Syncing production with projected sales is a balancing act for manufacturers. Produce too few products, and you risk shortages and missed sales opportunities. Manufacture too much, and that ties up precious capital in unsold inventory.
In this video interview, I learned how artificial intelligence (AI) helps manufacturers directly link customer demand and sales force activities back to the supply chain.
“Traditional sales forecasts aren’t necessarily the best input to production planning. AI gives sales managers the intelligence that production planning teams can rely on to exactly satisfy demand,” said Darren Goodman, enterprise architect at SAP. “Manufacturing companies can make fact-based decisions in demand planning, more accurately bringing sales volume predictions into the equation.”
The demo I saw at SAP TechEd showed how the sales performance predictive app relied on machine learning algorithms to analyze the likelihood of sales deals closure rates. Running on SAP S/4HANA Cloud, the app used actual, planned, and predictive sales models to identify key influencing factors on sales order closings, displaying correlations in colorful graphs. It also becomes “smarter” over time, delivering ever more accurate results.
“We’re replaced historically disconnected, less accurate data with a model everyone in sales, finance, and production planning can use to better match supply and demand,” said Goodman. “The future of ERP is using intelligent technologies like this to identify interruptions to the cash conversion cycle before they occur. Over time, sales managers can retrain the model with new data sets to create updated versions with potentially higher accuracy.”
Recent IDC research predicted more than 60 percent of global 2,000 manufacturers will rely on AI to drive digital transformation across supply chains by 2024 for productivity gains of over 20 percent. According to Sven Denecken, senior vice president, head of Product Management and Co-Innovation for SAP S/4HANA, intelligence brings value company-wide.
“Intelligent ERP supports data-driven decisions by providing insights into the future,” said Denecken. “Predictive models help people in each department gain the foresight into the part they have helping the company achieve overall revenue and margin goals. The information is available in the ERP system for all departments to use.”
AI promises to do much more than just close the gap between supply and demand. It can liberate the workforce from routine tasks such as data mining, time logging, researching logistics, and benchmarking budgets. This means teams can focus on higher-value tasks that depend on abilities unique to humans, like making judgment calls and forging relationships.
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