Process Analytics

Process Optimization Software Industrial enterprises use many processes to support their operations. From asset lifecycle management to maintenance management to everyday workflow processes and operations, there are myriad processes transpiring at any given time. Because these essential processes help keep businesses afloat, it makes sense for enterprises to analyze them to improve future performance.

This is where process analytics comes into play. By consolidating data about primary processes into a digestible, easy-to-understand format, process analytics help enterprises see firsthand just how efficient—or inefficient—their current processes are. Consequently, businesses can adjust their processes as needed to ensure optimal performance in the future.


What is process analytics?

Process analytics involves capitalizing upon process-related data to analyze and improve future process performance. Process analytics integrates real-time data to help enterprises analyze the current processes they have in place to determine whether they are delivering optimal results.

 utilizes process analytics to make this information accessible and digestible so companies can easily understand past and current process performance and consequential outcomes.

However, understanding process performance is just one component of process analytics. Process analytics also helps organizations identify tangible ways to improve current processes to maximize results. By using predictive and prescriptive analytics, companies can make more informed, data-driven decisions to improve future results.


Optimizing processes across industries

Process analytics can be implemented across a wide variety of industries to help improve core processes and accelerate productivity. Here are some examples of the many ways process analytics helps optimize processes across specific industries:

  • Pharmaceuticals - Pharma analytics helps enterprises in the pharmaceutical industry gain data-driven insights to optimize drug development and production, risk management, and operational efficiency while staying in compliance with federal and industry regulations.

  • Power Generation and Distribution - Using data analytics for utilities, electric utility enterprises can gain insight into asset utilization and performance to anticipate equipment failure and prevent outages. Enterprises can also use process analytics to assess power quality and make improvements as needed.

  • Manufacturing - Companies in capital-intensive industries can use process analytics and predictive maintenance software to anticipate equipment failure and prevent unnecessary downtime. These insights can be used to improve maintenance management and optimize asset performance throughout the equipment lifecycle.

Process analysis is a valuable tool that many industries can use to enhance productivity, reduce downtime and setbacks, and achieve better outcomes over time. Performance data helps businesses make smarter decisions to continue delivering optimal results to customers and yield higher profits.


Process analytics features

Virtually any industry can benefit from process analytics to identify areas of improvement. Some features of process analytics include:

  • Descriptive analytics gathers historical data so enterprises can gain insight into past patterns and trends and understand how these impact current performance.

  • Predictive analytics examines past performance trends and insights to predict future performance. Enterprises can use insights gleaned from predictive analysis to make data-backed decisions to improve future processes.

  • Prescriptive analytics builds upon predictive analysis by making data-driven recommendations on next steps that businesses can take to ensure better performance in the future.

Process analytics serves as a versatile and powerful tool that capital-intensive businesses can use to make smarter business decisions. By integrating data-backed insights into business strategies, organizations can optimize processes to deliver lasting and high-performing results.



What is process analytics?
Process analytics uses real-time data to analyze process performance and offers insights as to how to improve current processes. Process analytics can be implemented across a wide variety of industries to optimize business processes, including food and beverage manufacturing, pharmaceutical manufacturing, packaged goods and more.

What are the three types of business analytics?

  • Descriptive analytics involves examining the past — past performance, past occurrences that affected performance, and how these factors currently impact the business. Simple mathematics, charts, and graphs are often used in descriptive analytics to analyze past business performance and generate company reports.

  • Predictive analytics builds upon descriptive analytics by using historical data to predict what will happen in the future. Predictive analytics analyzes past trends and patterns to make data-driven conjectures about future performance. Unlike descriptive analytics, predictive analytics involves more complex mathematics to calculate probabilities and statistical outcomes. Special tools such as predictive maintenance software for industrial enterprises may be necessary to better anticipate future equipment downtime.

  • Prescriptive analytics takes things one step further by examining insights gathered from descriptive and predictive analytics and using this to make recommendations for future business strategies and processes. Organizations can capitalize upon prescriptive analytics to make intelligent business decisions that will improve future performance. Prescriptive analytics often involves machine learning and process optimization software to reliably generate insights that businesses can use to make future decisions.

What are business process analysis tools?
Business process analysis tools are tools that leverage process analytics to help businesses improve their core processes. One key example of a business process analysis tool is process optimization software, which allows businesses to gain data-driven visibility into process efficiency and outcomes. Organizations can then use the insights gleaned from this data to make smart business decisions to ultimately improve performance.