Forecast Bias: When Sales Targets Become Forecasts

🚨 When sales targets become forecasts, inventory carries the risk.

📊 This (anonymized) PlanVida example highlights:

📉 𝟳𝟵% forecast accuracy, down 𝟭𝟭.𝟭% points from last month

⚖️ 𝟭𝟱% forecast bias

🔎 High consensus forecasts for 𝟴 𝗦𝗞𝗨𝘀

The problem? Purchasing and production may commit cash to inventories and production that customer demand may not support.

⚠️ Unsupported optimism can turn into excess stock, aging inventory, and working capital commitments

👉 Question: “𝗪𝗵𝗮𝘁 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲 𝘀𝘂𝗽𝗽𝗼𝗿𝘁𝘀 𝘁𝗵𝗶𝘀 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲?”

🎯 Turn PlanVida’s indicators into decisions:

🔹 Review flagged SKUs using the AI Planning Brief

🔹 Validate forecast uplifts against orders, promotions, and market evidence.

🔹 Keep sales targets separate from expected demand.

🔹 Assign owners and track accuracy and bias after changes.

🤝 Demand, Sales, Supply, and Finance must agree on the assumptions before committing the forecast into execution.

🏛️ The decision belongs in your S&OP/IBP forum.

💬 Which indicator would trigger your next demand consensus review? Share your experience.

Read our related posts:

• S&OP is not consensus - It is conflict resolution!

• How Does Forecast Accuracy Matter Anyway?

• AOP vs S&OP - The Metrics Scorecard