Building a Scalable SIOP Foundation to Support Growth and Optimize Inventory

---

The Challenge

A growing manufacturer was preparing for a significant increase in demand, but its planning processes were still highly manual, fragmented, and difficult to scale. Limited visibility across demand, inventory, capacity, and production constraints made it harder for teams to plan proactively, while inconsistent governance and low confidence in ERP planning outputs contributed to excess inventory and reactive decision-making.

To support future growth, the organization needed a more disciplined planning model—one that could improve visibility, strengthen accountability, and create a reliable connection between demand signals, inventory policies, production planning, and execution.

---

Our Approach

TriVista established a clear current-state baseline by mapping cross-functional planning processes, evaluating SIOP maturity, analyzing inventory and planning data, and assessing how effectively the organization was using its ERP and MRP capabilities.

The assessment focused not only on identifying process gaps, but also on understanding the underlying causes of planning instability. TriVista evaluated master data quality, inventory policies, production scheduling practices, demand planning inputs, and governance routines to determine where changes would have the greatest impact.

From this analysis, TriVista developed a prioritized roadmap centered on strengthening planning governance, improving master data integrity, optimizing inventory policies, increasing production planning discipline, and building a more integrated SIOP process. The result was a practical implementation plan designed to improve near-term performance while creating a scalable foundation for future growth.

---

The Results

TriVista identified a substantial opportunity to improve working capital efficiency, including approximately 47% inventory reduction potential through stocking policies better aligned to demand variability, lead times, and service requirements.

The assessment also uncovered gaps in MRP configuration and master data that were generating unnecessary exception noise and weakening confidence in the planning system. TriVista defined specific actions to clean planning parameters and re-establish MRP as a more reliable planning signal.

Production schedule adherence ranged from 57% to 88%, highlighting the need for stronger schedule governance, recurring performance tracking, and root-cause management. Demand planning analysis also revealed OEM forecast bias ranging from -19.5% to +13.1%, creating a clear case for more disciplined forecasting inputs, accuracy measurement, and a stronger demand-to-supply handoff.

By translating these findings into a prioritized implementation roadmap, TriVista gave the client a practical path to reduce inventory, improve planning reliability, strengthen accountability, and build the SIOP capabilities needed to support sustainable growth.