Inbound Logistics | January 2024

Fearless Forecasts We’ll get tired of AI claims Expect AI exhaustion and a return to old- school evaluation. Rather than relying on the mere claim of being AI-enabled, companies are expected to showcase their capabilities and provide clear reasons for belief, signaling a return to a more traditional approach in purchasing decisions. –Donald Hicks, Founder, Optilogic Reshoring and friendshoring remain on whiteboards Investing in the development of strategic suppliers in nearby and/or politically friendly countries—reversing o shoring or sourcing from geopolitical rivals—seems like a sensible sourcing shift. It is generally easier to manage suppliers in neighboring time zones, creating an expectation of more reliable performance. However, challenges to this shift abound. Developing a strategic supplier entails high costs. A new strategic supplier also comes with quality, reliability, and overall performance risk while it climbs the experience curve. Even if it’s a success, the transition will be bumpy. While the old supplier will be indispensable during this lengthy transition, managing a long-time partner who sees the end of the road is a tough job. The outgoing supplier also presents a strategic risk. Will a competitor get an important boost by partnering with them? Finally, a lot of supply chain risk resides in lower tiers. Switching suppliers does not necessarily free a company of its existing lower-tier risk. In fact, it will probably remain dependent on many of the same links. With so many concerns, it’s unlikely many companies will drastically change their sourcing network in 2024. –Andrei Quinn-Barabanov, Senior Director, Supply Chain Risk Industry Practice Lead, Moody’s Analytics Truckload freight rates surge Driven both by an accelerated exit of surplus truckload capacity and a soft landing in the U.S. economy as inflation corrects below 2% while avoiding a painful recession, spot U.S.

Tp uply han o-D’s 1. R rn i  e  2. Es  f‚ƒ„ r† 3. B‰Š‹ pŽ‘’“‘s” 4. MŽ— ˜uš t‚ƒœ ž r ƒ’Ÿ¡ p¡‘’¢¡£i¡ 5. P‚”‚ ¦o¨ dšªži¡

manner should follow a responsible AI framework based on these six principles: Unbiased design – Identify and address inherent biases that may arise from the composition of your development team, data practices, and training methods. Resilience – Guarantee the security of data used by AI system components and the algorithm to safeguard against attacks and breaches. Explainable – Provide complete clarity on the AI’s learning methods and decision criteria. Aspects should be thoroughly understood and documented. Transparency – Provide appropriate notification to users, clearly identifying their interaction with an AI system and allowing them to select their level of engagement. Consistent performance – Ensure the AI’s outcomes align with company stakeholder expectations. Training and education – Employ proper training and communication for your workforce for easy deployment and operations. The pace, scale, and adoption of GenAI tools into supply chain operations aren’t like anything the industry has seen to date. Supply chain executives must accelerate adoption within their organizations and networks to remain competitive— but take caution and put the right governance, due diligence, and policies into place for success over the long term. –Ashutosh Dekhne, Supply Chain and Operations Leader, EY Americas


Rviw eslinc ivetmnt Realign resiliency investments to target the most business critical supply chain risks. Businesses may need to react to supplier geopolitical risks by diversifying their supplier base, which potentially raises procurement and management costs. Similarly, maintaining higher inventory levels as a bu er against supplier financial performance risks can tie up capital. Businesses need to consider not just the financial costs of their supply chain strategies but also the potential risks of di erent sourcing and inventory decisions. This requires a nuanced understanding of their supply chain ecosystem and a willingness to invest in risk management strategies that may not yield immediate financial returns, but will contribute to long- term stability and resilience. By utilizing a value at risk (VaR) approach, businesses can ensure that investments in resiliency are directly tied to risk appetite and focused on areas with the lowest risk tolerance. –John Donigian, Senior Director, Supply Chain Strategy, Moody’s Analytics Eta lih n A famwok Start with a responsible AI framework. Supply chain executives looking to integrate GenAI in an e ective, ethical, and eŸcient


continues on page 126

124 Inbound Logistics • January 2024

Powered by