Découvrir
Ateliers de procédés, audit des données, et un écart d’adéquation avec le produit standard.
Phase 1 · Sensibilisation
Strategic AI, data and analytics
Decision intelligence over static reporting: forecasting cash, inventory and churn
How finance and operations move from looking back at last month to forecasting cash flow, stock and customer churn from the same operational data.
The short answer
A report tells you what happened. A decision model tells you what to do next and how sure it is. Start with one decision, such as how much cash you will have in thirteen weeks, and build backwards from it.
Stages
From report to decision
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1
Name the decision Write down the decision, who makes it and how often: reorder, collect, hire, discount.
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2
Find the drivers List the data that moves it: open invoices, payment history, lead times, demand.
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3
Build the forecast Start with a simple, explainable model on the governed data. Add sophistication only if it beats the simple one.
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4
Put it in the workflow Show the forecast where the decision is made, with the reasons beside it.
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5
Close the loop Compare forecast with result every period and retrain or retire the model.
Decision points
Three questions that change the answer
Is the decision made often enough to justify a model?
YesBuild it.
NoKeep a report and a conversation.
Can the user see why the model says this?
YesRelease it to users.
NoSimplify it until they can.
Does it beat the simple baseline?
YesKeep it.
NoUse the baseline.
Milestones
What done looks like, and when
- Month 1 Decision and baseline measured.
- Month 2 First forecast on governed data.
- Month 3 Forecast embedded in the workflow.
- Quarterly Forecast accuracy reviewed.
Principles we hold to
- Begin with the decision, not the dashboard.
- Explainable beats clever.
- Always compare with a simple baseline.
- Retire models that stop earning their place.
Questions fréquemment posées
What is decision intelligence?
Using data and models to improve a specific, repeated business decision, with the reasons shown to the person making it, instead of only reporting history.
Can Dynamics 365 forecast cash flow?
Yes. Cash forecasting, inventory forecasting and customer analytics can be built on Dynamics 365 data with the Microsoft data and AI stack. Accuracy depends on your history and data quality.
Take this to your own programme.
Tell us where you are. We will tell you plainly what this means for your estate and what we would do first.
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Next: Retail and FMCG: a Dynamics 365 blueprint for POS, fiscal compliance and branch networks →
How an engagement runs
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It starts with a 45-minute consultation, then a discovery and fit-gap workshop on your own processes. You receive a written fit-gap and a phased plan before a programme is agreed. Four phases follow, each with something you can use and review.
Conception
Plan de solution, carte d’intégration, et les extensions dont nous aurons réellement besoin.
Déploiement
Configuration, répétitions de migration, formation basée sur les rôles, UAT et transition progressive.
Soutien
Hypercare, services managés, portail client, évaluations d’optimisation programmée.
What drives the cost: users, legal entities and currencies, integrations, data migration and the gaps found against standard. See how pricing works, run the three-minute readiness score, or book a consultation.