Report: 82% Of Supply Chain Managers Using AI Systems For Decision-Making Left Frustrated During COVID-19 Pandemic

Report: 82% Of Supply Chain Managers Using AI Systems For Decision-Making Left Frustrated During COVID-19 Pandemic

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By citiesabc resources

Secondmind report reveals potential for AI and human collaboration to strengthen supply chain resilience

Secondmind, The Decisions Company, today released new research indicating that 82% of supply chain decision-makers have been left frustrated by AI-powered systems and tools during the COVID-19 crisis. Secondmind commissioned independent global research firm Censuswide to survey over 500 supply chain planners and managers across Europe and the USA to learn how AI was helping or hindering their decision-making.

The results, released in a new report, show that despite the frustration, belief in AI’s potential is strong - 90% agree that AI-powered tools and software will help them make better decisions by 2025 and over half (59%) strongly agree that AI will transform supply chains for the better in the next five years.

The blockers to fulfilling AI’s potential

The managers surveyed cited a number of factors hindering the ability of AI systems to deliver value, all of which fell into two categories:

• Data: a lack of reliable data to feed into AI systems (37%), historic data becoming ‘meaningless’ in times of unprecedented change (19%) and the need to spend significantly more time on manually analysing and interpreting data (50%) were concerns at a time when accuracy and speed were of the essence.
• Organisational: a third of respondents (34%) said their leadership teams lack an understanding of what is currently needed on the ground to make faster, data-driven decisions. Furthermore, rigid processes and internal structures prevented over two in five planners and managers from quickly responding to changing market conditions (41%).

A longer road to resilience

The supply chain planners and managers surveyed believe that a third of their time (on average 2.83 hours daily[3]) is spent on manual tasks that could easily be automated. As frustrations with current AI systems emerged during the pandemic, half (50%)[4] said they spent significantly more time manually analysing and interpreting data to assist strategic and operational decisions.

The decision-makers surveyed stated these data pain points are holding them back from working on higher value initiatives that could contribute towards building more resilient supply chains, such as:

• Proactively preparing scenarios and plans for future unexpected ‘black swan’ events (30%)
• Spending more time on proactive and in-depth planning for major events such as Christmas and Black Friday (41%)
• Conducting more in-depth analysis, using their experience and expertise (51%)

The power of human & AI collaboration

The majority of managers who use AI systems want their domain expertise to factor into the decision-making process. Desirable capabilities for AI systems included: the ability to modify AI-generated forecasts using the decision-maker’s own judgement ( 53%), AI that can learn from humans when historic data is unreliable (47%) and AI that could show what data or contextual information that impacted a forecast (39%).

Of those who believed AI alone was not enough to inform effective decision-making, the reasons cited were that human intuition cannot be replicated by a machine (62%), there will always be some events that a machine can't predict (59%) and expertise developed from years on the job is critical in decision-making (51%).

Vishal Chatrath, CEO and Co-Founder, Secondmind comments: “COVID-19 has been a wake-up call for businesses operating in global supply chains as they prepare to rapidly accelerate the implementation and deployment of AI in the coming years. For AI to realise its potential, it will be critical for organisations to deploy systems that can cope with sparse or incomplete data environments and promote the effective collaboration between people and AI. Our report shows how much people benefit from AI, but also how much AI needs people. A collaborative approach to decision-making that combines the right skills and capabilities for each task is essential, particularly when systems are disrupted during uncertain times and unpredictable events.”

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