Are your forecasts wrong again?!
Go on, admit it: your forecasts are sometimes – or even often – wrong. Although market volatility and global instability don’t help, companies that are beginning to use automation, machine learning and data analysis create forecasts that are noticeably more precise.
Nobody saw the recent health or geopolitical crises coming. But real-time data analysis can help you adapt more effectively than your intuition. Take the case of a plant whose production forecasts were regularly off by 30%: the manufacturer was able to cut its inventories and product obsolescence by 20 to 40% (depending on the line) and boost sales by 5%. What was its secret?
- Over a six-month period, the company introduced a machine learning-based model capable of fetching and processing much more data in real time, including external data, on market trends, for instance, or Google searches from internet users.
- The company ensured that the finance and operational functions worked together. An obvious thing to do? Yes, but seldom implemented!
- Last but not least, the company found the right talents to deliver the project.
AI spots patterns and correlations that you miss. If you input relevant, continuous data, the results will be quickly visible.
“Predictive sales forecasting : Is your finance function up to code ?”
by Holger Hürtgen, Frank Plaschke, Karolina Sauer-Sidor and Nils Wittmann (McKinsey, August 11, 2020).
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