As we Know Supply Chains are showing extreme volatility and stress during the current times. The leaders are questioning the usefulness of traditional methods of planning and execution and are looking for better processes and tools to stay in control. A careful investigation of their situation reveals the following needs:
Supply Chain organizations must connect and align their business processes and information systems. Implementing an EPM-powered Sales and Operations Planning process can give them a big advantage.
As part of this live webinar, we will address common questions raised in an S&OP meeting:
Forecasting is a technique of predicting the future based on historical data results. It involves a thorough analysis of past data to predict future outcomes. Forecasting uses Statistical methods, Machine Learning models, and human decision methods and is an ever-relevant and dynamic field of knowledge.
In the supply chain context, especially for Demand Planning, an accurate and reliable forecast is very important, because it helps organizations align resources more effectively to fulfill customer and internal KPIs. However, from our experience, we have seen companies struggling to generate meaningful and usable forecasts despite their investments in enabling the process using a plethora of systems and tools.
Being all things to all people isn’t always the best business strategy. Sometimes, channelling slight variations of different products and services to different groups of your customer base helps to increase market share, improve revenues, and reduce costs. This differentiation process is called “Segmentation,” and when applied to products it is known as ‘Product Segmentation’. In the context to supply chain planning, an increasing challenge is to manage many items with unreliable demand forecasts. While improving demand forecast accuracy in general leads to a more efficient supply response, the business value of accurate forecasting is not uniform for all items that a company carries. Therefore, an obsessive focus on forecast accuracy alone sometimes leads to diminishing returns. The product segmentation principle leads us to NOT treat all products as equally important and apply different operational strategies for a different group of products. In this brief video, Sarbajit discusses practical pitfalls, methods, and results of applying product segmentation that we have seen from past experiences. Tune into this short session for more.
Despite all attempts to protect Supply Plans from nervous shocks, priority changes from Sales. In an increasingly unpredictable supply chain, change of priorities because of “urgent customer demands” is a reality that S&OP needs to address. Often when such urgent changes in priorities are discussed in an S&OP meeting, convenience wins over rationale. Worse, these conversations are repeated cycle after cycle sapping out useful energy. Frequent conversations do not necessarily imply better decisions. From our experience, what helps organizations greatly, are scenario-based decision tools, that help compose alternative supply plans based on changing priorities. Using scenario planning, supply planners can inform Sales about the options available to them. With visual tools clearly comparing plans on service levels and resource utilization metrics, a win-win response can emerge.
Dynamic slotting helps planners to maintain profitability by limiting of the set of time slots offered to individual customers. Customer choice means that tailoring offers to customers to entice them to select less popular time slots can create a more even distribution of deliveries. Dynamic slotting decisions depend on the current request, the already accepted orders, and orders still expected to arrive in the remainder of the order horizon. They entail solving three connected subproblems: Determining the feasibility of delivering the current requested order per time slot, determining the opportunity cost of promising the delivery and thereby potentially limiting the resources for accepting future expected orders, and determining the optimal assortment of offered time slots to maximize revenue given stochastic customer choice.