Research Preview May 29, 2024

The Ultimate Guide to AI ROI

What Supply Chain Leaders Can Learn from Warren Buffett

AI has the potential to revolutionize supply chain. But with so much hype, so many opportunities, and just 25% of leaders seeing tangible returns, where should you actually invest to see the most – and fastest – AI ROI? Our latest report tackles the issue head-on in the form of an AI investment playbook inspired by the stock market wisdom of Warren Buffet and backed by Zero100 research and analysis.

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Matt Davis

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In 2007, Warren Buffett bet a million dollars that, over the course of a decade, a simple S&P 500 index fund could outperform hand-picked hedge funds. Ted Seides, a hedge fund manager from Protégé Partners, took him on and confidently picked five funds-of-funds.

The outcome? Buffett triumphed – decisively.

In fact, Seides conceded early because there was so little hope of closing the gap, with Buffet’s modest index fund outperforming his fancy funds-of-funds by 90%.

Buffett’s win reaffirmed his lifelong conviction that making money on the stock market “does not require great intelligence, a degree in economics, or a familiarity with Wall Street jargon.”

“What investors then need instead,” he once wrote, “is an ability to both disregard mob fears or enthusiasms and to focus on a few simple fundamentals."

Today, mob fears and enthusiasm for AI are peaking which, not unlike investing, can lead supply chain leaders to make rash, regrettable decisions. But Zero100 recently surveyed 312 supply chain leaders (including nearly 100 chief supply chain and operations officers) as part of our annual AI survey, and a surprising relationship came to our attention. Supply chain organizations that are more mature in their AI strategy embody an investment philosophy well aligned with the one Warren Buffett has followed for decades.

Zero100's AI Investment Principles

  1. 1

    There’s No Substitute for an Early Jump on AI

    Warren Buffett is the sixth richest person in the world, with a net worth of $136.1 billion, much of it accrued as compound interest. Buffett knows that making an early investment, staying the course, and watching it grow is more valuable than waiting to see what others will do.

    To get going on your AI journey, and quickly, simplify your objective by asking: what does my organization need most from its supply chain? Then, define how you’ll measure the success of your AI strategy and ROI – when executives don’t see quantified value from AI, they’re less likely to continue to invest in it.

  2. 2

    An AI Strategy Should Be Holistic, Not Hype

    When deciding whether to invest, Buffett isn’t concerned with the popularity of a company. He’s concerned with how well that company can make money as a business. In the report, we’ve applied this logic to AI investment.

    Map your AI maturity to get a sense of where you are now and consider where there’s AI white space (Zero100’s AI Blueprint is intended for exactly this exercise). Then, make your vision tangible, working to reach AI implementation.

  3. 3

    Invest in Widening Your “Protective Moat” to Build Competitive Advantage

    When sizing up investments, Buffett scrutinizes a company’s “protective moat” – any hard-to-copy characteristics that provide a competitive edge. We can’t give you a crystal ball, but we’ve singled out a few opportunities that are likely to enhance your protective moat and deliver a high return over time.

    For example, you might go all in on genAI or compare LLMs with SLMs to understand which best serves your objectives.

  4. 4

    AI Investment Is a People Investment

    Buffett once said, “By far the best investment you can make is in yourself.” The same could be said for your workforce: our data science teams found that those who lead on AI hiring in supply chain have twice the rate of revenue growth than those less aggressive on AI recruitment.

    Ramp up hiring for the digital skills you need, but also invest in upskilling and skills exchange. Additionally, adopt a learning mindset yourself – you’ll give your team members permission to do the same.

  5. 5

    Trust Is like Interest – Without It, Your AI Investment Won’t Grow

    Every year, Buffett sends an annual letter to the shareholders of his holding company, Berkshire Hathaway. He writes the letter as if he’s talking to his two sisters, both of whom are shareholders who are not very involved in the business. Through this approach, Buffett prioritizes transparency, shared understanding, and trust over sounding impressive.

    AI Leaders are prioritizing these values, too. Demystify AI within your organization by openly discussing its purpose, capabilities, and limitations while also setting up guidelines around usage. Regularly review, update, and communicate these policies to maintain trust and look for ways to encourage AI engagement and experimentation.

  6. 6

    Flawless Feedback Loops Are More Important than Flawless Data

    Data management is the number one barrier to AI success across industries. Though AI models are only as smart as the data used to train them, part of the challenge comes down to perfectionism. As Warren Buffett would point out: “Opportunities come infrequently. When it rains gold, put out the bucket, not the thimble.” Imperfect though your data may be, this moment calls for a bucket, not a thimble.

    Address the data problem by building dedicated supply chain IT teams. This requires taking stock of the resources in your organization today and specifically considering who owns (or should own) elements of data engineering, analytics, data science, and even data management.

As Andrea Albright, Executive Vice President, Sourcing at Walmart and Operating Partner at Massmart, writes in the report foreword, those who don’t invest in AI today may regret their inaction tomorrow. The challenge lies in differentiating fantasy from reality to guarantee ROI. To that end, the full report shares specific actions leaders can take right now to move from talk to results, supported by Zero100 research, data, and case study analysis.

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