CoreProcess

Can you answer the following questions about your business, and be confident you can make major decisions on a regular basis on the strength of the answers?

• How profitable is each of our products, sold to each customer, in each location, in each delivery, or at least in each period?
• Which of our promotions really generates incremental profit, when lowered prices and increased supply chain costs are accurately allocated?
• Where are the easy opportunities to reduce distribution cost in our supply chain and what is the real scale of those opportunities?
• How should we construct and enforce supply chain trading terms to ensure we give the best terms to those customers which are contributing most to our true profitability?
• What will be the impact of fuel price increases on my cost-to-serve, by route?

Cost-to-serve is key to understanding "true profit".

Cost-to-serve analysis is based on the notion of going beyond gross margin measures of profitability, to measuring true profit. True profit is your gross margin, less the direct costs associated with sales. This key measure of profitability ensures that the attributable costs of fulfilling sales are taken into account. Pivotal to the concept of measuring true profit is the ability to identify and allocate costs by activity, by SKU. This is what cost-to-serve analysis provides.

Most supply chain cost analysis makes gross assumptions about the relative cost allocation of a particular acitivity. For example, storage in the warehouse and pick costs may vary between SKUs. Most analysis fails to differentiate between product variants (for example, vanilla yoghurt versus lychee yoghurt) even though order sizes, and therefore supply chain costs, may vary widely.

In using the typical 'average cost-per-case' approaches to supply chain cost allocation, the very differences which affect a product's true profit can be masked. High handling-cost, low cash-margin products are often subsidised by fast-moving, higher-margin products and high-cost customers are subsidised by low-cost customers.

Figure 1 shows the results of cost-to-serve analysis of all 238 products in a real supermarket chain’s Laundry category. The analysis includes costs from the retailer’s receiving dock through to the customer’s trolley. Each bar represents one SKU. For each measure, the products are ranked by diminishing cash profit (gross margin). 

In this real-world example, on a cash profit measure, all products are profitable. Cost-to-serve analysis, however, exposes the fact that direct costs, in absolute currency terms, vary widely. When these direct costs are netted off the cash profit contribution, the true profit contribution follows a significantly different pattern. A number of products which are solid performers on the cash profit measure lag significantly on the true profit measure. Only rigorous ongoing cost-to-serve analysis can maintain visibility of true profit: and it is true profit which goes to the bottom line.

Why undertake cost-to-serve analysis?

Cost-to-serve analysis can serve many purposes within a business. Whether tackling a specific issue (such as understanding and quantifying the true cost of transport at the customer level) or providing the necessary information to establish a menu-pricing regime (which matches price to service at the SKU level across the whole business) it is essential to be clear on why cost to serve analysis is being undertaken. The nature, complexity and timeframe of the analysis will be significantly affected by the answer.

• For Manufacturers, understanding the cost to serve each customer delivery point is central to developing a “going-in” position for price negotiation.
• Being able to use that understanding in negotiations will be critical to achieving a profitable outcome.
  A clearly defined customer engagement strategy will provide the framework for your organisation to plan.

For retailers, continuing visibility of cost-to-serve from receiving dock to shelf is the minimum capability required to be able to optimise shelf-space profitability. Again, gross margin measures such as are available from shelf-space planning tools fail to make visible the extent to which supply chain cost differentials between SKUs can undermine shelf performance.

In the hands of buyers, true profit visibility can lead to behaviour that drives end-to-end efficiency by recognising that it is net margin, not gross margin, which makes the retailer profitable. Applied end-to-end, the true profit measure provides a robust KPI of financial performance for collaborative engagement between suppliers and their customers. Even applied within the customer's supply chain, it represents good news for suppliers. It allows the cost-saving contributions of individual suppliers to be attributed to their products’ profitability

To be an effective management tool, cost-to-serve analysis must be undertaken on an “every period” basis, so that all executives can be presented with a true picture of the way in which product and customer profitability is being eroded by direct costs.

For a full expose on Cost-to-Serve, read “Using Cost to Serve to Enable Effective Customer Engagement”, downloadable from the Publications page.

What is cost-to-serve analysis and how does it work?

Let’s start with what cost-to-serve analysis is not. Cost to Serve is not just another name for activity-based costing (ABC). The ABC approach is unable to deal with the inherent day-to-day variations in the way costs fall to individual SKUs moving through the supply chain. This approach produces average values which may mask actual cost variations.  ABC is based on assumptions and proportions, while cost-to-serve analysis is based on rules which imitate reality on a transaction-by-transaction basis.

Cost-to-serve is a financial analysis method which equitably and accurately accumulates costs incurred in supplying goods or services. It is often used to gain a deep understanding of the cost of distributing goods from factory to customer delivery point.

To illustrate the difference in the two approaches, take the picking function within a finished goods distribution centre. In ABC, values for the proportion of case vs layer vs pallet-pick will be established for each SKU and/or each customer and these will be applied to deduce an average cost per case for picking. Well-constructed cost-to-serve analysis, on the other hand, will analyse the factors which determine whether a product is case, layer or pallet picked for each line item handled in the period and will apply the appropriate cost of picking to that line item.

To be effective, cost-to-serve analysis must simulate the distribution network, to allow the reconstruction of costs, line item by line item, activity by activity. This is where CoreProcess PIM excels. PIM is a simulation model, processing each transaction through a path in a model which matches the actual network. As a result, each transaction processed through PIM attracts the appropriate costs incurred by the actual transaction, not an averaged estimate of the costs incurred.

If ABC analysis has been undertaken to establish the cost of an activity, that cost can be an input to cost-to-serve analysis. Cost-to-serve is about the aggregration of activity costs along the supply chain at the individual transactional level. It is important to maintain the focus of cost-to-serve analysis on achieving usable, quality information with manageable effort, not on “boiling the ocean” to achieve perfect answers.

More often than not, projects which focus on perfection in the numbers fail, because the time taken to get the answers renders the answers irrelevant to addressing the issue which gave rise to the analysis. In cost-to-serve analysis, any estimate of an activity cost is an acceptable starting point. Where activities show up as worthy of more scrutiny on a first pass model, further analysis can always be applied to achieve a better estimate.  Similarly, not every activity needs to be modelled in an initial model build.

A typical scenario for cost-to-serve analysis is shown in figure 2. It is possible to have multiple entities at each layer of the diagram.

To be useful as an ongoing management tool, cost-to-serve analysis should be undertaken at the “line item within a delivery” level. Any aggregration above this level, at the calculation stage, will typically produce cross-subsidy of costs between SKUs (figure 3).

Undertaken at this level of detail, cost-to-serve analysis produces a very large amount of detailed cost information, which can then be rolled up in many different ways, to answer the questions posed at the beginning of this section. It is true that businessed rarely need to regularly use information about the cost to serve a given customer location with a given SKU in a given delivery. It is also true that, without this level of detail, it will not be possible to obtain answers to the more likely “big picture” questions about customer and SKU profitability.

The broad overall flow of cost-to-serve analysis is shown in figure 4.

CoreProcess PIM implements the cost-to-serve approach in a robust, maintainable, user-friendly solution, designed to provide an accurate picture of the true cost to serve your customers: every period, on demand.