Industry 4.0 is accelerating digital manufacturing and predictive analytics on the shop floor, much in the same way as the professional sports analytics revolution has allowed teams to do more pre-game planning and more real-time, in-game informed decision making on the field. As a manufacturer, do you have what it takes to build a winning team in Industry 4.0?
Queue the commercials, pile up the chicken wings and practice your best end-zone touchdown dances. The Super Bowl is one of the most anticipated sporting events of the year. But predicting who will win the championship is another story. It all comes down to the availability and analysis of data. Those of you familiar with Moneyball know that the MLB is a leader in data-based decision making, and the NFL is a laggard. NFL teams are just starting to utilize data to increase their chance of winning the game. They're backing up in-game decisions with data to answer simple, micro-level questions like "should we go for it on fourth down?" or, "kick the extra point or go for two?" These are adding up and resulting in macro-level performance for teams—strong playing records. Significant, relevant data is available at the fingertips of every team (player performance, play calling tendencies, situational analysis, etc.), but how it is utilized and interpreted varies.
The NFL isn’t the only organization using data to transform the way they work. The manufacturing industry is on the precipice of the fourth industrial revolution. After the lean revolution of the 1970s, outsourcing of the 1990s, and automation of the 2000s, manufacturing is now entering a phase of digitization with Industry 4.0, much in the same fashion as how sports teams transformed to a focus on data analytics in the 2000s. Data is already being generated and manufacturers can make a game plan to utilize the information and insights to think differently about how to execute day-to-day operations.
Like the NFL, the information collected throughout the production process can become a powerful tool with a little practice. However, not all companies are willing to put the time, effort, and understanding into how to best utilize it. If companies want to elevate their performance, they need to teach themselves or find data-savvy resources. Beyond just having the will to win through data analytics, manufacturing companies need to let go of their sacred cows. These are process, organization, and technology inefficiencies that prevent a unified, integrated flow of data ultimately reducing visibility into the production process. With Industry 4.0, manufacturing companies have been able to flip the script on operation excellence from historical reliance on lean or kaizen to a game-changing approach of using real-time manufacturing data to assist with predictive analytics.
Take the Chicago Bears for example, who during General Manager’s Phil Emery’s tenure (2012-2015) utilized data reactively to evaluate players based on past performance. Unfortunately, this result did not lead to much success, missing the playoffs in every one of those seasons. Compare the Bears to the Philadelphia Eagles who let analytics inform their decision-making in a predictive manner. They went for fourth down 26 times during the regular 2017 season—more than any other team in the NFL—and converted to a league high 17 attempts on their way to winning Super Bowl LII. These decisions were far from sporadic; they are calculated in advance of the game or in some cases the entire season by key decision-makers and data analysts on the management team. Much like reactive and predictive analytics in manufacturing, there are benefits to evaluating both and using these to get to peak performance.
Think of your staff, facilities and equipment as players in the game. Know their strengths, tendencies and weaknesses and what is the best plan of action in virtually every situation. Not sure where your focus should be? Can’t identify your own sacred cows? Bring in an outside perspective to build your game plan. The systemic trends and outcomes with the highest probabilities will always be found in the data.
A 6’6” 330lb offensive lineman seems like a great pick until you get him into his first game and realize he hasn’t read the playbook and has no idea what to do when the quarterback calls an audible. Implementing a new data solution and process without knowledgeable users has the same effect. If you can’t extract and understand the value behind the data, you can’t make good decisions. Recruit players that will challenge the status quo and can understand how to use analytics as a factor in the decision-making process; From data management and cybersecurity to the end-users on the shop floor.
Cross-functional partners will be key to winning the industry 4.0 Super Bowl. Collaboration and support between teams (finance, IT, R&D, sales, HR, procurement, manufacturing, and maintenance) will be needed to execute the changes needed at a technology, process, and organization level. Get them involved from draft day to the opening kick-off so that game-day execution is flawless. Do you have what it takes to win? If not, what part of your game plan is holding you back? Sources:
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