Electronic components distributor Avnet oversees supply chains for major corporations, but more importantly, the Phoenix-based multinational leverages intelligence insight from its data to help understand what’s important for customers to move product for maximum profitability.
“Everything we do from an AI standpoint helps to fulfil that philosophy,” says CIO Max Chan. “Leveraging AI means cleansing data so customers can make the right decisions.”
With over 100 years of history to look back on, Avnet has always been able to prioritize technological investment as its ecosystem has grown more complex. Fundamentally important is adhering to what’s most important to the business. “Instead of having my own technology or approach to digital AI, the strategy is how do we enable the business,” he says. “So every capability we have, we look at technology, digital enablement, and AI transformation to help accelerate, redesign, or reimagine them. It’s all about helping to transform the business.”
Of course, ROI from AI can be elusive, but Chan sees missteps or flawed strategies as evidence oflooking at the wrong place. “Some people look for ROI from an investment in AI itself,” he says. “It’s like the traditional ways of looking at FinOps, for instance, to look at how much you’re spending, improving, and making out of it. We look at it differently. To us, AI is transformational, so when we implement something with AI in mind, we look at what business outcome are we hoping to drive. We get the right pricing and a more complete quote to the customer to help them learn what that converts to in terms of top and bottom line.”
But just like everything else regarding technology investment or digital enablement, success comes down to change management and governance. “Change management is key, but the overall governance of going back to whether something is contributing to a business outcome, or is directly supporting a business strategy, is essential,” he adds. “Otherwise, people will look at different POCs and use cases. We’re only looking for what directly links to strategic capabilities and the business outcome we’re looking for.”
Chan also details modernizing legacy systems with greenfield architectures, and partnerships that build resilience and customer value across industries. Watch the full video below for more insights, and be sure to subscribe to the monthly Center Stage newsletter by clicking here.
How AI helps distribution: We see very strong leverage in the sales enablement site, engineering design, managing inventory and forecasting, and orchestrating the supply chain. The common thread across all these areas is the actionable insight and data we have. So from a sales enablement perspective, what comes to mind is quoting, which is the most important thing as a distributor in terms of being informed and passing that on as quickly as we can to customers. For them, they’re able to get their products at the point they need. For us, we’re able to win the business and improve conversion. AI has helped us with pricing, getting the right information on end of life and country of origins, and putting it all together so the customer can make the best decision for what they do. It’s also about how we can help our customer service agents have readily available information to advise people. So we use it internally and externally.
On the heavy lift of legacy systems: This has been a long journey we’ve been on. Avnet continues to reinvent and apply the same mentality to modernize with technology. Over 30 years ago, we decided we wanted to go to a major ERP to run everything, but within the last 10 years, we realized that such a monolithic environment isn’t good enough. So we started building, just like everyone else, to get benefit from cloud transformations and build on top of it. But what my team and I quickly learned was that wasn’t going to cut it. We had support from the organization to start from scratch, and build a modern architecture that’s digital and AI first, which allows us to leverage different capabilities. The mentality of continuous improvement, and not to get hung up on what we’ve built over the last 30 years, has helped us with that success in driving AI and the transformation we see today.
On the changes AI brings: It comes back to the culture and learning agility we want everyone in the organization to have. Interestingly, AI is probably a lot easier than most other technologies that came before it because of ChatGPT, gen AI, and the many different tools that suddenly came up in the last few years. Everyone got excited. Trying to create that learning pathway, and getting people systematically upskilled to be able to approach and leverage AI the right way, is what we’re doing across the organization. We see it like there are three different types of AI to grapple with. One is productivity tools like ChatGPT that we give people to do what they need to do. The second is what comes with all the software you have, since all major software comes with AI components. Then last are the things my team would develop and build in accordance with what we want in order to drive the company forward, and how we transform. So we have more than enough tools that we allow the organization to leverage, and we have a governance process to request what people can use, or we give them an alternative. If it comes with the software we own, if we already have the license, then go for it since it’s embedded and will help us better leverage the software. The focus we have on AI is what we’re doing to transform the way we work, the workforce, the work itself, and in some cases, the business and how we can better serve our customers and employees. One way is reimagining some end-to-end processes to see if they can be fully autonomous. If so, what would it look like? Once that’s done, we bring people back in the loop to augment it and make it even more powerful for our business.
On AI impacting workflows: As far as disruption and resiliency from a supply chain standpoint, focus is on relationships with customers, both upstream and downstream, and understanding what they are, what they have, what they need to do, and what they want to do. And the signals we send around the industry help strengthen that resiliency. We get asked how can we help avoid the next supply chain debacle, and it comes down to partnerships, availability of data, and connectivity. In order for us to do that internally, from a tech stack standpoint, we need to target the modern architecture that drives microservices and allows us to have strong API connections. We created a platform called the Partner Digital Exchange, which helps bring data downstream, and combines it with what we have to drive orchestration. And that allows us to bring AI into the mix and help customers with the information they need. It also helps Avnet create that stickiness in the ecosystem.
Read More from This Article: Ways AI proves its worth at Avnet
Source: News