Plutoshift: manual processes limiting value of data in manufacturing

Report says real-time analysis needed to make instant, actionable decisions and improve efficiency.

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PALO ALTO, CA, MARCH 4, 2019 — Manual processes and slow digital transformation within the manufacturing industry are inhibiting professionals from utilizing data to improve efficiency and processes, according to a new report.

The report by Plutoshift, a performance monitoring solution for industrial processes, shows that nearly half (48 percent) of manufacturing companies use spreadsheets or other manual data entry documents. As a result, only 12 percent are able to take action on their data insights automatically.

The report, The Challenge of Turning Data into Action, is based on a survey of 500 mid-level manufacturing professionals.

Manual processes, like spreadsheets and standalone solutions, are still used to collect and analyze data, creating inconsistent data, causing cost overruns, and imperiling regulatory compliance. Additionally, error-prone manual methods are causing mistrust in the data collected with 37 percent of respondents saying they can't take action on company data due to a lack of trust in the accuracy of that data.

To help mitigate these issues, more than three-quarters of manufacturing professionals (76 percent) identified software solutions that allow them to analyze data in real-time as a top solution. Over half of companies rely on other solutions like creating more efficient ways to communicate updates to people on the line and software that can be integrated with other systems so all data and information can be viewed in a single platform.

"The amount of tools available to transform the manufacturing industry grows every year," said Prateek Joshi, CEO and founder of Plutoshift. "But the ability to keep accurate and up-to-date reports on the performance of processes is paramount. Manufacturers are struggling with this endeavor, despite the myriad of tools available. They need simple, reliable solutions to surface insights of their data at the right time and to make actionable, proactive decisions."

Other key findings from the report include:

  • 28 percent didn't know if their company is collecting Industrial IoT data via remote sensors
  • The risks of not being able to react automatically to data insights are lack of process improvements (65 percent), lower response time in informed decision-making (60 percent), and Increased waste (59 percent).
  • The top four types of data collected are quality assurance (67 percent), operational efficiency (64 percent), labor time (63 percent), and cost of materials (63 percent).

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