4/25/22 2:30 PM
There are constant obstacles and challenges facing manufacturers today. Managers and supervisors are asked to balance the demands of maintaining a healthy business with an industry greatly affected by the changing times. As a result, planners are looking to technology to help in satisfying increased demands on their company.
Data tells a story. By gathering and analyzing data obtained over years of company operations, your manufacturing business could increase efficiency and return on investment. There are multiple ways predictive analytics can be deployed in the manufacturing industry. Here are some suggestions:
Manufacturing requires equipment and machinery, two things that need regular upkeep. When a piece of necessary equipment breaks down, that can mean thousands of dollars in lost revenue. Using data analytics to predict when machines and equipment should be serviced is essential to maintaining efficiency. Additionally, employing the use of real-time sensors can collect data to anticipate the likelihood of repairs. For example, a machine showing an increased running temperature could signify it is being overworked. These sensors can then message management on machine behavior, so sudden breakdowns become a thing of the past.
Customer demands fluctuate throughout the year, especially for seasonal consumer goods, and can be forecasted using predictive data analytics. Your company likely already performs some kind of market analytics. Numerous factors contribute to business success with clients and customers. Being able to anticipate demand can better enhance B to B and B to C relationships.
Materials that didn’t ordinarily present scarcity before the pandemic are now in short supply. Lumber, in particular, is more challenging to procure due to the heightened demand for construction materials for consumers and businesses. However, companies using predictive analytics for raw material procurement are more prepared with their inventory than those surprised by this new obstacle.
The market for skilled workers is more competitive. By using predictive analytics to observe employee productivity, managers can better target those who are over or under-performing. An overperforming employee is an asset who may not require the money or time spent on an underperforming employee. Perhaps pairing these two together could allow underperforming employees to learn from their coworkers to increase productivity.
In conclusion, predictive data analytics can enhance your manufacturing business and lead to future success. Data can be gathered to help supervisors and managers make informed decisions regarding Predictive Maintenance, Market Analytics, Raw Material Procurement, and Human Resources Planning. PlanetTogether Advanced Planning and Scheduling software has features that can help in all these areas. There’s even a feature allowing you to efficiently schedule employees and create a schedule that considers their productivity. When it comes to empowering your manufacturing company, PlanetTogether APS software is the best tool for optimizing your schedule.