Globally, more and more industrial robots are being deployed as part of manufacturing processes. Despite this, 72% of all work is still performed by humans. Despite fears that robots will cost many jobs, people remain central to the production process. Not surprisingly, as people have proven to add more value on the shop floor than machines.
These are some of the results of a survey conducted by A.T. Kearney and Drishti among 100 manufacturing industry leaders. Respondents reported having little insight into the activities of their human workers on the production floor. This lack of insight prevents companies from making informed decisions in areas such as capacity planning, workforce management, process engineering and in other strategic areas. "Think back to the last time you got a recall call for your car," says Anik Bose, general partner at Benhamou Global Ventures. "The car manufacturer recalls thousands or millions of cars for something that is probably just a minor problem. However, since they are unable to trace this problem back to specific factories, stations, services or VINs, they have to cast a wide net, while the cost is astronomical."
'Automation gets too much priority'
A.T. Kearney and Drishti argue that many companies give too much priority to automating manufacturing processes. "Despite the widespread presence of people in the workplace, digital transformation strategies for even the most well-known and progressive manufacturers worldwide are largely focused on machines," said Michael Hu, partner at A.T. Kearney. "This large imbalance in the analytics footprint creates a blind spot 'with a human form' for manufacturers worldwide and stands in the way of realising the full potential of Industry 4.0."
Many methods used to map and analyse tasks performed by humans are outdated, can in many cases be traced back to the days of Henry Ford and have not been renewed since then. As an example, Prasad Akella, CEO and founder of Drishti, cites lean and Six Sigma. "The principles under these 100-year-old measurement techniques are still relevant, but are too manual to scale up, produce incomplete data sets and are prone to observational bias," says Akella. "In the era of Industry 4.0, manufacturers need large and complete datasets on human activity to help operators add value to their full potential. Everyone in the assembly ecosystem will benefit from this data: plant managers, supervisors, technicians and, more importantly, the operators themselves."
How is data collected?
Respondents also indicated that collecting data in the traditional way is very time-consuming. For example, technicians spend on average 37% of their time manually collecting analytical data via time studies. 71% cite such information as (very) important to gain insight into their employee base. Data collected through Human Relations (HR) methods are also widely used. Despite the fact that this data is not very accurate, according to the researchers, 74% of respondents say they are more confident in this method (74%) than in collecting data via time studies (57%).
"People are the most valuable asset in a factory. Manufacturers should therefore use technology to increase the potential of both direct and indirect labour," Akella explains. "If you manage to give senior engineers more than a third of their time back, this translates into direct profit. Instead of spending hours collecting data, they can continue to focus their attention and expertise on the most critical decisions and tasks." Bose adds that differentiation is no longer about cost and capacity, but rather time-to-market and productivity. Employees can therefore be the biggest differentiators for an organisation, according to Bose.
'People provide variables'
Despite the fact that humans add a lot of value in the workplace, their presence also has negative consequences. For instance, respondents indicated that 73% of all workplace variables are caused by humans, while 68% of defects can be traced back to human activity. This is mainly due to people losing concentration, for example if they have had a bad night's sleep. Such problems are costly; engineers spend on average 39% of their time investigating the root cause of defects, amounting to 62 hours per month. With better data, this task can be done faster, allowing engineers to add more value.
"At the bottom line, better data helps both manufacturers and human operators," Hu said. "Data provides opportunities for productivity and quality improvements; simplifies traceability, mitigates variables and creates new opportunities for operators to add extra value. People are going to be the backbone of manufacturing in the near future. Companies that know how to perform better analytics on people will be best able to compete in Industry 4.0."
All research results are gathered in the report 'The State of Human Factory Analytics', which can be requested here.
Author: Wouter Hoeffnagel
Source: A.T. Kearney & Drishti
Source: report The State of Human Factory Analytics
Source photo: Pixabay / Martinelle
