Originally published in Manufacturer, ARB’s Manufacturing Industry newsletter.
Manufacturers have long gathered and analyzed data to make strategic decisions about their manufacturing processes. This is nothing new. However, advanced data analytics can supercharge the process by turning vast amounts of operational data into actionable insights.
Manufacturers can capture real-time data across production lines using Internet of Things machinery and cloud computing. Advanced analytic tools can process this data to uncover patterns, predict outcomes and optimize decision making. This shift can allow manufacturers to pivot from reactive to predictive — and even prescriptive — strategies, often leading to greater profitability.
Manufacturing-Specific Processes
Here are some key ways your company can benefit from using advanced data analytics:
Timing preventive maintenance. In manufacturing, machinery is bound to break down — often at the worst possible times. But predictive maintenance systems allow you to anticipate and prepare for these events, minimizing downtime. These systems combine embedded sensors, artificial intelligence and advanced data analytics to gather historical information on hundreds, or even thousands, of parameters. This helps the systems identify and monitor the factors most closely correlated with breakdowns.
By anticipating when breakdowns might occur, predictive maintenance enables you to schedule maintenance for times with the least impact on your operations (at night, for example). You can also minimize downtime by having the necessary personnel, parts and materials on hand when you need them.
Identifying operating inefficiencies. Even if you’ve minimized or eliminated unscheduled downtime, other operating inefficiencies may be more difficult to detect. Advanced data analytics can reveal hidden inefficiencies and bottlenecks by examining hundreds of production parameters that affect efficiency and throughput and applying sophisticated modeling techniques.
Often, relatively simple adjustments to these parameters can help streamline operations and maximize your output. For example, you may eliminate bottlenecks simply by rearranging the plant floor or relocating often-used parts to be more accessible.
Gaining greater control over your supply networks. The pandemic demonstrated the devastating impact of supply chain disruptions. Using data analytics allows you to monitor and analyze a wide variety of internal and external factors that affect the performance of the supply chain. Examples include inventory levels, customer demand, economic and political factors, weather and road conditions, and supplier quality. This information helps you anticipate potential problems and formulate contingency plans to minimize their impact on your production process.
Enhancing yield. Advanced data analytics can help you identify opportunities to enhance productivity or yield. In many cases, these opportunities are hard to discern using conventional techniques.
For example, a chemical manufacturer used advanced analytics to measure the relative impact on yield of various production inputs, including coolant pressures, temperatures, quantity and carbon dioxide flow. The analysis uncovered some surprising relationships. Specifically, variations in levels of carbon dioxide flow caused significant declines in yield. By adjusting its production parameters based on this finding, the company reduced raw material waste by 20%, lowered energy costs by 15% and improved overall yield.
Likewise, pharmaceutical manufacturers can use advanced data analytics to optimize production. A major challenge for these manufacturers is often the variability inherent in botanical raw materials and manufacturing processes. Relevant factors include climate, fertilization methods, harvest time and storage conditions for raw materials. They must also consider variations in the manufacturing processes, such as heating or adding certain chemicals. Advanced data analytics can be used to adjust production processes to ensure product efficacy and quality.
Streamline All Areas of Your Business
In addition to the manufacturing-specific areas discussed above, manufacturers can use advanced data analytics to optimize other business processes. These include finance and budgeting, scheduling, marketing and customer service. Turn to your business advisor to learn more about how advanced data analytics can benefit your manufacturing company.
This publication is distributed with the understanding that the author, publisher and distributor are not rendering legal, accounting or other professional advice or opinions on specific facts or matters, and, accordingly, assume no liability whatsoever in connection with its use. ©2025
Manufacturing Team Spotlight
John Hadwen is a Principal at ARB. He specializes in providing individuals and businesses with comprehensive
tax compliance and consulting services related to closely-held business, manufacturing, construction & real estate, and professional services firm taxation. Prior to joining ARB, John was a Tax Principal at a large, regional CPA firm.
