According to new data released 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."