In manufacturing, data is king. Peter Sondergaard, Vice President of Global Research at Gartner, aptly puts it, "Information is the oil of the 21st century, and analytics is the combustion engine." This analogy underlines the immense value of data but reminds us that without practical analysis, it's worthless. Data and analytics play a vital role in informed decision-making and business success in this data-rich era.

Challenges With Data in Factories

In the age of big data, the manufacturing industry finds itself at a crossroads. While the potential benefits of harnessing data are immense, several challenges must be addressed to unlock its full potential.

Data Deluge

Today, we produce as much data every two days as we did between the dawn of civilization and 2003. Each passing day adds to the deluge, making it challenging to manage and extract valuable insights.

Gaps and Silos

The 4th Industrial Revolution has seen increasing automation in factories with sensors on production lines feeding better real-time data. However, despite the tremendous amount of data being collected, many of the processes today that involve frontline workers are still being done on paper. Or in the best-case scenario, data is rekeyed into spreadsheets for at least some basic digitization. We must fully digitally integrate our workers, just as we have done with our assets. Doing so will bridge a crucial gap between data collection on the factory floor and our capacity to derive insights from it.

Data Collection vs. Presentation

Most industrial systems, such as ERP and MES systems, excel at data collection but often fail to present it meaningfully. This mirrors concerns raised by Peter Sondergaard about the disconnect between collecting and interpreting data. As a result, there's a burgeoning market for specialized reporting and business analytics tools, including Power BI and Tableau.

However, even with these solutions, senior business leaders frequently express dissatisfaction with the tools available to them for making timely, data-driven business decisions. The hunger for meaningful insights persists, emphasizing the need for improved data utilization.

Manual Data Handling

A significant hurdle is the tediousness of manual data preparation. The entire process, from rekeying data from paper forms into spreadsheets, to consolidating to analyzing data and then relaying results using spreadsheets or other manual tools, is not just time-consuming but also error-prone. Companies often spend more time tweaking the data than acting on it.

The Solution: Poka & Poka Analytics

Poka is a Connected Worker platform that helps you digitize your daily operations on the factory floor. Our digital forms and checklist capabilities ensure data from inspections, operational tasks, and reports are captured efficiently and consistently. A testament to efficiency, one manufacturer notes that filling out a form in Poka is 40% faster than a paper form. Moreover, data captured in Poka is instantly available to empower timely, actionable insights.

At its core, Poka Analytics is your gateway to a single source of truth for your data. It connects to your Poka data sources and empowers you to create and share insights through rich visualizations, interactive dashboards, and detailed reports.

Use Cases and Advantages

When applying Poka Analytics to your business, the use cases are virtually endless. The analytics solution covers both the Daily Management and Learning and Development (L&D) sides of your business. Here are just a few use cases that demonstrate its versatility:

Identifying inspection worst offenders
Detecting deviations in 5S checklists to pinpoint areas that need attention
Monitoring plant safety risks
Addressing team skill gaps

Analysis isn’t confined to the plant. Poka was designed with enterprise-scale operations in mind, so you can extend your analytics to corporate or HQ levels for a holistic view of your plant data. This way, you can benchmark plants to identify top or under-performers and identify areas for improvement.

The primary goal of data analytics dashboards is to provide decision-makers with the tools to visualize data and make data-driven decisions more efficiently. With Poka Analytics, you can gain valuable insights into production issues and workforce performance, so you can zero in on priorities that need corrective action.

Getting data from one system to another, without manual manipulation, mass pulls or corruption is still a bit of a golden goose hunt - valuable but elusive. Instead, reduce the time and effort it takes to extract insights from your production floor data by keeping everything within Poka, which is powered by its own internal analytics engine. This eliminates the need for third-party data integrations, eradicating the complexity and errors often associated with exporting and processing raw data.

Real-Life Examples: Customer Case Studies

Upfield: Health and Safety

Upfield's commitment to health and safety is exemplified through their adoption of Poka Analytics, driving transformative improvements. They introduced "safety care conversations"; follow-up conversations with staff based on an electronic form that is filled out anytime an unsafe act or behavior is observed. This digital shift replaced paper forms with streamlined data collection, offering real-time insights through user-friendly graphs, automated processes, and enhanced data accuracy. Analysis of the custom-made dashboard then informs what safety training needs to be implemented to reduce these newly identified risks.

For instance, if management notices a spike in unsafe conditions in a particular production line, they swiftly investigate the cause and take immediate corrective action. The ability to identify trends and make rapid, well-informed decisions decisions is the most valuable benefit for Upfield. “We make the call right away - why it's happening, and how to resolve it; because safety is the number one priority for every organization,” said Arif Khan, Continuous Improvement Specialist at Upfield.

Barry Callebaut: Training

With Poka Analytics, all plant employees and their corresponding skills are pulled from the Skills Matrix into a single, comprehensive dashboard. Previously, each team’s endorsements would have to be reviewed separately and pulled into a master pivot table, taking about an hour a week of manual data manipulation. Now, the information is automatically assembled and emailed out to supervisors, cutting the time down to 10 minutes a month - or as long as it takes to skim the chart. Barry Callebaut also uses conditional formatting to make important information stand out. This transformation significantly reduced the time needed for managing employee competencies, enabling skills quick gap analysis for supervisors and HR and pinpointing areas where further training is required.

Barry Callebaut: Quality Assurance and Food Safety

Another way Barry Callebaut utilizes Poka data management capabilities is to improve their Quality Assurance and Food Safety processes. Consolidating and treating their Foreign Materials data for a daily meeting was taking a staff member up to 20 minutes a day. The hangup was again getting the data into a third-party system for analysis. Associates would fill out a digital form noting who found the foreign material, where, what it was and what action was needed. In the multi-step process, the data was downloaded daily from Poka, compiled into a spreadsheet, and then fed into Power BI to be generated into a dashboard.

Now with the analytics engine integrated directly into Poka, even more comprehensive analysis can be done without an external Power BI connection. An automated email at 8 a.m. is sent to the responsible person, complete with all the relevant information in the Poka dashboard. “It saves a lot of time and it saves a lot of work. [The email] was easily done with all the information that we already had in the analytics,” said Ailana Pereira, Reliability and Continuous Improvement at Barry Callebaut. “Now they just have to check the email, see the information and then take it to the daily meeting”

Poka’s analytics capabilities proved invaluable in simplifying their workflow and enhancing data accessibility, making Quality Assurance and Food Safety processes far more efficient and productive.

Conclusion

The data deluge in factories is overwhelming, and the gap between data collection and interpretation remains a significant hurdle. Industry leaders like Upfield and Barry Callebaut have leveraged Poka Analytics to enhance their health and safety, training, and quality assurance. This transformation not only saves time but also empowers swift, data-driven decisions. Poka Analytics is proving its value as a versatile tool in navigating the data-rich landscape of modern manufacturing.

Want to learn more about how Poka can boost your use of data? Reach out to one of our experts today!

From Data Overload to Informed Decisions: Unleashing the Power of Manufacturing Analytics