GFL Is Said to Consider Sale of Stake in C$5 Billion Infra Arm
GFL Environmental Inc. is considering the sale of a stake in its infrastructure arm, people with knowledge of the matter said, in what could be one of Canada's largest infrastructure deals this year.
The company is seeking a valuation of as much as C$5 billion ($3.7 billion) including debt for the affiliate, known as Green Infrastructure Partners Inc., the people said. The stake sale is attracting initial interest from potential investors including General Atlantic, Energy Capital Partners and Neuberger Berman, the people said.
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Christian Hyatt is the CEO and Co-Founder of risk3sixty. As a cybersecurity expert, he has overseen more than 2000 engagements. If you've ever ordered a package online only for it to end up lost, you know how frustrating the experience is. You're left wondering where your package disappeared to, and when you contact the company, that team has to scramble to figure out the answer. The team often tries hunting down the missing package by searching the warehouse, reviewing the order system, contacting the carrier, etc. In the interim, they may not be able to give you a clear answer, and you might end up having to push them to get a reshipment or refund. Lost packages are one of the many examples of poor customer experiences resulting from the siloed, reactive and disconnected state of supply chains. Other examples of poor customer experiences include wrong packages being delivered, package tracking issues, a lack of control over how and when items are delivered and customer service that is not consistent and not personalized. However, AI can help companies tackle these issues. By leveraging AI, supply chain leaders have the opportunity to transform the customer experience. Why Many Supply Chains Still Haven't Caught Up To Consumer-Centric Thinking Many supply chains, I've observed, still haven't caught up to consumer-centric thinking. In my view, that lag stems from the historical B2B mindset in the supply chain world. Before Amazon, many of the stakeholders in the supply chain world were primarily geared toward serving other businesses. FedEx, UPS and DHL, for instance, started by serving businesses, not consumers. In the supply chain world, the B2B mindset prioritizes driving down unit economics as much as possible. And part of driving down unit economics? Offering standardized services, including a one-size-fits-all approach to the customer service experience. This tends to work well in B2B contexts but less so in B2C ones. For instance, when a business reports a missing package, it expects to work through standard channels to resolve the issue, such as filing claims and waiting for an investigation. However, when a consumer reports a missing package, they typically want an immediate response and a faster resolution. Research has shown just how much a good customer experience matters. A 2022 survey of 1,000 Americans by omnichannel solutions provider Mitto found the following: 'In the past year, 80% of respondents said they experienced at least one delivery delay. A majority (55%) of consumers have canceled a delayed shipment because of a bad customer experience. And when asked whether bad CX or a product delay is worse, over three-quarters (76%) of respondents indicated bad CX.' How AI Can Help The Supply Chain World Move Toward B2I To keep up with consumers' preferences, I believe the supply chain world needs to go one step beyond shifting to a B2C mindset—it needs to shift to a business-to-individual (B2I) mindset. An article in Strategy+business (s+b), an outlet run by PwC, put it well by stating that nowadays, whether organizations succeed is 'based on their ability to build and maintain lasting relationships with individuals.' B2I is personalization at scale. Achieving personalization has historically, overall, been a costly and friction-filled process. However, AI can help supply chain leaders create personalized, predictive and proactive customer experiences. Specifically, leveraging AI, leaders can bridge the gap between their customers and their supply chain systems, thanks to real-time tracking, personalized communication and automated issue resolution. For example, say you order a package from a company that uses AI to refine the customer experience. Your package gets lost. You go to the company's website and enter your tracking number. On the backend, the AI-powered technology can gather various data points, such as the carrier assigned to the package, geographic data and traffic conditions to determine what likely happened to your package. The AI-powered solution can also highlight your purchasing history with the company—you happen to have a high customer lifetime value, having made 100 different purchases in the past two years. With that information, the AI-powered solution can begin investigating the issue with your package and working toward the correct resolution. Simultaneously, through the AI-powered customer service interface, the company can send you an apology, acknowledge that it knows you're a long-time customer and offer you the option of either shipping you a new package or giving you store credit worth the value of the missing package. Moreover, it can adjust its communication style based on its inference of your preferences from past interactions. In turn, you, the customer, receive a more streamlined, friendlier experience that's likely to leave you with a good impression of the company. How Companies Can Navigate The Risks AI Poses AI, however, is not without its risks. Supply chain and other company leaders need to consider data privacy concerns, the potential for AI solutions to hallucinate and the possibility that their teams will misapply AI. Rather than viewing AI as an all-encompassing solution, supply chain and other company leaders need to carefully think through its limitations and risks and ensure they're in compliance with all applicable regulations. Additionally, given that implementation is often expensive and time-consuming, it's important that supply chain and other company stakeholders carefully think about the problems they're trying to solve, rather than focusing on potential solutions. By understanding the problems they're trying to solve, leaders can evaluate potential vendors through the lens of those problems and also evaluate whether they want to build their own AI solutions in-house. When it comes to the buy versus build debate, I recommend that leaders weigh whether they have the time and resources to build their own solutions and whether doing so would detract from their primary organizational more and more factors arguably become commoditized in the business world, I predict that in the future, reputation will be one of the strongest, if not the strongest, differentiators for companies. And in a world where a brand can be destroyed with just a single post online that reaches the right audience, it's vital that companies strengthen their reputations by offering great experiences to consumers. Despite the risks that AI poses, I believe it stands to help positively change the customer experience in the supply chain world—and by extension, help companies strengthen their reputations. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
