Enterprise Decision AI Resources & Blog | DATA POEM

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.

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.

How to build an AI business case your CFO will approve

A step-by-step way to build the AI business case your CFO will fund: the spend table, the objections, and the build-vs-buy call.

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.

Decision AI vs Business Intelligence: why dashboards don't drive growth

Business intelligence shows you what happened. Decision AI decides what to do next. Here is the real difference, and why dashboards alone never move growth.

How enterprise leaders use AI for business growth

A practical guide to AI for business growth for enterprise leaders — the use cases that move the P&L, why most underdeliver, and what connects them into one decision model.

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.

Enterprise Planning: How Fortune 500s Are Unifying Strategy and Execution

Enterprise planning unifies strategy and execution. See how Fortune 500 leaders build one plan across finance, supply chain, and commercial.

Enterprise Decision AI in Practice: How Fortune 500 Brands in CPG, Retail, and Automotive are Using It Today

What Enterprise Decision AI looks like in CPG, Retail, and Automotive — and why it differs from the AI you already have.

Three Categories. Same Unification Problem. One Category Left to Solve.

CRM unified customer data. ERP unified operations. Enterprise Decision AI is the fourth category, unifying the enterprise growth decision into one model.

Your Analytics Stack Reports. Enterprise Decision AI Decides.

MMM, attribution and forecasting all report what happened. None tell you what to do next. How Enterprise Decision AI prescribes where the next dollar goes.

Four Agents. One Unified Causal Clarity.

Most AI agents retrieve and summarize. POEM365's four causal Decision Agents forecast, plan, optimize and explain enterprise growth. See how they work.

Every Function Hit Their Number. The Business Still Lost $58M.

Every function can hit its KPI while the business loses money, because no model sees the system. Learn why the overlap goes unpriced, and how to fix it.

Different Models. Different Answers. One Decision.

Same Budget. Different Architecture. +$130M in Recovered Growth.

How a Fortune 500 brand recovered $130M in growth from the same marketing budget, using POEM365's unified causal model. Same spend, very different result.