In many businesses, strategic decisions are based on numbers... but not always the right ones. A key indicator that varies from one department to another, a sales figure that arrives too late, or even a tinkered Excel table to “repair” a Power BI export... These situations are expensive, not only in money, but also in terms of responsiveness and credibility.
Chez Strat37, we often see the same scenario: teams spend more time validating numbers than deciding. However, it is possible to turn the situation around quickly. In 30 days, thanks to a progressive method and the support of artificial intelligence, your data can become reliable, enriched and ready to guide your decisions.
We start by building a solid foundation.
AI plays a role from this first phase by automatically identifying inconsistencies: duplicates, missing values, statistical anomalies on prices or quantities... It can even propose corrections based on your business rules and your histories.
In parallel, we are setting up a data quality score that measures accuracy, comprehensiveness, consistency, consistency, freshness, uniqueness, and traceability. The objective is clear: to correct as a priority the anomalies that have the most operational impact, so that 80% of the frictions disappear quickly.
Once the base is cleaned, you need to fill in the holes and provide context.
AI can accelerate the unification of product, customer, or site repositories by detecting correspondence and coding inconsistencies. It can also enrich your data from external sources — NAF codes, weather, weather, geographic areas, customer segments and automatically standardize formats (units, currencies, statuses).
This step is crucial: it transforms raw data into information ready for analysis, contextualized and usable in your decision-making processes.
Once the data is reliable and enriched, it is time for strategic exploitation.
We are setting up KPI contracts : each indicator has a unique definition, a clear source, a manager and alert thresholds. AI comes in here to automate anomaly detection, generate intelligent summaries, anticipate trends with forecasts, and even simulate “what-if” scenarios to assess the impact of your choices.
The strong point: you can query your data in natural language. Need to know which product grew the most last week? The AI answers you instantly, without going through complex filters.
Slow and unreliable reporting slows down the entire business. On the other hand, management based on clean and dynamic data frees up time, streamlines communication between services and makes it possible to react more quickly to market changes.
Beyond saving time, the impact is measured in opportunities seized more quickly, in losses avoided thanks to the early detection of anomalies, and in decisions better aligned with operational reality.
AI doesn't just produce pretty graphics: it acts throughout the chain, from initial reliability to implementation, by making information clear, coherent and directly usable.
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