Sales data in S&OP
Your supply chain processes can be too supply focused. To provide the Availability of products and services needed by customers and consumers requires a knowledge of markets and sales.
Sales and Operations Planning (S&OP) is the tactical planning process that brings together the Sales and Operations views on the future of markets and supplies. The Supply Markets Plan was discussed in the previous blogpost (the Capacity Plan is for a future post). This blogpost discusses the Demand Plan as a critical input to S&OP.
The need for S&OP has become more important in recent years due to the increase in Stock Keeping Units (SKUs) that address the assumed needs of ever smaller market segments. This has led to lumpier demand for items considered to be more ‘fashionable’, combined with higher levels of ‘forecast error’ in sales forecasts.
Demand Challenge
The influences noted in the previous paragraph has meant that Demand Latency is becoming more visible; that is, the time from when an item is sold to a customer until the order for replacement items is delivered. This is a new play on the P:D ratio. D (demand time) is the time customers wait between ordering a product and receiving it and P (procurement and production throughput time) is the time taken to obtain resources, then produce and deliver the product.
Actions identified to reduce the P:D ratio (and now Demand Latency) were:
- Improve forecast accuracy – this is difficult in a time of heightened sales variability, so improve the quality of market knowledge
- Add safety stock and/or capacity buffers along supply chains. Difficult to achieve outside of your business. Inventory likely to have been removed to improve asset utilisation
- Standardise the product range through the use of common parts
- Simplify the product range through reduction of SKUs has difficult internal politics to overcome
- Reduce the P time – focus on lead times through supply chains, production throughput times and supplier contract negotiations
This list generally stopped at the first point – to improve forecast accuracy. Better still, the wish to have no forecast, but an instant translation of demand to supply. The elimination of forecasts was a part of Efficient Consumer Response (ECR), which commenced in the early 1990s.
The objective was to link retailers with manufacturers and utilise current Point of Sales (POS) data. The business initiatives considered necessary for the successful implementation of ECR included:
- electronic data interchange (EDI),
- continuous replenishment program (CRP),
- computer assisted ordering (CAO),
- flow through distribution (cross-docking),
- activity-based costing (ABC) and
- retail category management (RCM)
While computer technologies may change, the practices required some thirty years later are similar. To reduce the P:D ratio is a generally accepted approach; however, the practice of design, development and implementation is proving to be more difficult.
Demand Plan inputs
A Demand Plan should provide the best estimate of market demand, sales income and gross profitability for the products on offer. This is provided through a Forecast; an estimate of demand covering a future period, for a product group or larger segment i.e. a ‘product family’ in S&OP. This can be provided because the different attributes of individual product line items are not considered. A Forecast should always be based on the probability of an optimistic outcome and of a pessimistic outcome – never one number. This enables Supply to interpret the criticality of requirements for materials and components. The sales forecast is developed from historical records, Demand Sensing and Demand Shaping:
Demand Sensing: An automated process to quickly sense changes in buying trends for consumer product and sales channels; helping to reduce the P:D ratio or Demand Latency. The ultimate implementation is to analyse a range of external data, including: point of sale (POS) machines; card/mobile phone sensors; unstructured statements posted on social media; web site ratings and reviews of products and services; warranty and product returns via eCommerce and physical sales outlets and weather forecasts. For inventory management, the data can be input to a geographic application, enabling demand to be anticipated by region and therefore more applicable inventory to be held.
Demand Sensing has a new urgency due to the current pandemic, which has affected sales of products around the world. Current sales are certainly not a reflection of past sales patterns, which has been the basis of past sales forecasts.
For example, in Australia the early days of the pandemic saw panic buying by consumers (and businesses) of ‘essentials’. Later, with directives to ‘work at home’, there was increased buying of exercise equipment, jigsaw puzzles, laptop computers, computer monitors and coffee machines. Being at home meant more cooking – sales increased for flour, spices, mushrooms and tomatoes, with buying in larger size packages.
With no overseas holidays allowed and interstate travel restricted. has this caused the increased spending on sofas/settees and outdoor furniture? And what is the reason for a decrease in sales of skincare products and men’s deodorant?
The situation for many businesses is that the past is not an indicator of the future. Will increased/decreased demand pattern for products continue after restrictions on movement are removed – past order and sales data will not provide the answer.
Demand Shaping: Design programs to increase customer and consumer demand for products. These include: new product releases, upgrades to current products, product promotions, price reductions, commercial buyer (or trade) incentives and sales force incentives. The challenge is that uncoordinated implementation (that is, not through the S&OP process) can increase uncertainty through the supply chains.
Demand Shifting is a practice in sales that moves the recorded sales and or delivery of products from one period to another. It includes practices such as: the: ‘end of month (and quarter) rush’ to get finished products out of factories to meet production targets; shipment of orders this month that should be delivered the following month and ‘stuffing’ the sales channel with additional product sold on delayed payment terms. Demand Sifting distorts demand signals and increases costs in supply chains (especially air and express freight).
An effective S&OP process that feeds the Distribution & Operations Execution process is but one step in making your supply chains a critical part of the organisation. Another is to consider how your suppliers can better synchronise, with minimal delay, your organisation’s improved sales and operations plans.