In traditional manufacturing models, there needed to be more connection between the ability to meet customer demand and manufacturing execution. Subjective data-gathering on demand coupled with manual processes and manual data collection in manufacturing obscured the real demand picture.There was also a significant lag between when demand data was collected or available and when manufacturing had to begin producing to meet forecasted production goals. The time lag and flawed data quality often combined to create over or under-production of needed finished goods and an inability to gauge the importance of meeting customer demand.A tighter link between the two has long been needed because demand drives execution and impacts almost every facet of an operation. The answer has proven to be a two-step digital solution requiring advanced software and data analytics that utilize real-time data.You Can’t Execute What You Can’t ForecastThe days of manual surveys, interviews, and gut feeling to predict demand accurately are gone. And in their traditional form, they were never going to close the data gap in time for accurate and agile execution.Today, manufacturers must forecast accurately. That means using advanced demand and supply planning software and demand-driven execution. Leveraging real-time data across the enterprise means demand planning can draw on cross-functional inputs to manage inventory, supplier performance, and logistics without guessing.Human analysis can’t manage large data sets deeply enough in planning. But a cloud-based system using advanced analytical insights can. This system uses external data that indicates demand signals and makes it immediately available to supply planners and schedulers. The result is a real-time, data-driven picture of demand so that forecasts and production schedules can be executed confidently. That execution is also rendered dynamic as the system will detect and identify both supply chain issues as they arise and production bottlenecks that occur unexpectedly in time to make adjustments and stay on plan.You Can’t Execute What You Can’t ControlThe second step in this digital solution is control over manufacturing processes. A smart manufacturing platform combined with powerful MES software makes production processes visible. Real-time analytical insights allow decision-makers and managers to change and optimize processes to increase OEE and reduce planned and unexpected downtime.A smart manufacturing platform like Plex also creates a closed-loop system where machine and operator performance generates real-time KPIs and user alerts that allow action as or even before the problem becomes critical.These capabilities empower companies to digitally track vital inbound parts and materials with insights generated from the accurate forecast and supply plan. Managers know when they will arrive, where their orders are regarding WIP, and which ones are complete and outbound so they can meet specific customer demands.Because data quality is exceptionally high in a smart manufacturing system using cloud-based demand and supply planning software, managers and teams can leverage analytical insights for metrics like cycle time, downtime, quality, machine availability, and more to identify and implement process improvement. As execution becomes more agile and precise, improvements create a feedback loop that allows the demand and supply software to adjust and sharpen forecasts even more.Take Control and Forecast AccuratelyThe ability to meet changing customer demand will either drive execution inaccurately (causing missed opportunities and waste) or accurately by using real-time data and analytical insights. By combining the power of demand and supply planning software with a cloud-based Manufacturing Execution System (MES) like that from Plex, a company can leverage its data to provide agile and flexible production execution that can turn on a dime as forecasts adjust to real-time market conditions and inputs.To learn more about what demand-driven planning based on real-time insights can do for your manufacturing operation, read this knowledge article.
