Forecasting and AI for Manufacturers
This post about AI for manufacturers originally appeared in https://servicecasterblog.com/forecasting-and-ai-for-manufacturers/. Complete Intelligence is honored to be part of the USAMfgHour series, hosted by CVT Plastics, DCSC Inc., and Service Caster.
On May 21, 2020, Tony Nash, the CEO and Founder of Complete Intelligence (@complete_intel), hosted a #USAMfgHour Twitter chat on forecasting and AI for manufacturers. Below is a summary of Tony’s (@TonyNashNerd) questions and answers on this very important topic.
Question 1: What are some of the trends manufacturers can expect to see in 2020 and in the next few years?
Answer 1a: “Procurement and category leaders will increasingly become strategy players within their companies. With AI/ML tools for cost transparency & scenario planning for manufacturing, these leaders can show ROI, significantly improve margins”
Answer 1b: “#Supplychains will become more regionalized over the coming years. #Manufacturers will need #AI #ML cost technology to quickly run scenarios on cost estimates, supplier comparison and risk assessments for each new #sourcing location”.
Question 2: Why choose an #AI solution for cost control in #manufacturing?
Answer 2: “Non-AI forecasting methods are limiting. As companies are reforecasting, decision cycle time is critical. AI/ML models compute millions of calculations to optimize cost outlooks. Better information & forecasts = more informed clients = better decisions”
Question 3: Did you know the average consensus forecast error is double digits? Do you know the accuracy of the forecasts you are using?
Answer 3: “We regularly test our #AI #ML forecast accuracy compared to consensus forecast. Our core belief is that data & math should drive the forecast results without human intervention or bias. What we found was astonishing. CI outperformed consensus 88% of the time.”
Question 4: If enterprise BOM materials aren’t publicly traded commodities, can these material costs be forecasted accurately?
Answer 4: “Yes! One of the challenges we see for product lines is that consensus forecasts & indexes lack context and detail for specific products, components, and raw materials. Our #AI #ML platform incorporates enterprise & market factors for specific cost & revenue items.”
Question 5: Should my company build an #AI #ML cost analysis model in-house or outsource?
Answer 5: “Consider the budget, time to results, and expected outcomes. Looking for value and access to results quickly? Look to outsource those #AI #ML projects. Commercialized AI applications like @complete_intel’s CI Futures & CostFlow have a track record & proven success.”
Visit Complete Intelligence to learn more about its #AI and #MachineLearning platform that gives highly accurate revenue and cost #forecasts
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