Implementing Predictive Analytics Outside the Factory Floor
A growing number of manufacturers, particularly those with large global footprints and complicated supply chains, have realized the power of predictive analytics. However, many are not taking advantage of this technology for larger, strategic decisions.
Some manufacturers are using predictive analytics to improve production line productivity, combining industrial IoT, cloud and analytics technologies to predict machine failure. Others are using predictive analytics to improve quality control by using automated sensors to detect the smallest of flaws.
Where predictive analytics offers manufacturers the highest ROI, though, is not analyzing processes inside the factory – but rather in analyzing the world’s influence on company performance.
Manufacturers using predictive analytics to accurately forecast demand — using internal and external data — are poised to make improved strategic decisions, gain greater visibility into their supply chains, plan better for market disruptions and know where best to invest their marketing dollars.
Using predictive analytics and external data, companies can develop fact-based demand plans and gain insight into upcoming headwinds and tailwinds. This can also reduce the bias during a consensus forecasting process.
Traditional forecast methods often rely exclusively on trend analysis of historical data. This does not take into account changes in global markets, changes in consumer demand, or regional economies. Often, a manufacturer’s forecast is highly dependent on their largest customer’s plans. Getting this incorrect can have ripple effects through the supply chain, resulting in excess inventory and reduced margins.
Bottom line: If demand estimates are off, companies are effectively operating in the dark. No wonder only one-third of CEOs have a high-level of trust in the accuracy of their data analytics, according to KPMG.
For large global manufacturers with multiple product lines or products that serve diverse end-use industries, forecasting can be an extremely time consuming and frustrating process. It may take analysts months to compile estimates, only to discover they failed to account for an internal or external factor that spoiled their results.
In contrast, predictive analytics can greatly improve the speed of market analysis. Using predictive analytics software, what would take teams months to analyze can often be cut down to weeks or days.
