Supply chain executives are focused on reducing material supply risks and avoiding unplanned delays and outages in the year ahead, according to a survey by supply chain technology company Verusen, released earlier this month.The tech firm’s 2022 State of Supply Chain Management report surveyed executives at large global organizations about a range of issues and found that many believe they lack the resources and direction to meet supply management goals in the year ahead, especially when it comes to data and technology.
“Verusen’s 2022 Supply Chain Management survey reveals that poor data quality, outdated technology, and disparate data silos are the top three causes for inefficiency in supply chain executives’ materials management process,” Paul Noble, Verusen’s founder and CEO, said in a press release detailing the report.
Among the survey’s key findings, 80% of respondents said they cannot digitally track the movement of direct and indirect materials across their enterprise network, and 43% said a lack of visibility into inventory availability is keeping them from sharing critical materials with other facilities in their network.
The report’s authors say artificial intelligence-based tools (AI) can help centralize data and improve visibility into inventory, allowing supply chain managers to make better decisions.
“Supply chain executives are constantly faced with indecision due to the lack of visibility into their inventory availability. This indecision leads executives to make hasty decisions around direct and indirect materials data,” Noble also said. “However, this need not be the case, especially with new AI tools that can accurately generate guidance for actionable decisions across an enterprise supply network.”
Other survey findings include:
When asked about hurdles to a digitally transformed approach to materials management, 76% of executives pointed to disparate silos of materials data and lack of knowledge;
The #1 priority among respondents over the next 12 months is reducing supply risk for their materials;
More than 75% of respondents believe implementing an AI-driven Materials Management solution would take 12-24 months;
More than half of the respondents claim they need to expedite spare parts on a weekly and monthly basis to avoid production outages.