Smart Manufacturing Blog

Welcome to your source for all things smart manufacturing. Whether you’re looking for expert insights, hard data, or actionable tips for your plant floor, we’ve got you covered every week of the year.

Announcement
7th Annual State of Smart Manufacturing

Now Available!

Get your copy of the 7th Annual State of Smart Manufacturing and hear from 300+ manufacturers in this new survey report!

Where Did My Forecast Accuracy Go?

Machine Learning, Supply Chain Management
June 14, 2023

Many people use GPS to navigate to their destination. It is fast, accurate, and uses advanced satellite technology to deliver people to a precise location on a map. But imagine a world where GPS only gives drivers a vague direction to point their car in with no set path or even distance. Chances are, it would fall out of favor quickly.

Yet that is what countless manufacturing companies do when forecasting their operation. Using manual data collection, spreadsheet-based analysis, siloed data, and spotty communication, they wind up with a forecast that says, “Go that way…for a while.”

Accurate forecasting is crucial in a complex manufacturing system to meet customer demand. And it depends on precise control of data, which is impossible to achieve with manual tracking methods. But, today, there is software that will bring automated data and processes to make highly accurate forecasts for any operation.

The Importance of Precise Data Control

Manufacturers need a comprehensive and precise understanding of their data to achieve accurate forecasting. This understanding includes information about production processes, inventory levels, lead times, and customer demand patterns.

However, manually tracking and analyzing this data in complex manufacturing systems can be time-consuming and error-prone. And inaccurate or incomplete data leads to poor forecasting, resulting in stockouts, excess inventory, production delays, and dissatisfied customers.

Manual Tracking - The Barrier to Accurate Forecasting

Manual tracking and forecasting methods simply cannot keep up with the vast amounts of data generated by today’s advanced, high-speed manufacturing equipment. It’s like the adage “trying to drink from a fire hose.”

In addition to the overwhelming volume of data, the risk of human error increases as employees must manually input, update, and analyze data across spreadsheets and siloed disparate legacy systems. This practice leads to systemic inaccuracy and time-lagged visibility into the supply chain.

Without the ability to process all the data coming in and by leaning on insufficient data that is captured, companies struggle to make accurate predictions about future demand and fail to optimize their production and inventory levels fully.

Software Solutions for Enhanced Forecasting Accuracy

Implementing advanced software solutions specifically designed for supply chain management can dramatically improve forecasting accuracy. It embeds with your processes to automate data collection and analysis, and it empowers better decision-making so manufacturers can access real-time, accurate information about their operations.

Some of the key benefits of implementing supply chain planning software to improve forecast accuracy include the following:

  1. Data Automation - Automated data collection and processing reduce the risk of human error, ensuring data accuracy and consistency.
  2. Real-Time Visibility - Access to real-time data and analysis enables manufacturers to adjust quickly to changes in demand or production constraints, minimizing disruptions and improving forecasting accuracy.
  3. Advanced Analytics - Software solutions often include advanced analytics capabilities, allowing  manufacturers to uncover hidden patterns and trends in their data, further  enhancing their forecasting accuracy.

Emerging Machine Learning Capabilities

Integrating machine learning capabilities into supply chain software promises to revolutionize forecasting accuracy. Machine learning algorithms analyze enormous volumes of data to identify patterns and make predictions that increase accuracy over time.

By analyzing historical data, machine learning algorithms can predict future demand patterns more precisely than traditional methods. These algorithms continuously learn and adapt to new information, allowing manufacturers to optimize their operations and improve performance.

This capability allows manufacturers to anticipate fluctuations in demand better and adjust their production and inventory levels, minimizing waste and ensuring customer satisfaction. You can learn more here about the capabilities of machine learning and other technology forces in our Smart Manufacturing Software Buyer’s Guide.

Dial in Accuracy in Your Forecast

If your forecast is like that lousy GPS that says, “Go that way…for a while,” or if your data is like drinking from a firehose with no ability to take it all in with manual tracking, Plex Supply Chain Management Software has the tools to help you gain control over your data, optimize your operations, and generate highly accurate forecasts using real-time data.

Plex also offers advanced machine learning technology to solidify a strong digital foundation further. The introduction of machine learning capabilities to the Plex Manufacturing Cloud enables manufacturers to harness the power of artificial intelligence to improve their forecasting accuracy even more.

Contact us to learn more about Plex Supply Chain Management software and the exciting features machine learning can offer to give you precise control of your data.

About the Author

Plex DemandCaster Supply Chain Planning

Since joining forces with Plex, by Rockwell Automation, in 2016, we’ve harnessed the power of its Smart Manufacturing Platform and industry knowledge to offer a digitized supply chain planning product. It seamlessly unites your business from the plant floor to the executive suite. To learn more about how we are bringing the Connected Enterprise to life across industrial enterprises, visit rockwellautomation.com.

Plex DemandCaster