DefTech Manufacturer Improves Production Lead-Time Forecasting Accuracy to 93% with IT-Enterprise ERP

For a manufacturer operating in the DefTech sector, one of the critical challenges was determining the actual lead time for a new order. The previous accounting system could not automatically calculate the expected completion date based on current production capacity, resource availability, and material availability. As a result, agreeing delivery dates with customers largely depended on manual assessments of the production situation.

The company implemented a multi-level planning system based on IT-Enterprise, using CRP (Capacity Requirements Planning). The solution connected customer orders with actual production capabilities and introduced a “Promise Window” — a forecasted completion timeframe calculated based on the current state of production. As a result, production lead-time forecasting accuracy increased to 93%.

From Standard Lead Times to an Actual Completion Date

Before the ERP solution was implemented, accurately determining an order’s completion date was difficult. The standard duration of production operations alone could not show when an order would actually be completed. The final date was affected by existing orders, equipment and workforce utilization, material and component availability, the sequence of production operations, and other production constraints.

The ERP system was therefore configured to generate forecasts based on the combined impact of these factors.

The calculation takes into account:

• current equipment utilization and production capacity;
• workforce availability;
• availability of materials and components;
• production routings and operation sequences;
• the current order portfolio;
• production resource requirements for each order.

This enabled the manufacturer to determine lead times based not simply on standard production durations, but on the actual production situation at the time an order was accepted.

CRP Planning and the “Promise Window”

When a new order is received, the ERP system assesses the resources required to fulfill it and matches these requirements against available production capacity.

CRP planning takes into account the workload of individual production areas, already scheduled operations, the sequence of manufacturing processes, and the availability of required resources. Based on this calculation, the system generates a forecast completion date.

This calculation became the foundation for the “Promise Window” — a timeframe that the company can use when agreeing order delivery dates with customers.

As a result, the sales team receives more than an estimated date: it receives a timeframe supported by the current production capacity.

Implementation Results

After the ERP solution went live, the process of agreeing delivery dates became significantly more controlled. Production workload, resources, materials, and orders are considered together, eliminating the need to manually collect information from different production areas each time a delivery date needs to be assessed.

This also changed the approach to order management: delivery dates are determined before the company commits to production, rather than being explained after a delay occurs.

For sales, this means the ability to provide customers with a well-founded delivery date faster. For production, it provides visibility into which orders already have agreed deadlines and what load they create for the company's resources.

Another important benefit is faster response to changes. If equipment availability changes, materials are delayed, or an urgent order is added to the production schedule, the updated calculation shows how these changes may affect existing delivery dates.

68% → 93%: Making Forecast Accuracy Measurable

One of the key project results was an increase in production lead-time forecasting accuracy from 68% to 93%.

This means that the completion date forecast by the ERP system became significantly closer to the actual order completion date. For a manufacturing company, this KPI has direct operational value: the more accurately a delivery date is determined when an order is accepted, the lower the risk of a gap between the customer commitment and the actual production capability.

Why This Matters for DefTech

For Ukrainian defense and dual-use manufacturers, delivery-time predictability becomes increasingly important as production scales up. As order volumes grow, so does the number of dependencies: one order may compete with another for equipment, workforce, or components, while a change in a single production parameter can affect the entire manufacturing schedule.

In such an environment, standard lead times no longer provide the full picture. Manufacturers need to know not only how long it takes to produce a product, but also when a specific order can realistically move through all required production operations.

This was the practical outcome of implementing the solution at the DefTech manufacturing company: production constraints were connected with customer delivery commitments within a single digital environment.

The Result

The project enabled the DefTech manufacturer to move from estimated lead times to data-driven forecasts based on the actual state of production.

For DefTech, this means moving from reactive delivery management to a model in which the manufacturer can determine when an order can realistically be completed before it enters production.

Digital solutions from IT-Enterprise turn everyday manufacturing challenges into manageable processes — from calculating available capacity to establishing realistic customer commitments.