ABC analysis based on contribution margin

Customer contribution margin accounting is a fundamental analytical method for measuring customer value. This method maps customer sales, direct costs, and overhead costs to assess the customer’s contribution to the earnings for the entire company (Homburg & Wieseke, 2011).

The starting point for the analysis is always the customer’s sales turnover, which should be calculated on the basis of listed or catalogued prices. After deducting customer-specific costs such as rebates, discounts, bonus agreements, and variable costs, it comes to contribution margin 1. This amount indicates the customer’s contribution towards covering the remaining fixed and distribution costs. Focusing only on the contribution margin 1 can lead to misperceptions if the customer has high customer-specific fixed and distribution costs. To cover this misjudgement and to obtain the value of contribution margin 2, the customer’s fixed costs must be subtracted from contribution margin 1. To determine contribution margin 3, the custom distribution costs must be deducted from contribution margin 2. When the

88

percentages of non-customized associated costs such as HR and R&D costs are subtracted, the right result for the customer emerges. In the further course of the thesis, the researcher refers to contribution margin 2.

The breakeven method is useful to identify the customer’s cost components that can be debited to the greatest extent to achieve the results. Customers with a high price level and a good contribution margin can prove to be unprofitable at the end of the year because they have an agreement for a high bonus that is paid at the end of each year. Furthermore, contribution accounting is a purely static process that does not allow the forecasting of the profitability of customers in future.

The results of the contribution margin analysis can also be shown by an ABC analysis.

Table: 8 80/20 ABC analysis contribution margin sample referring to Freter (2008)

Figure: 17 Diagram 80/20 ABC analysis contribution margin sample referring to Freter (2008)

Sequence Customer Average value per order Yearly orders Yearly Turnover Average gross margin in % Average gross margin in € % of the Yearly Turnover Cumalative % Category 1 Customer 1 € 100.00 300 € 30,000.00 20% € 6,000.00 39.4% 39.4% A 2 Customer 2 € 60.00 300 € 18,000.00 31% € 5,580.00 36.6% 76.0% A 3 Customer 3 € 5.00 1,000 € 5,000.00 23% € 1,150.00 7.5% 83.5% B 4 Customer 4 € 20.00 175 € 3,500.00 34% € 1,190.00 7.8% 91.3% B 5 Customer 5 € 30.00 50 € 1,500.00 27% € 405.00 2.7% 94.0% B 6 Customer 6 € 200.00 7 € 1,400.00 37% € 518.00 3.4% 97.4% B 7 Customer 7 € 70.00 4 € 280.00 34% € 95.20 0.6% 98.0% C 8 Customer 8 € 10.00 24 € 240.00 34% € 81.60 0.5% 98.5% C 9 Customer 9 € 50.00 10 € 500.00 25% € 125.00 0.8% 99.4% C 10 Customer 10 € 25.00 12 € 300.00 33% € 99.00 0.6% 100.0% C Total € 60,720.00 29.8% € 15,243.80 100.0%

89

In addition to the contribution margin analysis based on past data, a potential contribution margin analysis can also be carried out. This method takes into account the current contribution margins and the future potential for development. In this case, the method switches from a retrospective analysis model to a prospective model. This is very common for companies with contractual purchase obligations (Heinemann, 2008). This analysis takes into account the development of a customer during the course of the business relationship. At the beginning, the customer generates a low or even negative contribution margin, but becomes more and more profitable during the partnership. This method, including the future projected contribution margin, can also be used for new or potential customers. If no firm commitments or agreements have been made, such a factor must be considered. Otherwise, the business relationship could grow in a wrong and unplanned direction. There should be a comparison among customers to verify if similar characteristics have shown up in the past.

The results of the ABC analysis based on the contribution margin and contribution margin potential can then be interpreted in a manner similar to the results based on sales turnover. This method has most of the advantages and disadvantages of the ABC analytical methodology. In this method, profitability is considered, but not the size or value of the customer.

Regardless of the turnover or contribution margin, the greatest advantage of the ABC analysis is that it is easy to understand and apply (Cooper & Kaplan, 1991). Another major advantage is that this method is easy to use and simple to comprehend for everyone in the company (Keskin & Ozkan, 2013). Complex issues can be analysed at an acceptable cost with this method by limiting the ABC analysis to the essential factors. For the user or observer, a great deal of company-specific knowledge is not required to identify the main customers. This is because the results are represented clearly. This method is applicable not only to customer or sales data but also to other types of data and factors (Homburg & Wieseke, 2011).

However, Homburg and Wieseke (2011) and Freter (2008) pointed out the disadvantages of this method. First of all, it is a rough segmentation method. If an SME works with a lot of customers, the ABC analysis can generate very large segments. Evaluation with only a single factor is also a great disadvantage because other factors that are important to evaluate the probability and value are not considered. If the company segments the customer by the contribution margin percentage, customers with the highest per cent rate have a low turnover

90

in many cases because customers with a higher turnover drive a hard bargain and get better (lower) prices. Lower purchasing price for the customer leads to lower turnover and contribution margin.

The three different segments are clear but no useful strategy can be deduced regarding the customer. This is because each segment is appropriate for their different needs and behaviours.

Both kinds of ABC analysis are simple and commonly used across the SME sector. However, in the last few years, ‘several methods have been developed to perform multi-criteria ABC analysis that can be quite easily implemented today’ (Ravinder & Misra, 2014, p. 257).