Dr. Chockalingam

About Dr. Chockalingam

Mark Chockalingam is the Founder and President of Valtitude, a strategy and solutions consulting firm headquartered in Boston, MA, specializing in Demand Forecasting, S&OP, and end-to-end supply chain transformation. Founded in 2004, Valtitude serves Fortune 500 companies and mid-market businesses across industries including Pharmaceuticals, Consumer Products, High-Tech, Food & Beverage, Aerospace, and Oil & Gas. Dr. Chockalingam is also the Founder and Chief Architect of PlanVida, Valtitude’s cloud-based supply chain planning platform. Mark has over twenty years of consulting and corporate experience in Predictive Analytics, Sales Forecasting, Supply Chain Optimization, and Integrated Business Planning. Mark has consulted for many marquee names including Wyeth-Pfizer, Miller SAB, FMC, Labatt USA, Pepsi Foods, Schlumberger, Honeywell, Facebook (now Meta), Qualcomm, Tropicana Brands, Prestige Healthcare, Cuisinart, Abbott, and Mars Petcare, among others.

PlanVida 2.0: What It Means for S&OP and IBP Teams

By |2026-08-14T15:22:39+00:00August 14th, 2026|Categories: Blog|Tags: , , , , , , |

PlanVida 2.0 Most planning platforms do one layer well — forecasting, or inventory, or S&OP, and leave the rest to spreadsheets and workarounds. PlanVida 2.0 takes a different approach: one system spanning S&OE, S&OP, IBP, and executive decision-making. What's [...]

Why Shipment Forecasting Fails CPG Demand Planning (And What Fixes It)

By |2026-08-12T11:38:46+00:00August 12th, 2026|Categories: Blog|Tags: , , , , , , , , , , |

POS-Based Demand Forecasting: Why CPG Companies Must Flip from Shipments to Sell-Through 🚚 Most CPG demand planning models may not be forecasting the right signal. We build sophisticated statistical and ML models on outbound shipments - what left our [...]

IBP vs S&OP: Why Treating Them as Separate Processes Creates Chaos

By |2026-07-31T16:04:59+00:00July 15th, 2026|Categories: Blog|Tags: , , , , |

IBP vs S&OP: Why They Are Not Two Different Processes There is a number of visuals and infomercials making the rounds in LinkedIn praising the glories of IBP - the Integrated Business Planning process and why this is distinctly [...]

Forecasting the Pattern vs the Cause: The Smoothing Trap in SAP IBP

By |2026-07-30T11:16:49+00:00June 19th, 2026|Categories: Blog|Tags: , , , , |

Forecasting the Pattern, Not the Cause: Why Smoothing Over Events Distorts Your Demand Signal Actual Worst Practice in SAP implementations: Removing all events from historical data and making it flat to produce a smoothed forecast!! Ask yourself: is your [...]

SAP IBP Consulting: From Blueprint to High-Performing Planning Machine

By |2026-07-30T11:31:43+00:00June 12th, 2026|Categories: Blog|Tags: , , , , |

Turning Supply Chain Blueprints into Reality: SAP IBP Consulting from the Ground Up At Valtitude, we help organizations unlock the full power of SAP IBP — from the ground up.  Brownfield or Greenfield, we level the playing field for [...]

Why Splitting Monthly Forecasts Evenly Across Weeks Hurts Your Supply Plan

By |2026-07-30T11:40:50+00:00June 12th, 2026|Categories: Blog|Tags: , , , , , , , , , |

Worst Practices Supply Chain Planning: Equal-Split Weekly Disaggregation That Erases Real Demand Patterns 📉 Equal-split forecasts in SAP IBP: convenient, but is it costing you? 🤔 A pattern I see often in IBP implementations: the monthly forecast gets disaggregated [...]

Forecasting Worst Practices: When Discontinued Products Never Really Die

By |2026-07-30T12:05:20+00:00June 11th, 2026|Categories: Blog|

Forecasting Worst Practice #8: Ghost Demand from Discontinued Products That Never Leave the System This worst practice is not just in SAP IBP.  This is common across many systems. Forecast accuracy gets scrutiny. Master data accuracy deserves the same. [...]

Why Defaulting to Heuristics in Constrained Supply Networks Costs You

By |2026-06-10T14:48:24+00:00June 10th, 2026|Categories: Blog|

SAP IBP Worst Practice #5: Heuristics on high gear ⚡ Fast planning ≠ smart planning. A lesson every supply chain team eventually learns the hard way. A typical worst practice in SAP IBP implementations: using the Heuristic engine in highly constrained, [...]

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