Practical thinking for consumer goods planners

True IBP excellence doesn't come from a monolithic suite. It comes from purpose-built tools — like CauSelf and your supply chain planning tool — designed to be exceptional in their domain and to work seamlessly together.

42% of companies scrap AI initiatives. The problem isn't the model—it's the architecture. Learn why AI-native platforms actually ship.

45% budget overruns, 7% schedule slippage, 56% less value. Learn why rapid 12-16 week increments are the antidote to big-bang IT project risk.

Only 20-25% of CPG companies link demand planning to P&L. Discover why finance leaders need visibility into profitability by SKU, channel, and scenario.

Despite AI hype, adoption remains low in CPG. Discover why teams struggle with data science, and how CauSelf turns complexity into clarity for better decisions.

Resilience isn't about holding more stock — it's about planning with agility. Discover how integrated demand, trade, and financial planning drives supply chain resilience.

Most FMCG companies spend $200K+ annually on scan data but only analyse a fraction. Discover how to unlock hidden insights and turn data into decision-ready intelligence.

Most companies live with hundreds of small spreadsheet disasters every month. Discover why spreadsheet chaos erodes performance — and how to fix it without losing flexibility.

Why accurate budget tracking drives better demand forecasts. Discover how sales and demand planning can work symbiotically to hit targets and improve forecast accuracy.

Why sales teams and demand planners have been talking past each other for 30 years — and how the tool design is the root cause, not the people.

Overfitting is the statistical equivalent of an octopus predicting the World Cup. Here's how to spot it in your FMCG forecast models — and what to do about it.

Even Fortune 1000 companies with $50M+ data budgets are struggling to build a data culture. What does that mean for mid-market consumer goods companies standing at the edge of the chasm?

Most businesses have more usable data than they think. Here's how CauSelf analyses up to 20 causal factors — including freely available public data — to improve forecast accuracy.