Lean Solutions Group, a leading freight brokerage firm, has experienced remarkable growth over the past few years. The company's employee base has expanded from approximately 700 individuals in 2018 to over 10,000 today, with operations spanning across multiple countries including Colombia, Guatemala, and the Philippines. This rapid expansion can be attributed to the company's ability to offer cost-effective solutions to freight brokerages by relocating back-office functions to nearshore labor markets where the economics made more sense. By doing so, Lean Solutions Group was able to provide a 40% cost arbitrage that initially drew brokerages to its services.
However, as the industry continues to evolve, clients are now pushing for even greater savings - up to 60% or 70% - without disrupting their operations. To meet these demands, Lean Solutions Group is shifting its focus towards artificial intelligence. While AI has gained significant attention in recent times, many experts argue that it's essential to understand the 'real stuff' behind AI implementations.
The company's CTO, Alfonso Quijano, emphasizes that logistics is a highly fragmented and varied industry, making it challenging for any single AI product to serve a broad customer base without customization. In fact, Lean Solutions Group previously supported over 180 distinct job functions across the transportation and logistics sector, many of which were tailored to specific workflows by individual brokerages.
This fragmentation is a significant challenge for AI-first solutions from outside the industry, as they often struggle to accommodate the diverse needs of various customers. According to Quijano, each customer requires some form of customization that can break wide-scale product adoption.
Lean Solutions Group's experience with early-day rival brokerages who demanded firewalled networks, branded workspaces, and siloed SOPs to protect their operational identities mirrors this competitive tension. Similarly, AI deployments now face a similar instinct from clients, who require tailored solutions to effectively adopt AI.
The company has developed a playbook for one of the most significant change management implementations in the industry, having worked with numerous workforces. They have gained valuable insights into how people work and how workflows need to adapt to successfully implement AI.
However, Quijano is cautious about the limitations of large language models in logistics operations, particularly when companies attempt to deploy fully autonomous AI workflows. He notes that these models still struggle to make high-quality judgment decisions, which can lead to undetected errors cascading throughout the system.
The impact of such errors can be severe, as seen in a common-sense failure where an AI chatbot advises someone to walk to a car wash rather than drive the car that needs washing. This anecdote highlights the need for more sophisticated AI solutions that can navigate complex logistics operations.
As Lean Solutions Group continues to adapt to industry shifts, it's essential to acknowledge the importance of understanding the nuances behind AI implementation in logistics. By doing so, companies can develop more effective solutions that meet the diverse needs of their customers and mitigate potential errors.
s are taking note of Lean Solutions Group's approach to AI implementation.
