Sales and Operations Planning (S&OP) is a process that has been deployed primarily to align different functions around the best plan they could identify, working together as collaboratively as possible. Many standard and emerging analytic techniques can be employed to supercharge performance and optimize S&OP decision making.
S&OP is not a new process and has been used widely across industries for many decades. Most practitioners would probably accept the following definition of S&OP:
“A process focused on ensuring a continuous alignment between demand, inventory, supply and manufacturing plans on the one hand, and between these tactical plans and the business plan on the other hand, in order to maximize operational performance”
Unfortunately, the goal of continuous alignment is more of an aspiration than a realizable objective for most organizations. There can be many reasons for a lack of alignment, and these reasons fall into a number of categories related to data, IT, business process, and organizational challenges. Some companies truly embrace S&OP at a deep level, fully enable the process analytically and provide practitioners with all necessary data sources. These advanced capabilities, considered as a whole, are sometimes referred to as Integrated Business Planning (IBP).
One significant challenge that has remained extremely difficult to overcome has been accurate forecasting; it is the most significant driver of supply chain costs, complexity and performance issues. Analytics can help companies significantly improve their understanding and use of demand data to guide S&OP decision making and performance.
There are different analytic techniques that can significantly improve S&OP capabilities and help optimize enterprise performance; they are, as follows:
Supply Chain Planning: optimizes revenue or profits by balancing demand and supply within current constraints and capacities
Network Optimization: optimizes revenue or profit by determining network flow and sometimes positioning of facilities thus reducing cost-to-serve
Multi-echelon Inventory Optimization (MEIO): reduces working capital by taking and end-to-end view of inventory requirements, thus positioning inventory in the most efficient way in the supply chain, while balancing service levels and cost
Advanced Demand Forecasting: improves forecast accuracy taking into account exceptional conditions
Demand Shaping: leverages pricing to shape demand to optimize revenue and profits
It is not surprising that Sales and Operations Planning (S&OP) is experiencing a renewed interest within many companies. The incorporation of more analytic techniques into the process provides a true renaissance for S&OP. The companies who move quickly to deploy these new techniques can achieve a significant competitive advantage.
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