Dr. Chockalingam

SAP IBP Worst Practices WP3: When Your Algorithm Forecasts a Ghost — The Hidden Cost of Ignoring PLM Flags It is not about the model but everything that supports it. WP3: Not considering PLM or other flags that reflect business realities. Here is a forecast output from a live IBP instance. The product had zero demand for 18+ months. No [...]

Worst Planning Practices in SAP IBP — WP #2: A "Best Fit" Model Pool with No Design Thinking Continuing our Worst Planning Practices in SAP IBP series — The Best Fit configuration checked all the right boxes during implementation, but its real-world performance introduced considerable forecasting challenges. The Scenario A consultant configured Best Fit statistical forecasting in SAP IBP [...]

Worst Planning Practices in SAP IBP — WP #1: Applying an Aggressive Forecast Model to a New SKU Most SAP IBP problems don't announce themselves. They show up months later — as excess inventory, a write-off, or a board asking why forecast accuracy keeps sliding. Trace it back, and it's almost always a planning decision nobody challenged. This is [...]

Implementing SAP IBP Inventory Optimization in CPG — what actually works Most implementations take longer than they should — not because the technology is hard, but because teams try to boil the ocean before proving value. 💡 Secondly, the IO methods leveraged are quite basic NOT doing justification to the tool capabilities. After working with CPG companies across snacks, [...]

SAP IBP Heuristic vs Optimizer: When to Use Each Engine (and Why the Wrong Choice Costs You Service Levels) Most SAP IBP teams default to the Heuristic engine because it's fast. In constrained, multi-node supply chains, that habit quietly drives stockouts, excess inventory, and lost margin. Here's how to choose deliberately. Fast planning isn't smart planning. It's one of [...]

#Demand_Modeling_in_SAP_IBP Three steps involved in setting up a Demand Model in SAP IBP are described in this modeling primer videos for Demand Planners. Step 0 — General Settings surfaces the key configuration parameters: planning horizon, time profile, aggregation level, and key figure mapping — the foundation everything else depends on. Step 1 — Pre-Processing now explicitly calls out the [...]

In an era of relentless market shifts, a "good guess" is no longer a viable strategy for supply chain leaders. At Valtitude, we recognize that moving from reactive firefighting to proactive planning requires more than just a software license—it requires the precise engineering and implementation of a robust digital core. As specialists in SAP Integrated Business Planning (IBP), we [...]

New product forecasting is always a challenge for most organizations. FMCG and Food & Beverage companies, in particular, experience this frequently — sometimes as often as twice a year. Ironically, most planners rely on manual forecasts that are numerically entered directly into the system, typically sourced from a brand manager responsible for the category. At times, this could be [...]

Effective supply chain management demands both efficiency and precision. At Valtitude, we combine SAP Integrated Business Planning (IBP) with a sophisticated segmentation algorithm to classify products and the product-customer matrix. This structured approach enhances both demand modeling and inventory strategies, helping our clients meet market demands while optimizing resources. Strategic Segmentation for Better Planning Our proprietary algorithm segments products [...]