Creating Strong, Scalable Production Teams With Analytics
Numerous studies have demonstrated how analytics will change manufacturing quickly over the next three to five years. Manufacturers leading the adoption curve know that having their teams engaged, owning the analytics app development, customization and launch will determine if the many efforts to bring analytics online will succeed or not.
- 68% of manufacturing executives are investing in analytics apps including Manufacturing Intelligence to streamline plant-floor operations, become more customer-driven and grow revenue.
- 46% of manufacturers agree that analytics are a must-have application and skill set today to stay competitive.
- 32% are planning to capitalize on the evolving area of the Industrial Internet of Things (IIoT) and Big Data to solve their most urgent supply chain, shop floor coordination and quality challenges.
These and many other findings are from a recent Honeywell survey, Data’s Big Impact on Manufacturing: A Study of Executive Opinions. The survey was jointly conducted by Honeywell Process Solutions (HPS) and KRC Research Inc. More than 200 North American manufacturing executives took part in the study.
People And Teams Are the Most Vital Catalyst Of Analytics Success
Getting the shop floor teams to buy into analytics and see dashboards as their own, reflecting their team’s accomplishments sets a strong foundation for ongoing improvement.
You can sense this ownership when you walk through a manufacturing plant and talk with team members during breaks. They immediately tell you how what they are doing fulfills customer requirements. The word customer comes up a lot in these conversations. And in manufacturing centers doing customization including build-to-order work, names of customers and the reasons for their unique requirements are common knowledge throughout production teams.
To the team members on the shop floor, analytics can become a way of keeping score on how well they are excelling at serving customers.
Making the numbers move in the right direction is seen of as more of a challenge than management micro-managing performance. That’s what drives great analytics programs, the team members on the shop floor take ownership of outcomes and drive them in a positive direction.
Based on working with manufacturers on their adoption of new analytics and manufacturing workflow apps, here are the key takeaways for improving the probability of success for analytics programs:
1. Rely on the expertise of team leaders and members in defining how the data are driving the analytics will be collected, using which approaches, and how often.
The goal of early involved with team leads and members is to provide them visibility into what’s getting measured, why, and how they will be able to stay in control of the factors impacting the data captured. Giving production teams completely visibility into how data is captured, aggregated and reported gives them ownership and infuses trust into the process.
2. Give team leaders a few weeks to work on the dashboard designs and requirements with their teams and use their suggestions in system design.
One of the best ways of accomplishing change management programs with employees is to give them a voice in how the dashboards and screens they’ll be working with daily can best be designed to meet their needs. With large-scale analytics implementation there are often many different groups and teams involved. It’s important that the teams whose progress is getting measured and reported have a chance to design the screens that report progress – as they’ll be creating reports and using them to monitor their progress daily too.
3. Pilot analytics reporting for 30 – 45 days and provide production teams a chance to experiment and see how they can make small changes to workflows to drive up performance.
Often during pilots entirely new findings will emerge from data collected. It’s common to find slight areas of improvement that teams can take on fast and improve performance. Give the teams the freedom to do this and get a sense of ownership over the process and the data. Give teams a chance to review pilot data before it’s presented to senior management so the production leads know what is going to be reported. They can also help in providing analytical insight into how performance gains can be made as well. One project manager invites in production leads to senior management reviews to present pilot results. She’s found this cuts down on action items for her team and given the production leads strong ownership over the analytics program succeeding.
4. Once a pilot is complete decide which specific measures of performance will be reported on the manufacturing-wide reporting flat screen monitors seen on the shop floor.
In the best-run manufacturing plants the culture is one that embraces measurable feedback. It’s often because the team leads and their teams had a chance to own the outcomes of the analytics as they were being implemented. The large flat screen monitors in these types of manufacturers flash the most customer-centric metrics the plant operates from. Often these metrics are chosen between senior management, plant management, and team leads. Owning the figures and being committed to improving them is the sign of a successful analytics and Manufacturing Intelligence program.
