One of the most common issues executives raise is the inability to secure reliable delivery dates upfront when communicating with customers and taking orders. Clearly, this bottleneck results in frustration and the potential for lost orders as customers demand reliable delivery dates, stable lead times, and expedited performance. It also creates concern for executives as they want to know what volume of orders they can take before bumping up against capacity barriers so that they can proactively address to meet their goals. The solution lies in developing a capacity planning and labor scheduling process that will provide reliable, timely information.

Case Study: Industrial Power Equipment Manufacturer

An industrial power equipment manufacturer supplied several markets including data centers. With the surge of interest in AI, data centers have been exploding. Thus, business was booming but limited by capacity (facilities, machines, workforce/ labor, skilled resources, Engineering, etc.). Executives wanted to know how many orders they could take upfront to fill each week, month, and quarter fully as they had customers anxiously awaiting dates and several new opportunities for growth. They did not want to commit to an order with a key customer and fail to deliver on-time. Thus, they needed a quick solution to fill the capacity planning gap.

Of course, it is never simple or straight-forward. They recently went live on a new ERP system, and their order stages and statuses were unclear, their data integrity was suspect, their capacity planning functionality was not understood, and even though they had a daily huddle meeting with a review of a Heijunka board, they were chasing orders around the factory. In essence, they had a capacity planning spreadsheet from their legacy system that the planner keyed orders into, massaged information for what she knew to be true (that was not reflected anywhere in the ERP system), and she did her best to track progress and capture capacity. But, it was not nearly fast enough or reliable at scale. Customers were clamoring for reliable information. Executives wanted to know where to invest and how to deploy resources. Thus, everyone crowded around the planner’s desk.

Not surprisingly, the situation was complex as otherwise they wouldn’t need consulting experts to develop capacity planning processes and models. Although there was some level of repeatable business that could be planned upfront, knowing if the item was standard (and repeatable) or custom was not flagged in the ERP system (SAP Business One), or in MRP (material requirements planning) or CRP (capacity requirements planning). Thus, all orders had to wait in line for the expert planner to be available to review. However, even if the type of item could be flagged, the planner waited for Engineering to finalize the item so that she could plan capacity and add it into the production schedule. The Engineering lead time was far longer than the manufacturing lead time, and so everyone had to wait until the bill of material (BOM) and routing was finalized. Even if this information was available, the run times associated with the key steps of the process (those that were planned) were not clear. The planner relied on her expertise to pick the appropriate pieces of information from the routing and used ballpark information from the prior ERP system in the interim (although there was not a cross-reference to gain insight into these rules of thumb nor access to the prior system). And, if that wasn’t bad enough, the capacity availability, number of people required to run certain items, and the complexity associated with certain product groupings was only available in her head.

Thus, a deep dive was required. Of course, the path forward had to achieve progress in setting delivery dates while creating a capacity planning process for the long-term. We had to run several parallel paths simultaneously:

• Order backlog: Get our hands around the order backlog. Understanding the orders, availability of BOMs, visibility to Planning, sequencing of orders (identifying parent-child relationship), order status visibility, assignment to cells and/or facilities, etc. This also involved a deep dive with Customer Service, customer requirements, and constant interaction with the Sales team.
• Capacity product groupings: It was important to identify and create product groupings that have similarities in run rate, engineering layers, operational capabilities, etc.
• Connecting orders to capacity groupings: It isn’t enough to simply identify product groupings, you have to design a way to assign these grouping upfront.
• Making sense of dollars to units for revenue predictability: This sounds reasonably easy yet was one of the most challenging tasks as the level of complexity of the orders was unknown until fully engineered. In addition, knowing which items to include in the revenue forecast and which to exclude created a complex puzzle.
• Capacity resources / availability: Different items required different predecessors (children), operational steps, different types of skilled resources, and different configurations / subsystems. Defining capacity resources and availability across the facilities was key.
• Use of ERP & related systems: Calculating these values manually was a recipe for disaster. Thus, we had to determine how to best utilize SAP Business One, the quoting and configuration system and related reporting/ information to gain insights into capacity.
• Develop an automated capacity model with key user input: In order to fully leverage the ERP system to plan capacity, several additional areas of functionality had to be rolled out (unscrambling the routing files with a focus on planned operational steps, setting phantom bills of materials, determining how to incorporate differences between sites, planning transfer capacity between sites, connecting routings and boms, advanced planning capabilities with work centers and scheduling, etc.). Customers were unwilling to wait, and so we developed a stop gap capacity model that integrated with SAP data and master file type information in the interim.
• Operational flex capacity: Worked with Operations to understand flex capacity, operational capabilities, and what levers could be pulled to increase capacity in certain situations.
• Tie with SIOP (Sales Inventory Operations Planning): Integrate capacity planning into the SIOP process so that key decisions can be evaluated such as make vs buy, reallocation of production among sites, offload options to flex capacity, sourcing additional suppliers, etc.

We took the 80/20 standpoint to create a directional view of capacity so that we could address this critical bottleneck rapidly yet have it result in a reasonably correct dollar and capacity view. Although we powered through the order backlog with the planner to set dates, if you fast-forward two months, we had a directionally correct model that was used to flex capacity, plan resources, and develop an achievable revenue forecast. Once the bleeding stopped, we could drive continuous improvement, roll out additional SAP functionality, and automate capacity reporting in the business intelligence report tool. This set the company on course to have their best year yet and exceed revenue goals. Customers gained due dates sooner in the process, and the situation flipped from reactive to proactive to support a sustainable process and profitable growth.

The Path Forward

As companies grow and manufacturing surges with investments in the U.S., scaling capacity and knowing how many orders you can take will be critical. For example, if you have a short term bottleneck and must prioritize orders, you can focus on the strategic customers and utilize customer and product profitability analyses to determine which orders to fulfill. On the other hand, if you see a lull coming down the pike, you can optimize profit, take advantage of the opportunity to train and develop resources, and/or invest in additional capabilities for the future. The bottom line is that you can create your future instead of reacting to changes as they occur.

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Using Capacity Planning to Increase Revenue & Profitability