject and context: a project, an activity or the whole organisation;
• the provenance, or source, of the information supplied;
• the degree of accuracy needed;
• the materiality of the subject, and the tolerance for error; and
• the time frame, because beyond a certain point any forecast is flawed.

Companies use forecasts to decide how to allocate budgets. They update them regularly, for example monthly or quarterly, when plans, operations or inventory change. Forecasts can be short term or long term, and management can act on them at once, for example by adjusting production and stock.

In the exam, the first step is always to build the forecast from the information provided, before you change or challenge any critical factor. That gives you an agreed starting point.

Budgeting

Budgeting prepares detailed income and expenditure for a future period, usually one year, and summarises it in financial statements. A budget states the quantitative and financial results that management wants to achieve. It includes estimates of revenue and expenses, expected cash flows and expected debt reduction, and it is compared with actual results to calculate variances.

Forecasting and budgeting differ, but they work together: short-term and long-term forecasts help to create and update a budget.

Financial appraisal and reporting

In a Case Study, a financial appraisal often begins with something that has happened, such as a flood or fire, or something that might change, such as the selling price of an important product. You must calculate the effect and present it to the client for further discussion or a report. As with every forecast, start with the information provided before changing or challenging it.

Consider the provenance of the information, the accuracy needed and the materiality of the matter and the tolerance for error.

Financial appraisal can also support a credit facility. Here the aim is to judge whether the estimates of costs, expenses and revenues are correct and reasonable. They include the selling price, the cost of machinery, the total cost of the project and how it will be financed.

The work usually involves financial modelling in a spreadsheet: take the financial statements of earlier periods and forecast the position over the period of the loan. Then compare each year’s cash flow with the loan instalment, because the cash flow must pay the bank. The test is the company’s debt servicing capacity.

The debt service coverage ratio is calculated for each future period, and if it meets the bank’s norms the loan can be approved.

Worked example: a forecast after a fire

1. Lost sales.
   20 × 3 = ₦60 million.
2. Lost contribution.
   60 × 35% = ₦21 million.
   Fixed costs are unchanged, so the whole contribution is lost.
3. Insurance.
   21 × 60% = ₦12.6 million.
4. Net loss.
   21 − 12.6 = ₦8.4 million.
5. Assumptions and caution. The 60% cover is an expectation, and the claim may be delayed or reduced. The calculation assumes no lost customers and no extra costs, such as overtime on other lines. Flex the insurance recovery, for example at 40%, which would raise the net loss to ₦12.6 million.

Worked example: debt service coverage

1. Ratio.
   Debt service coverage = cash flow available ÷ debt service = 180 ÷ 120 = 1.5 times, above the norm of 1.25.
2. Flex.
   If cash flow falls by 20% to ₦144 million, coverage is 144 ÷ 120 = 1.2 times, below the norm.
3. Judgement. The loan passes in the base case but fails if cash flow is only a fifth lower. The bank may require security or a smaller loan, and management should check how reliable the cash flow forecast is.

Common mistakes

• Restating figures the client already has instead of analysing them.
• Challenging the given figures before building a forecast from them.
• Stopping to ask for more information instead of making stated assumptions.
• Choosing the wrong tool, for example a profit approach where a contribution approach is needed.
• Presenting a single result with no flexing of the key assumptions.
• Writing for a financial reader when the audience is not financial.

Quick revision

• Financial data analysis: identify and analyse the data for a decision, then communicate it.
• Four parts: tool, calculation, assumptions and flexing, interpretation.
• Focus on a current issue and an imminent decision.
• Forecast: start from the given figures, consider provenance, accuracy, materiality and time frame.
• Budget: one year, top-down or bottom-up, with variances.
• Credit appraisal: debt service coverage against the bank’s norm.

Practice questions

These are original questions in the style of the Institute of Chartered Accountants of Nigeria exam. Try each one before you open the answer.

Model answer

The next topic covers breakeven and profit-volume analysis for pricing decisions.

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