Middle-market manufacturers use advanced analytics to drive business
How advanced analytics can help manufacturers improve their bottom line.
It’s a new era for middle-market manufacturers, one where advanced analytics can help to decode complex manufacturing processes in order to reduce flaws, drive growth and improve the bottom line.
What is Advanced Analytics?
Advanced analytics uses mathematical tools to assess different types of business data that can help guide strategic planning, monitor real-time operations, and find the root causes of issues before they become larger problems. Traditionally, most manufacturers collect an overwhelming amount of data, but typically use it only for tracking purposes, not as a basis for improving operations. With advanced analytics, the focus is on predicting the effects of potential changes in business strategies on future outcomes.
In a 2014 report by The Economist, a survey of 50 C-suite executives from manufacturers in North America and Western Europe showed that while more than 90 percent of manufacturers collect data from monitoring production processes, less than half have predictive data analytics in place, and less than 40 percent use data analysis to find solutions to production problems.
What Benefits Can Advanced analytics Provide?
Manufacturers can use advanced analytics to help improve their businesses in a variety of ways from using predictive analytics to reduce risk in the supply chain to harnessing machine-level data to manage equipment life cycles. Here are four of the key areas where advanced analytics can make a difference to mid-market manufacturers:
- Quality control: Manufacturers have used statistical analysis to help control quality for almost a century. But, with improvements in databases and data storage, and easier-to-use analytical software, the quality of the data today is vastly improved. The additional data can lead to an improved bottom line. An article by McKinsey & Company illustrated that advanced analytical techniques allowed one chemical manufacturer to identify opportunities which increased earnings before interest and taxes by 55 percent.
- Forecasting demand: Demand for a product can be cyclical or seasonal, and historically, forecasting what would sell might have consisted of compiling an aggregate figure obtained from sale reps. Using predictive analysis enables manufacturers to examine sales data and apply it to more precise sales models in order to increase future sales.
- Maximizing equipment value: Manufacturers want to ensure they get the most value out of the equipment in their factories. Advanced analytics may help them do this by automating a great deal of the analysis process so that even individuals without high-level skills can perform various analyses that were previously only done by spreadsheet. Predictive analytics helps to optimize machine utilization, combining forecasted demand with the product mix to provide greater accuracy.
- Increasing equipment uptime: Using advanced analytics as a predictive tool may also enable manufacturers to increase production equipment uptime. In other words, knowing when a machine is likely to malfunction means that a manufacturer can perform the necessary maintenance in non-emergency conditions without the need to shut down production. Predictive analytics allows a business owner to take a look at the history of machine breakdowns and compare those breakdowns to sensor data the machine gives off in order to spot patterns before the next breakdown occurs.
New techniques are continually being developed in this area of preventive maintenance, some by individual manufacturing companies, many others by the manufacturers of production equipment. Equipment manufacturers can use this type of predictive analysis as an add-on service, collecting data from all of their machines from many different factories; more data on machine failure means more accurate predictions.
How to Use Advanced Analytics to Transform Your Business
The variety of advanced analytical tools available can help midsized manufacturers increase their share of today’s competitive marketplace by improving the quality of their products, better forecasting the demand for their products, maximizing the value of their equipment and more precisely predicting when their equipment is likely to malfunction. And it doesn’t take a group of IT specialists to obtain the data; even employees without high-tech computer skills can perform some, if not all, of these advanced analytical functions.
The key for manufacturers is to determine how to use analytics to transform and improve their businesses. To learn more, review the white paper by Sight Machine, the developer of the world’s leading manufacturing analytics platform, which shares the following best practices for implementing advanced analytics:
- A direct connection to multiple data sources
- The ability to handle terabytes of data
- The capacity to integrate both structured and unstructured data which including time series, metadata, pictures, videos and more
- Cloud-enabled functionality for both unlimited storage infrastructure and anywhere/anytime access
- Real-time dashboards along with deep-dive analytics for optimal insight, decision making.
Using the power of advanced analytics can help mid-sized manufacturers tackle tough problems, using predictive data to make better and faster business decisions.