In the manufacturing business, striking the right balance between overproduction and underproduction creates the lifeline of production process efficiency. While the imbalance often results in loss of revenue or profitability for the manufacturer. Highly optimized production processes boost the business by ensuring that the product is available for the customer when they need it and at the same time, inventory is not sitting in the warehouse, incurring the unnecessary cost.
‘how to get there?’ ‘predictive analytics is the most effective and proven way to get there! With application in a wide range of industries, predictive analytics is increasingly playing a vital role in improving productivity, sales and of course, profitability. Predictive analytics is expected to save manufacturers approximately $630 billion by 2031.
Here are some areas of the supply chain where predictive analytics can widely help the businesses
Identification of customer purchasing behaviors in real-time
Predictive analytics enables detecting purchasing behaviors in real-time, providing manufacturers and logistics firms a whole new insight on their customers. This, in turn, helps manufacturers in improving product design, product rollout and order fulfillment.
Effective demand forecasting
Demand forecasting plays a major role in your supply chain strategy. Automated and accurate demand forecasting powered by predictive analytics empowers you to proactively respond to demand fluctuations and maintain ideal stock levels at all times.
Price optimization
By harnessing the power of big data with predictive analytics, manufacturers today are able to adjust the prices of their products according to market demand and competition. AI and machine learning technologies are playing a major pivotal role in making more accurate price predictions.
Operational effectiveness
By increasing the quality of the data across the entire supply chain and identifying the bottlenecks in the production process help gain tremendous operational efficiency during the supply chain process. The right mix of predictive analytics and IoT (Internet of Things) helps in proactively predicting and preventing machinery failures by feeding them with timely information on the required upgrades, services, repairs or replacements.
Better supplier management
Advanced data analytics tools can also help businesses gain valuable insights on their suppliers. By assessing these suppliers against various key performance metrics like quality of service, location, profitability, customer reviews, level of compliance, etc., manufacturers can select the most appropriate supplier for any particular product.
Many leading manufacturing players have already begun leveraging predictive analytics solutions to make more informed decisions and improve efficiency. In the years to come, the industry will witness a disruptive transformation in its supply chain space and manufacturers will have happier, more satisfied customers. When are you joining the revolution?
