Supply chain leadership in an age of upheaval
Volatility, technology, and talent are reshaping supply chain management....
Supply chain
Why generative AI is set to transform supply chain management
Supply change managers have a track record of making adept use of artificial intelligence technology, argues Carlos Cordon of IMD, but generative AI represents a potential step change.
Supply chain leaders were early adopters of artificial intelligence (AI) technologies when AI-powered tools first became available a few years ago. Now they look set to embrace generative AI solutions with similar enthusiasm. While this technology is in its infancy, supply chain managers are already eyeing a broad range of applications as large language models such as ChatGPT proliferate.Ā
The key will be to build on existing successes. So far, deployments of AI and machine learning tools have focused on areas such as demand forecasting and logistics management tasks such as route planning optimization. These technologies have augmented supply chain professionalsā experience and expertise. The results have often been impressive. Research from McKinsey suggests AI-enabled supply-chain management has enabled early adopters to improve logistics costs by 15%, inventory levels by 35%, and service levels by 65%.Ā
Going further with generative AIĀ
Now, however, there is an opportunity to use generative AI to go further. Harnessing the ability to derive insight from ever larger pools of data, and to express that output in much more user-friendly mediums through a range of different forms, rapidly evolving generative AI tools have multiple potential applications for supply chain teams. The bottom line is that generative AI not only interrogates existing information but also creates new content.Ā
Advances in demand forecasting are a good example. Generative AI tools now make it easier to run multiple what-if scenarios that test likely levels of demand in the event of different circumstances ā including potential adverse impacts that the organization had not previously considered. These tools can also suggest a range of potential responses to the outcomes of these exercises, making it much easier for the organization to head off potential risks or to grasp opportunities.Ā
In that context, generative AI offers the promise of optimizing inventory levels, production schedules, and logistics with far greater accuracy than in the past. Managers have the advantage of working with detailed risk assessments and event scenarios, presented in narrative form rather than through a traditional data dashboard or a spreadsheet.Ā
New use casesĀ
However, as well as improving existing technology deployments, generative AI also offers the chance to innovate in new areas of supply chain management. In the field of procurement, for example, generative AI solutions could revolutionize the way organizations work with key suppliers. The US retailer Walmart, for example, is reported to be using a chatbot that automatically negotiates costs and purchasing terms with some of its smaller suppliers.Ā
With larger suppliers, meanwhile, generative AI can be used to extract key information from contracts, analyze the natural language outputs of such partners, and assess performance. The potential is for a stronger and more transparent relationship with such suppliers ā and the ability to identify efficiencies and improvements that alternative suppliers might be able to offer.
āThe US retailer Walmart, for example, is reported to be using a chatbot that automatically negotiates costs and purchasing terms with some of its smaller suppliers.ā
Elsewhere, some companies see an opportunity to drive improved internal performance too. Providing their own production data, for example, manufacturers can train generative AI models to identify the biggest productivity and efficiency improvements and to head off outages with predictive maintenance. This will support increased levels of automation.
In logistics, meanwhile, there is also growing excitement about the potential of generative AI. Leaders in the field, including Amazon, have already begun introducing advanced automation in their warehouses; smart robotics is part of the picture, but AI is also used to optimize picking routes and to drive better inventory and asset management so that fulfillment centers are used efficiently.
The race for advantage
Interest in all of these areas is ramping up, with technology providers racing to establish their credentials, or looking to M&A to secure proven expertise. One good example of the latter is the recent purchase of the German software business risk methods by Sphera of the US. Launched in 2013, riskmethods was an early pacesetter in the race to build supply chain solutions leveraging AI. Its software scans real-time data from sources globally to identify potential risks and threats to usersā supply chains so that they can take early action to mitigate the danger.
Sphera, which specializes in technology linked to environmental, social, and governance (ESG) issues, recognizes risk methodsā ability to help companies monitor sustainability practices and ESG compliance in the supply chain. This is another significant area of opportunity ā the potential is for generative AI tools to support stronger ESG risk management across each link of the supply chain.
Indeed, the German industrial conglomerate Siemens already works with Scoutbee, a Berlin-based startup, which last year launched a chatbot that responds to requests to locate alternative suppliers or vulnerabilities in the userās supply chain. That could prove valuable as Siemens seeks to reduce its dependence on Chinese suppliers amid rising geopolitical tension.
Itās not only technology providers that are exploring strategic investment. Users of these tools are also exploring capital opportunities. The shipping giant Maersk, for example, played a key role in the $20m fundraising last year at Pactum, which has developed a bot that negotiates contracts on behalf of Maersk and other businesses.
Will AI take your job?
Still, with so many different use cases for generative AI, some supply chain professionals are worried about their jobs. After all, analysts from Morgan Stanley predict that āAI may be able to totally (or nearly) remove all human touchpoints in the supply chain including āback officeā tasks.ā One recent poll by Freightos found that almost a third of supply chain professionals believe the adoption of generative AI tools will lead to significant job losses.
āThe shipping giant Maersk, for example, played a key role in the $20m fundraising last year at Pactum, which has developed a bot that negotiates contracts on behalf of Maersk and other businesses.ā
Possibly, but such fears may be overdone. For one thing, previous rounds of transformation of supply chain technology, which also prompted predictions of job losses, do not appear to have had this effect. The widespread adoption of Excel spreadsheets by supply chain professionals, for example, reduced the need for manual data crunching but increased the scope for analysis.
There is good reason to think history will repeat itself. New research from the International Labour Organization argues that generative AI is likely to create more jobs than it destroys because the new tools will be complementary to many existing elements of work, rather than replacing them already.Ā
In other words, supply chain management functions may be standing at the brink of opportunity. Itās worth noting that unlike in other professions, supply chain leaders have yet to identify a standard piece of software that supports the way their staff work. There is, for example, no supply chain industry equivalent of the customer relationship management (CRM) packages now ubiquitous in sales.Ā
Maybe generative AI is about to change that. Freightosās poll found that while only 14% of supply chain professionals are currently using AI tools, 96% have plans to adopt them. This could be the technology that changes everything.Ā
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