Analyzing Sales and Product Performance

Tools to analyse sales, portfolio performance, seasonal variations, price-volume-mix factors

by Andrei Okhlopkov
Associate Director, Private EquityFollow 232

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Description
This publication contains a set of very practical tools to describe, analyze and forecast a company’s sales, profitability and portfolio performance. They are accompanied with professionally designed charts to help communicate the outcomes and can be used for in-house analysis, management or shareholder reports, due diligence or consulting assignments.

The tools:

1) Describe and visualize a company’s actual performance
– Calculate the total, average, median sales and other statistics giving a full picture of the historic sales performance

2) Explain the basis of seasonality analysis
- Draw seasonality patterns on a cycle plot
- Analyse and forecast seasonality based on monthly data.

I have a separate publication which explains seasonality analysis further. You can find it on this link: https://www.eloquens.com/tool/7jLXsr8b/finance/financial-modeling-courses-tutorials/measuring-and-modeling-seasonality

3) Identify the reasons for variations between the years or between the budget and actual (calculate price, volume and mix effects for the whole portfolio and by category).

If you wish to learn more about price-volume-mix analysis you can check out my publication https://www.eloquens.com/tool/zQwBi72a/finance/variance-analysis-excel-templates/price-volume-mix-analysis

4) Provide a scientific basis for making educated predictions of future sales and portfolio performance

– Build trends and explain why commonly used CAGR rarely gives reliable future estimates. CAGR takes only two reference points (beginning and end of analyzed period) and does not take into account possible fluctuations between those points. This section also explains how to tie volatilities to a timeline using standard error and make sensitivities based on that analysis.
– Measure historic volatilities and translate them into model scenarios with a desired level of confidence. In this part we will calculate the standard deviation for quarterly data and see how it is extrapolated to annual amounts.

This Best Practice includes
1 Excel file, 1 PDF file