Why Nestlé put learning over knowledge at the heart of its talent playbook

In March this year, news broke that thieves had stolen 12 tons of KitKat bars during transportation from Italy to Poland.

It could have been a disaster for parent company Nestlé. But the result was quite different thanks to some quick thinking and risk taking by some of its marketing experts.

A real-time strategy was launched leaning into the brand’s iconic slogan ‘Have a break’, inviting consumers to take part in tracking the stolen merchandise and turning a potential PR nightmare into an award-winning marketing campaign.

Markus Graf, Corporate Head of Talent at Nestlé, believes the incident is a perfect example of how the food and beverage giant’s overarching talent strategy works in action.

“This team didn't have a playbook; they had judgment and the permission to read a new situation and act quickly,” Graf tells UNLEASH.

For an organization with 160 years of heritage, the new competitive edge isn't what people know; it’s how fast they can learn and make decisions.

Arriving as a learner to build a talent ecosystem at scale

Graf joined Nestlé in April this year where his remit spans the end-to-end execution of talent, leadership, capability building, culture and belonging. He “chose to arrive as a learner” rather than an expert.

Despite having prior HR leadership experience at organizations including Novartis and PepsiCo, Graf undertook “hundreds of conversations” across Nestlé’s businesses, markets, factories and R&D sites in what he refers to as “a very humbling experience.”

“For me, what worked was listening longer than felt comfortable, because I had this drive for action,” he explains.

“There was a kind of temptation to translate my previous experience too quickly into answers for Nestlé, but listening gave me an opportunity to ask better questions.”

Taking an initial position of curiosity and openness to learning meant Graf avoided the risk of “validating a strategy I may have already had in mind.” Instead, he experienced the flow of work across the organization firsthand without bias.

For an organization with the scale and diversity of Nestlé - comprising more than 30 billion-dollar brands - building a new talent ecosystem means starting with architectures rather than programs.

This structure is based on three core layers:

• Mindset – the “willingness to learn and work differently.”
• Skillset – the “capability to lean into business value.”
• Toolset – the “infrastructure you need to build in order to reach really 270,000 people with the learning offering.”

With hundreds of workers undertaking different capability-building work across the organization, Graf’s team functions at the center of it all; setting strategy, standards, governance and operating a common platform in Cornerstone.

Graf adds that it was important to start with the mindset, because technology only creates value when employees change how they work accordingly.

“The answer cannot be to always say we need a bigger learning department. It's about how you build an ecosystem to tap into what's happening.”“The answer cannot be to always say we need a bigger learning department. It's about how you build an ecosystem to tap into what's happening.”

Decision making at scale: Centralize the backbone, localize the work

The HR function at Nestlé works as a mirror of how the overall organization runs, by centralizing what “creates scale and coherence,” and localizing “what creates proximity to the work.”

A specific example of how governance works without just becoming a top-down mandate in practice is the Enterprise Learning Council, which sets the overall structure of learning programs throughout the business.

The Learning Council brings together representatives from the center, with others representing different markets and functions, with the system “intentionally designed so we bring these different perspectives together and make these choices together.” Everyone contributes to the decision.

“The goal is to standardize the backbone and outcomes while allowing for the relevant contextualization and the experience,” he adds.

For example, the R&D function will set its own priorities for skills and capabilities, while the HR function decides on the technology to use and how progress is assessed.

This strategy is also used to build AI literacy and competency across Nestlé. Instead of applying a blanket program to upskill all facets of the workforce to the same level, Graf explains that the target is “depth for the few and fluency for the many.”

He highlights the organization’s Marketing function as a specific example of how this works in principle, where Nestlé made a specific investment decision to raise the deep brand-building capabilities for thousands of its marketeers around the world, while building fluency for 30,000 people with a Brand Building White Belt.

The approach to AI follows suit: “We need a specialist group that needs deep technical expertise where we invest in depth. In the wider company, we need AI literacy and judgment. So that's what we offer across the board,” Graf says.

“The goal isn't AI expertise for everyone in depth, but AI judgment for everyone, so they know what to delegate, how to verify the output, and where a human must decide.”

What ‘over’ means for Nestlé’s learning strategy in the AI era

For an organization like Nestlé, it is unsurprising that talent priorities will pull in different directions.

When these tough decisions arise, Graf highlights one of the four cultural pillars at the organization: learning over knowledge, with a specific emphasis on ‘over’.

“We deliberately describe two positives in each case. Speed and perfection. Courage and comfort. Collaboration and consensus. Learning and Knowledge. Both are genuinely good,” he explains.

In practice, this means asking whether a decision is reversible, and if it is, favoring speed over perfection.

While the company does not compromise on safety, compliance, and quality, Graf also says that the organization will favor learning over knowledge, accepting the inherent trade-off.

“At the end of the day, this ‘over’ word is the thing that costs us. But, to some degree, if nothing is sacrificed, you have not really made a choice.”“At the end of the day, this ‘over’ word is the thing that costs us. But, to some degree, if nothing is sacrificed, you have not really made a choice.”

An example of this in action is how Nestlé reviewed its learning solution portfolio and found that half of the portfolio assets were not being used by workers. The result is an ongoing consolidation Graf describes as “not about spending less but spending where it counts.”

The emphasis on learning instead of knowing is “a massive shift” for the organization, but it also prepares Nestlé for the AI era where the stakes are higher.

In the AI-driven future of work, knowledge is “less likely to be a sustainable competitive advantage.” As a result, learning becomes far more valuable for organizations.

Graf points to “asking better questions, learning faster, testing assumptions, adapting and applying human judgment” as differentiators in this environment. He adds that the mindset/skillset/toolset model operates as “a catalyst for better and faster work and decisions.”

“In an AI-driven world, the winners will not be the organizations that know the most; it will be the organizations that learn fastest and apply the best judgment,” Graf concludes.