Supply chain professionals spend nearly two full days a week manually tracking data, as revealed by a new survey conducted by LeanDNA and Wakefield Research. The report sheds light on the challenges executives face in leveraging technology to optimize operations and prepare for disruptions.
The findings highlight a significant gap between supply chain executives' intentions to invest in proactive management (92%) and the reality that a large percentage (76%) still don't have a predictive view of supply and demand. This discrepancy underscores the need for advanced analytics tools to help executives make informed decisions and mitigate risks.
“In a rapidly evolving market, this inefficiency points to a significant loss in productivity and a barrier to effective day-to-day decision-making,” said Richard Lebovitz, CEO of LeanDNA. “There’s also grave concerns about their ability to prepare for the next major supply chain disruption.”
When COVID-19 reached its apex in 2020, the supply chain descended into chaos. Four years later, executives are making every effort to prepare for the next disruption. Among the worries looming over supply chain leaders are supply shortages (56%), public health crises (52%), natural disasters (50%), government regulations (49%), cyber-attacks (49%), and geopolitical conflicts (45%).
These concerns demonstrate the need for better data and proactive strategies to mitigate risks and ensure operational resilience.
Preparation for the next disruption, however, is easier said than done. Many supply chains have resorted to holding excess inventory to weather another major disruption. However, this approach does not generate the resiliency organizations need and may undermine it. As a result, nearly all (96%) supply chain executives say their organization is under at least a little pressure to balance preparedness for a major disruption and avoid excess inventory.
While most executives agree that supply chain disruptions are a major concern and that embracing AI and other automation is the solution, many companies have yet to implement any substantial changes. Gina Chung, Vice President of Corporate Development at Locus Robotics, notes organizational roadblocks prevent the widespread adoption of these changes.
“Supply chains are highly complex environments with many interconnected systems, making technology upgrades difficult,” Chung said. “There is inertia and resistance to change, as revamping processes requires upfront investment. Plus, a current lack of technology skills/literacy in the workforce impedes the adoption of new solutions. Companies have also been hesitant to retrain or hire specialized roles.”
While there's no doubt automation will enhance efficiency, companies need to be smart with their investments. According to Capterra’s 2024 Tech Trends Survey, 58% of U.S. businesses regret at least one software purchase they’ve made in the past 12 to 18 months and 23% have made multiple regretful purchases.
This often leads to drained IT budgets, hampered employee productivity, and decreased competitiveness within their industry.
It's also prompted companies to rethink their decision-making process. ”'The way we do things,' including when buying software, can be hard to change in any organization,” says Brian Westfall, principal analyst at Capterra. “However, the fact that most U.S. businesses are making regretful purchases points to flaws in how they find and evaluate software. Software investment is going up in most cases in 2024, and this creates an opportunity to right past wrongs.”
A study published by Gartner’s Dwight Klappich predicts that by 2027, over 75% of companies will have adopted some form of cyber-physical automation within their warehouse.
That’s not to say there aren’t success stories already. Companies like FedEx, DHL, Target, and Walmart are leveraging AI-enabled supply chain innovation to optimize operations.
Locus Robotics has successfully automated the warehouse operations of several companies including Carhartt, which uses LocusBots to ease the physical burden of employees fulfilling orders in a massive warehouse. “From the very beginning, we've been developing and implementing cutting-edge AI and robotics solutions,” Chung says. “This applies to elements such as our navigation stack, pick density optimization, optimal path planning, and more, providing autonomous optimization and predictive analytics for intelligent warehousing.”