Sales and Operations Planning for Cash Forecasting

Sales and Operations Planning (S&OP) is a very well known practice in the physical supply chain. There are many reasons why I believe it could become an excellent paradigm to improve cash forecasting in the financial supply chain. The assumption I make is that treasurers would be in a better position if they could incorporate in their forecasting exercise any of the factors that affect and modify corporate cash flows. For instance, wouldn’t it be valuable to project the impact on corporate cash of a marketing campaign while it dynamically changes and evolves under the expert hands of marketing pros and board member decisions?
Another example might refer to a situation where limited resources (e.g., machines; workforce; materials) do not allow to fulfill all customer orders. Which orders should be left behind? Is there a way to measure the impact on of these delays on corporate cash flows and provide the treasurer with a projected scenario that allows to take decisions to produce the least negative impact on corporate cash?

At budget level (i.e., running scenarios annually or every six months) this is possible and in many cases already happens. What if this analysis and simulations could be run on a real-time basis with live data? Well, this is what right now is possible in the physical supply chain with S&OP. Why wouldn’t that be possible also in the financial supply chain for cash forecasting?

Definition of S&OP (i.e., the physical supply chain)

Let’s take a step back and understand what sales and operations planning is. S&OP is an iterative business management process that determines the optimum level of manufacturing output. In most cases it is run monthly, but under the current stressed market conditions it’s not rare to see weekly iterations of the process.
S&OP begins with the recognition that different parts of an organization have different goals in a company. For example, production's desire for limited variety, stable designs, and long lead times is naturally at odds with marketing's desire for endless variety, extreme design flexibility, and the ability to make last-minute orders. Of course, both departments can never accomplish all of these objectives at the same time. In the absence of a solid planning system, each unit typically looks out for its own interests.
In a highly competitive world many executives see the need to improve coordination between functions. Better coordination between the sales and operations (i.e., production; procurement; logistics) departments can make the difference.  At the strategic level, S&OP begins by forcing executives to answer some tough questions such as  which segments to serve; What service levels to commit to; How to prioritize customers in case of supply shortfalls. Once those decisions are made, the top management team decides how demand should be balanced with supply, based on profitability objectives, channel requirements and the overall business strategy. A possible objective could be to serve only profitable customers, or at least serve them better.

Typical components of the process are the definition of a consensus based demand plan, a supply plan (constrained based) and agreeing on exactly how to meet demand and supply.
A typical S&OP process is structured in steps[1]:

• Collect data from sales and marketing through collaborative forms.
• Use statistical analysis and/or management input to build a multi-period forecast plan.
• Compare the multi-period output of the statistically generated forecast to the collective sales forecast and key channel partner forecasts to analyze and understand exceptions.
• Develop plans and analyze lift for demand shaping, including promotion planning, price management, contract compliance, and the timing of new product introductions.
• Analyze the best alternative for the business based on profitability, revenue, customer service, and targeted inventory levels.
• Conduct a what-if analysis by supply to determine tradeoffs on the measurements and identify demand-shaping opportunities.
• Review scenario alternatives and gain consensus on the operating plan.
• Communicate the constrained plan to the operational teams for execution.

S&OP software solutions

That the above described process flow is not mere academic fantasy is confirmed by the number of S&OP software solutions available in the market today (e.g., Oracle-Demantra; Logility-Voyager; JDA; IBS). These suites of applications automate the execution of the process along three major areas:

Collaboration- The various parties (e.g., production; logistics; sales; marketing; controlling; procurement) engaged in the S&OP supply chain planning process work together to produce a final output that will drive the execution of the corporate supply chain operations. S&OP platforms allow interaction, exchange of data, and information to produce the final output.

Integration- Each party works on a system to perform daily duties. The applications used in these systems are not necessarily the same. For instance, sales will work with IT applications quite different from those of procurement. On a regular basis the parties meet in the S&OP platform to generate the operations planning schedule. The data exchanged are extracted from the “daily” systems (e.g., ERP; sales system; production schedule) and shared across the platform to produce a single view of the flows of data on which the work begins to generate the final planning result.

Optimization- There are inevitably opposing objectives and different agendas between the participating parties. While logistics will want to schedule deliveries according to customer orders at the risk of shipping partially loaded trucks, procurement and controllers will prefer to have full loaded trucks to benefit from economies of scale spreading the cost of transportation over the units shipped. The S&OP algorithms will factor in all these contrasting instances to generate a suggested production plan that can be further elaborated through what-if simulations until a final agreement is reached.
The optimization process goes even further allowing to simulate the projected capacity profiles of the critical resources (e.g., machines; materials; workforce). Immediately it becomes possible to anticipate future critical points and take immediate action (e.g., pile up stock to anticipate peaks of demand; inform suppliers of critical future demand; plan for overtime;  plan to outsource part f the production schedule). The system also enables to decide to postpone some deliveries if the situation cannot be resolved within predefined parameters of convenience. For instance, it might be less profitable to spend resources to ensure an on-time delivery of an order vs. allowing the order to be delayed. Depending on the service level established for that client the company might decide it is worth to focus the limited resources on more critical and profitable clients. The system takes into account these parameters suggesting the optimal balanced sales and operations plan.

What this means to cash forecasting (i.e., the financial supply chain)

Typically cash forecasts are based on input data from the accounting system (i.e., payables, receivables, and inventory). Some foreseen cash inflows/ outflows are also factored in, usually via manual input. The examples of the S&OP practice demonstrate that the technology is already available and tested, enabling parties to collaborate, integrate data, and optimize the final output in an automated way. This opens the likelihood of interesting (and technically feasible) scenarios in the financial supply chain:

• The treasurer automatically uploads in the cash forecast system the sales, purchasing, marketing, and production plans from the corporate ERP. No order has been issued, so no payables, receivables, or inventory data are available yet. A normal cash forecasting system would not consider this data. An S&OP-like cash forecasting system, instead, would factor in and elaborate predictions of how these plans affect cash inflows (e.g., sales and marketing) and outflows (e.g., purchases and production).
• A treasurer can anticipate liquidity requirements for a marketing campaign that launches a product line in a foreign country to open up new market channels. There are no orders yet in the accounting system. There are more products in the pipeline, each one with its original price and promotional discount based on customer segment and geography. The S&OP-like cash forecasting system can capture this data from the ERP system, where it’s usually resident, and project cash outflows in foreign currency with associated planned requirements for FX hedging.
• Sales volumes are growing and production will not be able to deliver all orders on time. Customers are all important and strategic so none has to be left behind. Decision to outsource production to offset resource constraints is unfeasible because unprofitable. The only decision for the company is to pile up stock and keep it for a long time until the sales orders are due. The S&OP-like cash forecasting system can support the treasurer in multiple ways:
  • Suggest inventory finance options offered by banks participating in the platform.
  • Trigger the banks to take action and propose pre-shipment financing options to the company.
  • Prioritize the orders to be delivered not in terms of customer service/ satisfaction, but rather in terms of cash profitability. That is, propose the least negative cash flow projection and suggest what orders to leave behind.

The described scenarios might appear science fiction and nice-to-haves. This is not the case. They already operate in the physical supply chain. Why shouldn’t they work in the financial chain as well?

[1] Source: AMR