Chris “Jay” Hawkinson is the Senior Director of Data & Analytics at Lamb Weston.
In today’s rapidly evolving digital landscape, data and artificial intelligence (AI) are no longer optional tools—they are essential drivers of innovation, efficiency and competitive advantage.
The question isn’t whether to adopt AI, but how. Think of it in terms of building the “Six Million Dollar Man”—meaning, enhancing capabilities requires careful oversight to avoid unintended consequences. Fortunately, there are plenty of insights to help businesses avoid said consequences.
Readiness depends on a few key factors, such as data quality, governance and ethical usage. While most companies are technologically ready, success depends on aligning AI adoption with robust governance and real accountability.
So, how should business leaders begin? To leverage AI effectively, start with the fundamentals: understanding and simplifying existing processes. It’s vital to identify inefficiencies before introducing AI. Otherwise, AI will simply help make mistakes faster.
AI is most impactful when used to identify process weaknesses and eliminate unnecessary complexities, such as redundant approval flows. The result: streamlined operations that enhance customer-facing value.
The next step is to select the right data analytics tools, which is not a one-size-fits-all approach. Since there are no perfect tools, it’s important to align them with your company’s maturity level and business objectives, while avoiding frequent switching.
Switching tools often results in lost productivity, so it’s best to prioritize maximizing the value of existing tools while maintaining long-term visibility. The goal is to give people access to the information they need as soon and as comfortably as possible.
In industries like consumer packaged goods (CPG) and manufacturing, data can be impactful or actionable—but it’s not always both. For example, supply chain visibility is crucial for long-term strategy, but inventory movement data often provides the most actionable insights in the short term.
It’s important to remember that good data drives actionable decisions, in any industry. Focus on data that is both high-quality and within the company’s control.
When it comes to measuring the success of implementing new tools and AI initiatives, keep this in mind: it’s not always about the bottom line. Business impact should be defined before implementation—and while some outcomes, like metrics, can be seen directly, others (like improving safety and reducing risk) aren’t as easy to track.
With sustainability being a core value at so many companies, including ours, it’s important to note that AI and data are vital in meeting sustainability goals. AI helps standardize and analyze sustainability data quickly, enabling actionable plans without months of manual human processing.
The key lesson for leaders is clear: Data and AI are tools for enabling better decisions, not just faster ones. The true value lies in using these technologies to drive long-term growth, improve efficiency and create meaningful business outcomes.
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