AI in FMCG: The top use cases transforming global brands
Eight AI use cases global FMCG brands run today, from pricing to agentic AI, and why they need one causal model.
ArticleGrowth PlanningCausal AIUnified MarketingGrowthCausalityCMO
Enterprise Decision AI Resources & Blog | DATA POEM
Guides, case studies and research on Enterprise Decision AI, causal modeling and unified growth planning from DATA POEM.
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AI for CPG: How to plan across every retailer at once
How CPG brands use causal AI to plan trade and retail-media investment across Amazon, Walmart Connect, and Kroger in one model, not three.
ArticleGrowthCausalityCPGCMOPOEM365Causal AIEnterprise Decision AIUnified MarketingGrowth Planning
How to optimize your marketing budget: A data-driven playbook for CMOs
A CMO's playbook for reallocating an existing marketing budget by causal contribution, defending it to the CFO, and holding it in a downturn.
ArticleGrowth PlanningUnified MarketingCausal AIGrowthCausalityCMO
How AI is transforming marketing mix modeling
AI is reshaping marketing mix modeling, from open-source Bayesian models to causal structure learning. What's changing, and what it means for your budget.
ArticleForecastingEnterprise Decision AICausal AIGrowth Planning
Incrementality testing: What geo and holdout lift tests measure, and where they fall short
What geo lift and holdout incrementality tests actually measure, where each falls short, and where always-on causal measurement fills the gap.
ArticleCausalityCausal AIPricing & DemandForecastingEnterprise Decision AI
Predictive analytics vs causal AI: why knowing "what will happen" isn't enough
Predictive analytics tells you what will happen; causal AI tells you what to do about it. The methodology difference, and when each one fits.
ArticleCausalityCausal AIEnterprise Decision AIGrowth PlanningData OfficerForecasting
How does causal AI replace traditional analytics for enterprise revenue decisions?
See the mechanism behind causal AI's replacement of MMM, MTA, and forecasting models for enterprise revenue decisions, and where each still falls short.
ArticleCausalityForecastingFOUNTPOEM365Enterprise Decision AICausal AIUnified Marketing
Agentic AI in marketing: Why an LLM agent can recommend a decision but cannot own it
AI agents execute marketing decisions at scale. But can they own them? Why LLM agents recommend but don't decide, and what causal reasoning changes.
ArticlePOEM365FOUNTEnterprise Decision AICausal AIForecastingCausalityUnified Marketing
Unified marketing measurement is still fragmentation, unless you use one model
Unified marketing measurement usually means combining MMM, attribution, and incrementality. But that's still fragmentation. Here's why we say so, and what consolidating everything into one causal model changes.
ArticleGrowthUnified MarketingCausal AIGrowth PlanningCMO
What is a Large Causal Model? Reconciling three competing definitions
We define the Large Causal Model, and how it differs from three academic uses of the term and from a standard large language model.
ArticleCausalityEnterprise Decision AICausal AI
Data silos and the fragmentation problem: Why enterprise brands are making $500M decisions from five contradictory models
Consolidating data into one warehouse does not stop teams getting different answers. The real fragmentation is in the models. Here is how to fix it.
ArticleGrowthCausalityEnterprise Decision AICausal AI
Why most enterprise AI projects fail, and how causal architecture fixes it
Most enterprise AI projects fail for reasons no better model can fix. Here is the architecture problem underneath, and how to solve it.
ArticleEnterprise Decision AICausal AI
The fourth layer: how Enterprise Decision AI completes the enterprise intelligence stack
The enterprise intelligence stack has three layers that describe the business and one missing layer that decides. Here is what the fourth layer is and where it sits.
ArticleEnterprise Decision AICausal AI
Large Scale Causal Foundation Models [Whitepaper]
Read the research behind POEM365. FOUNT is the world's first Large Causal Model, beating Google, Salesforce and the M5 Kaggle winner. Download the whitepaper.
WhitepaperCausal AIData Officer
Build vs Buy for Causal AI: The True Cost of Building In-House vs Deploying POEM365
In-house causal AI runs $11M+ over 18 months; POEM365 runs $500K–$1.5M over three years. The real build-vs-buy math, and what most teams get wrong.
ArticleCausal AICFO
What is Causal AI? The Complete Guide for Enterprise Leaders
Causal AI explains why outcomes happen, not just what correlates. A plain-English guide to how it works, what it replaces, and where it adds value.
ArticleCausal AICEO
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