More than four out of ten (43 per cent) of senior decision-makers at mid-market discrete manufacturers identified artificial intelligence (AI) among technologies likely to have the greatest impact on supply chains over the next three years, putting it well ahead of other innovations like the Internet of Things (31 per cent) and blockchain (24 per cent). That’s according to a recent independent study commissioned by advanced technology solutions and services provider, Delaware.
Nearly half (47 per cent) of the research sample named ‘to reduce costs’ as a top reason for innovating or making changes to their organisation, while 42 per cent cited ‘to drive operational efficiencies and productivity’. Yet, many manufacturers remain ‘behind the curve’. 75 per cent are not using AI in their supply chain today, while 74 per cent are not taking advantage of machine learning. That is something that will need to be addressed as these businesses focus on how they can best use technologies to drive the recovery from COVID-19.
The technologies most widely used by manufacturers were Internet of Things (35 per cent) and robotics-based automation (29 per cent) but levels of usage of innovative technologies overall were low across the board. More than half (55 per cent) of the research sample still manage their assets in a primarily or fully manual way, with only nine per cent operating with a fully automated approach.
“Given the impact of COVID-19 on their operations and their supply chains, in particular, it is key that manufacturers use new technologies proactively to fuel their fightback from the pandemic, and enable them to move positively into the future,” said Richard Seel, managing director (UK & US) at delaware. “As the recovery gathers pace, manufacturers will urgently need to look at how they can best make use of AI and machine learning to deliver operational efficiencies, optimise processes and achieve competitive edge.”
The study found, over a quarter (27 per cent) of discrete manufacturers still use ‘old school’ methods like ‘conducting surveys into consumer buying behaviour’ or ‘collecting patterns on buying patterns by analysts or industry experts’ to forecast demand when sourcing raw materials at the beginning of their supply chain.
“It is also concerning that 77 per cent of manufacturers we surveyed revealed that the data they derived from across their supply chain was not ‘completely accurate,’” added Seel. “Data accuracy will be key in delivering supply chain efficiency through the recovery. Also, given the disruption caused by the pandemic, supply chain visibility will be increasingly key to manufacturers to understand the risks they face to continuity of supply and how best to alleviate them through improved forecasting.”