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Modern manufacturing is a complex endeavor for any company. Equipment capability, labor and productivity must be balanced against demand, sales forecasts, supply chain issues and many other factors to produce the right volume at the right time. Too much and the inventory excess will impact cash flow. Too little and customers will seek products elsewhere as production stalls.
To keep manufacturing balanced between all these inputs, companies use capacity planning to keep production optimized. Simply put, with capacity planning, a company gauges production capacity in terms of equipment, staff and maintenance that is required to meet demand. This allows them to make critical decisions that impact the profitability of the company over time and decisions that can reduce costs and improve competitiveness.
Depending on the products manufactured, companies have a variety of strategies available to them for capacity planning. For companies with heavy seasonal demand, capacity planning may utilize a Lead Strategy. Here, capacity is added prior to demand to keep them ahead of the demand curve.
If a manufacturing company has an agile production system, say one with few process steps or rapid completion of units, then they may seek to use Lag Strategy. In Lag Strategy, capacity is only planned after demand has occurred. This reserves finances until they are needed and depends on the ability to add capacity quickly.
Many small and medium sized companies (SMBs) use Match Strategy for capacity planning. In a Match Strategy, capacity is added incrementally, increasing proportionally as demand increases. This “pay as you go” strategy is useful in balancing the cost of capacity increases.
Regardless of the strategy used, there are five production capacity planning challenges to be aware of that can impact production no matter the scale and complexity of the organization.
Planning software mitigates and eliminates the challenges to production capacity planning. Because collected data is unsiloed and kept in a unified system, it is standardized and available for all, delivering a single version of truth for the enterprise.
Data quality is also improved with software. It eliminates the need for manual aggregation and reconciliation of different data types. This reduces error and frees up time and resources needed to understand the results and make decisions based on real-time information. Because all functional areas are linked through automation, changes in data in one location is advanced throughout the entire platform and changed dynamically.
Today’s software comes with advanced analytics, machine learning, and a wide range of analytical tools that can plan capacity to the unit, cost, margin or revenue. Because dynamic real-time calculations can be performed by the system, it eliminates the need for multiple spreadsheets and manual data inputs. The accuracy of the formulas and calculations saves time and reduces errors.
Planning software also allows for multiple views and iterations at different levels. From advanced analytics and machine learning algorithms to multi echelon “what-if” scenarios that help identify capacity constraints, plans can be produced for short-term operational needs as well as medium and long-term strategic planning.
Finally, capacity planning software improves communication and collaboration. With intuitive dashboards, alerts and other tools, data from the ERP system can be leveraged to optimize plans based on current material and capacity constraints. The system can be integrated with ERP and MRP systems to provide BOM-level finished goods forecasts at the component level. These functions can trigger alerts, schedule replenishments, identify constraints and drive cross-functional collaboration in real-time.
While capacity planning is complex, today’s cloud-based software from DemandCaster can deliver solutions to overcome the challenges inherent in the old version of the process. By deploying this software, the system can deliver value in the form of reduced errors, lower costs and greater precision to better meet service levels and to drive process improvements.