S&OP is fundamentally about process: an organized set of steps required for education, implementation and sustainable practice. These encompass organizational alignment, data gathering, analysis, consensus, implementation and so on. This is not the place to debate the right number of steps or methodology. Rather, sooner or later all S&OP processes must confront the fundamental reason why they exist in the first place: the synchronization of supply and demand, i.e, aligning available resources (myopically often limited to manufacturing capacity) with forecasted demand.
The next time you hear about S&OP, pay particular attention to the synchronization step. You will probably find only vague references to unspecified “analytics”. If you drill down, you will likely discover nothing more than what one company calls “warring spreadsheets”. Sales and marketing come equipped with spreadsheets containing the latest forecast. Wrong. The forecast should be a cross-functional effort. Manufacturing puts in an appearance, armed with spreadsheets containing the latest capacity numbers. Then the fun begins. Manufacturing professes to be appalled by the implications of the forecast: not enough capacity, excessive line changeovers, etc. Marketing takes the side of the angels: customer satisfaction. They argue, eventually compromise, and obtain senior management approval. Frustration abounds. The process eventually dies.
The most disappointing aspect of the above is the simplistic technology used to achieve synchronization. This complex problem has been well understood by advanced analytics experts for decades. It demands the application of mathematical optimization for two reasons: (1) the necessity to allocate limited raw material, manufacturing, and storage resources (capacity limits), and (2) open/close decisions by production line and shift. It cannot be properly addressed by heuristics, expert systems, simulation or, worst of all, warring spreadsheets.
So…what to do? A straightforward solution, one increasingly recommended by experts, is the venerable supply chain design model. Such tools have traditionally focused on strategic questions: number, location and sizing of facilities, outsourcing, customer service levels, and so on. But a little appreciated capability of a network model is to use it in tactical mode. For example:
• Build a comprehensive model of the supply chain, from raw material acquisition to final customer demand
• Build a multi-period model, typically at a monthly level of demand and supply
• Freeze all customer assignments
• Use forecasted demands
What do you get for your trouble? Among other things, raw material requirements by supplier/raw material, production volumes by location and line, storage requirements and inventory by location, and detailed transportation flows, all by time period going forward and determined by the costs and capacities of the entire supply chain, not just manufacturing. Critical: inventory pre-builds are automatically addressed. Supply-demand synchronization is directly solved by the only analytic tool with the power to handle resource constraints: mathematical optimization.
The promise of SCM can be realized and a powerful enabling tool can be S&OP. But five decades of SCM evolution tell us that there are no guarantees. Success demands that organizations bash silos and replace them with genuine cross-functional processes. In addition, management must recognize that supply-demand synchronization, the heart of S&OP, necessarily crosses all functional silos and is a challenging problem that must be addressed with suitable optimization - based on advanced analytics, not simplistic spreadsheets.
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