An out of stock situation means too little supply, too much demand, or both. While it may have been the result of poor planning, out of stock situations often arise from unforeseen events or new variables coming into play. For manufacturers, it becomes a question of how quickly they can respond by weighing tradeoffs to make decisions while mitigating out of stock situations in the future.


SITUATION: A publicly traded consumer beverages company produces ~50 SKUs for a particular geography across 7 bottling lines. Weekly S&OP meetings determine day to day production schedules for the next 2 weeks. Historical out of stock and their exact deficits are recorded in a spreadsheet, while any immediate situations are discussed in the weekly meeting.

CHALLENGE: Demand forecasts may be off, causing more inventory to be drawn than anticipated. Production may be limited by production line capacity, meaning certain SKUs need to be sacrificed for other SKUs. These decisions are often made by experienced personnel leaning on their intuition to make ad hoc judgement calls. It’s unclear if these decisions are best based on quantitative data.

SOLUTION: All variables needed to automatically generate and update a production schedule are modeled out, including SKUs, raw materials, production lines, warehouse space, cleaning rules, and operating times. As demand forecast and inventory figures are inputted and updated, production schedules will adjust accordingly in real-time. Different scenarios can be compared and evaluated based on quantitative impact across key business metrics.