Last week I gave a short presentation at a breakout session of the Industry of Things East World event in Orlando. This podcast is a recap of the talk done in a slightly different style. As the fourth speaker in the afternoon surveying the audience, I switched styles to one I hope kept everyone awake.
I wanted to talk about data. Why we collect it. How we can use it. And good management practices. All in fewer than 20 minutes. Allowing time for a decent discussion at the end.
My response to automation and robot dystopian writers is that for the most part these technologies have removed humans from dangerous and monotonous manufacturing work. Humans are freed to do things using their heads as well as their hands. This report from A.T. Kearney and Drishti further contradicts hype about accelerating factory automation; demonstrates the need for greater investment in the human workforce.
According to new data released today by A.T. Kearney and Drishti, humans still perform 72 percent of manufacturing tasks. This data, from a survey of more than 100 manufacturing leaders, suggests that despite headlines about robots and AI replacing humans in factories, people remain central to manufacturing, creating significantly more value on the factory floor than machines.
Respondents also noted that there’s an almost universal lack of data into the activities that people perform in the factory. This analytical gap severely limits manufacturers’ ability to make informed decisions on capacity planning, workforce management, process engineering and many other strategic domains. And it suggests that manufacturers may overprioritize automation due to an inability to quantify investments in the human workforce that would result in greater efficiencies.
“Despite the prominence of people on the factory floor, digital transformation strategies for even the most well-known, progressive manufacturers in the world remain largely focused on machines,” said Michael Hu, partner at A.T. Kearney. “This massive imbalance in the analytics footprint leaves manufacturers around the globe with a human-shaped blind spot, which prevents them from realizing the full potential of Industry 4.0.”
While manufacturing technology has seen increasing innovation for decades, the standard practices for gathering and analyzing tasks done by humans – and the foundation of holistic manufacturing practices like lean and Six Sigma – are time-and-motion study methodologies, which can be directly traced back to the time of Henry Ford and have not been updated for the digital age.
“The principles underlying these 100-year-old measurement techniques are still valid, but they are too manual to scale, return incomplete datasets and are subject to observation biases,” said Prasad Akella, founder and CEO of Drishti. “In the age of Industry 4.0, manufacturers need larger and more complete datasets from human activities to help empower operators to contribute value to their fullest potential. This data will benefit everyone in the assembly ecosystem: plant managers, supervisors, engineers and, most importantly, the operators themselves.”
Additionally, the survey respondents noted the significant overhead needed for traditional data gathering methodologies: on average, 37 percent of skilled engineers’ time is spent gathering analytics data manually.
“Humans are the most valuable asset in the factory, and manufacturers should leverage new technology to extend the capabilities of both direct and indirect labor,” said Akella. “If you could give your senior engineers more than a third of their time back, you’d see immediate gains. Instead of spending so many hours collecting data, their attention and capabilities would remain focused on the most critical decisions and tasks.”
The survey also revealed the flip side of human contributions to manufacturing systems: Survey respondents noted that 73 percent of variability on the factory floor stems from humans, and 68 percent of defects are caused by human activities. Perhaps as a result, 39 percent of engineering time is spent on root cause investigations to trace defects – another manual expenditure of time that could be greatly reduced with better data.
“The bottom line is that better data can help both manufacturers and human operators across the board,” said Hu. “Data illuminates opportunities for productivity and quality improvements; simplifies traceability; mitigates variability; and creates new opportunities for operators to add even greater value. Humans are going to be the backbone of manufacturing for the foreseeable future, and the companies that improve their human factory analytics are the ones that will be best positioned to compete in Industry 4.0.”
To view the full report, click.
A.T. Kearney is a leading global management consulting firm with offices in more than 40 countries.
Browsing LinkedIn, something I seldom do, I saw this image from a company called Seebo. “Where IoT Projects Fail.” Interesting, but can’t these be summed up in a word or two?
Try “management” or “leadership”.
The recurring theme I’ve found in my consulting and qualification process for a client concerns not really understanding what Internet of Things (IoT) means. Nor do they always understand realistically what benefits could accrue. Or what technologies fit.
A client one time hired me to justify a decision already made—in their minds at least—about acquisitions that would enter them into the IoT market. Another looked for use cases and settled on one not understanding the complexity of that use case.
On the other hand, a wise CTO once explained to me about themes for the company’s annual conference. One year might be IoT and another digitalization. He said they looked at the current themes in the market and then figured how their products fit, and presto—a theme.
