Five Keys to True AI Breakthrough

Last week, 200 supply chain leaders gathered at Zero100 Live in San Diego to get into the details of how AI is changing operations today. It was not a futuristic dream fest of cool tech and ambitious goals, but instead a remarkably grounded, consistent story of getting the basics right while moving fast and scaling dramatically better supply chains.??

Guest speakers from every industry shared detailed stories of how they are transforming supply chains to be faster, better, more resilient, and more adaptable. What stood out most, however, was that they all said essentially the same things about how they’re doing it. All are: ?

• “Productizing the data” to feed powerful AI applications,??

• Building “fusion teams” comprising both operations and IT people, and??

• Thinking about business and operations strategy two or three moves ahead.?

To Have and To Have Not?

The good news is that we may have consensus on what needs to happen with people, process, and technology to truly unleash the power of AI in supply chain. We also know, based on extensive data analysis, how much better the supply chains of digital leaders perform. They grow revenue twice as fast, earn 440 basis points better margins, win more patents, turn inventory 80% faster, are more accurate with EPS guidance, and even lead on decarbonization.??

It’s clear that winners are pulling away from the pack. How, specifically, are they doing it? The worry for any who have not begun to productize data, build fusion teams, and think strategically is that they will fall ever farther behind.?

A Five-Point Winners’ Formula?

Zero100 has analyzed over 4 million data points and thousands of use cases to isolate five organization-level capabilities that are essential to success when it comes to AI for supply chain:?

1. Systems Thinking - A systems thinker knows how to surface issues and symptoms of deep systemic structures and patterns. They draw up a holistic view of the entire system and identify leverage points that, if altered, create a more efficient, cohesive design.??

For example, while seeking to reduce production costs by a whopping 50%, Tesla saw a leverage point in a design simplification that was easy but powerful. The product development and production teams leveraged marketing sentiment analysis to eliminate the sunroof with no offsetting loss in customer loyalty, enabling a massive simplification of the chassis and associated cost reductions.??

It’s not about working harder but working smarter.?

2. Learning Acumen – This means maintaining a culture of curiosity that breeds the skills needed to “pull” you toward the future.? Zero100 analysis of millions of job posts between 2022 and 2024 shows that mentions of some skills, like ERP and master scheduling, are declining by 25% or more. Others, such as AI, automation, coding, and change management, are increasing by more than 50%.

Unilever is one in a cohort of companies leaning in to build literacy and acumen on skills of the future through robust learning platforms –?one example being the recent Coursera Supply Chain Data Analyst Professional Certificate it made available to the broader population. Unilever is well ahead of its peers in terms of hiring for “citizen” digital skills, like AI/ML familiarity and data fluency. It’s also adding planners with “translator” skills, such as prompt engineering, LLM proficiency, and product management at 8.5x the rate of the average CPG company.?

Lifelong learning is essential to winning with AI.?

3. Change Mastery - Choreographing change to accelerate technology and process adoption starts with strong communication from the top. It includes facing the reality that work will be radically different, starting now. It also includes overcommunicating the value of future state, actively engaging stakeholders with authenticity, embracing objections and disagreement, fast tracking change champions (including early adopters/super users), and continuously pulse-checking progress.?

AI leader?PepsiCo,?for example, runs continuous pulse surveys for all major transformation initiatives and reports on stakeholder health as part of?quarterly?executive scorecard reviews. It also paints a compelling vision of the future state, creates and leverages super users, and engages key constituents continuously on the road to change.?

Change is here to stay. Leaders lean into it.?

4. Fusion Teams - Seamlessly connected teaming and workflows between IT and supply chain across disciplines is the key organizational building block of AI for supply chain. It is all about shifting away from a project mentality focused on installing software and the “go live” date and toward a product mentality that works backward from a user-focused outcome. Then, it’s necessary to stick with that mentality for the continuous iteration and lifecycle management of a tech product in business use.?

Haier, for example, has organized itself into self-managed teams accountable for not only developing tech but rolling it out, changing as needed to drive better performance, and building new product ideas that extend from its stable data and foundational systems of record. Not only does this improve tech product performance, but it also reduces bureaucracy.?

Teams need to be reimagined around the fact that tech and ops are merging.?

5. Future-Facing Tech – This means a three-tiered tech stack that takes full advantage of the user interface revolutions that are possible with genAI, an emerging set of autonomous agents, and robots. It also enables heavyweight adaptive simulations and optimization to drive dramatically better decisions based on huge amounts of descriptive problem data. All of this sits on open, scalable platforms comprising of system-of-record foundations, like ERP or PLM; extensible data lakes for outside-in data; and a sensing network gathering machine, POS, RFID, and social media data.?

Colgate-Palmolive is an example of this approach, balancing careful attention to a stable and scalable systems and data foundation with a portfolio of exploratory investments into more advanced capabilities like AI optimization and simulation. Colgate’s continued stock price outperformance is consistent with the differentiating impacts we are seeing in the data among AI leaders more broadly.?

AI demands a new tech stack, and leaders are building it now.?

Zero100 is continuously measuring and correlating behaviors of more than 300 global consumer and industrial brands. And our data shows that these five capabilities, when exercised together, create massive competitive separation. It’s up to leaders now to seize the moment.?