If you are in an IoT project or contemplating one as a user or looking at a product and service plan as a supplier, step back and try using good basic management first. Organizing, defining, staffing.
Here is the list from the image:
- Failure to capture business opportunities
- Unclear and incomplete use cases
- Systems are too complex to communicate
- Missing critical data
- Unable to extract actionable insights
- Unable to identify root cause of product malfunctions
- Ensuring market-fit and early buy-in
- High cost of mistakes
- Prototyping products not technically or financially feasible
- Skills or capacity gap
- Aligning and syncing teams
- Detailed and complete spec docs and keeping them up-to-date
Companies are adopting Lean manufacturing with increasing frequency. And that is a good thing. A Lean culture is people-friendly, not to mention profit friendly. And thus the story of a GE Brilliant Factory award winning plant.
GE has around 400 manufacturing locations. It has had a contest to find the “most brilliant of the Brilliant Factory” plants in its system. I had the opportunity to interview Rob McKeel, CEO of GE Automation & Controls, whose plant in Charlottesville, VA was one of the 17 chosen from 400+.
Manufacturing Day was last Friday, but we need to continue to promote the importance of manufacturing and production throughout the year so that we can attract our fair share of the best and brightest young people into our industry.
McKeel told me the theme is digitizing Lean manufacturing. The plants are using the advantages of GE’s tools. Different plants chose different problems to tackle. The A&C factory in Charlottesville, VA was chosen as one of the “Most Brilliant of the Brilliant Factories” by meeting its goal to reduce cycles—lean out inventory turns.
The biggest challenge was changing the culture to really become Lean. The worker at the line really owns the results in Lean. Everyone around them has the function of supporting the line worker. On Gemba walks, the line leader presents the situation for that line and then asks for help. Help is given immediately.
Here’s a video that GE created about its Brilliant Factory in Charlottesville.
The second thing is to apply technology. Some technologies used included robots, augmented reality, and visualization to provide data in real time.
“We have a very different plant from 25 years ago—mostly due to tapping the energy of the people,” stated McKeel.
I asked how they went about transforming culture. He told me that first the plant manager went to Toyota to study the Toyota Production System. He took the “big” course. But everyone needs to understand. So then he had some team members took Lean training at Toyota. Then, walking the talk, showing the changes they wanted to effect. The first teams learned to react to worker problems quickly. That action and trust led to other questions. Main value is that the worker comes first, management and other team members support the worker.
Sounds to me like they used a basic method of creating trust. Without trust, you’ll never have a successful Lean implementation.
McKeel said, “We don’t have a single unproductive moment for the worker.”
A&C was awarded the GE Brilliant Factory of the Year for its leadership, people and manufacturing excellence. While four inventory turns per year has long been standard in the industry, the Charlottesville BF is pacing for 50 inventory turns in 2017 on its model product line.
The era of improving plant performance and profitability through efficiency—that is by cutting costs—is over. So stated Emerson Automation Solutions executive president Mike Train while kicking off the 2017 edition of Emerson Global Users Exchange in Minneapolis.
“The past 30 years have brought us fantastic advances in the manufacturing sector, including greater operating efficiencies enabled by automation,” said Train. “But the incremental benefits gained are diminishing. The pressure is on industry leaders to take the next step to the game-changing performance made possible by digitally empowering the workforce.”
Emerson has researched industry performance and drew a profile of Top Quartile industry performers – those in the top 25 percent of performance among their peers – Emerson has identified five essential competencies as critical to realize the value of “digital transformation”:
• Automated Workflow: Eliminate repetitive tasks and streamline standard operations to focus personnel on exceptions and other opportunities that require human intervention
• Decision Support: Leverage analytics and embedded expertise to provide actionable insights that reduce complexity and enable higher quality, faster decision-making
• Workforce Upskilling: Identify approaches that empower workers to acquire knowledge or experience faster and more effectively, to support higher-level and collaborative decision-making
• Mobility: Provide secure, on-demand access to information and expertise regardless of location, enabling collaborative workflows
• Change Management: Combine strategies, processes, tools and expertise that, in the right combination, simplify and accelerate the institutionalization of operational best practices
As always, this is a huge customer conference. There is abundant energy. Informal networking occurred all over the place. At this time, Emerson is the most vibrant of the companies in this area. It’ll be interesting to watch how, or if, business continues to grow from the company’s continued vision of industry.
More coming. Gotta listen to the next speaker.