Lalo Luna, global head of strategy and insights at Heineken, is a man on a mission. Having developed a range of data leadership skills at blue-chip businesses, his priority now is to use that knowledge to help the brewing giant make the most of emerging technologies and the treasure trove of information the company holds.
“We have a mantra here in the insights team: ‘Learn, share and reapply’,” he says. “And these are the basic pillars for everything that we’re doing.”
Luna has been with Heineken since March 2018, having previously been with Colgate, Palmolive and Mondelez International. He started working for the company in Mexico, before moving to Amsterdam during 2020. Luna has been in his current role since April 2023.
“I was looking for a bigger challenge – and this is a big company,” he says, thinking back to his move to Heineken. “We have powerful global brands, but the company also has more than 1,000 local brands. We have a pretty decentralised business and we need to take that into consideration in our work.”
Luna says decentralisation is a crucial element of the broader organisation’s structure and his team’s efforts to make data available to line-of-business employees.
“Our global brands are very well structured and information travels faster,” he says. “But when you are talking about local brands, everybody’s working at the local level. So, we need to work in these two realities. We need, of course, to start sharing more – we need to reuse, to learn, and to reapply. And it’s a huge challenge working across this size of company.”
As global head of strategy and insights, Luna describe his role as consultative, where he acts as a role model for the organisation and establishes strong data-sharing principles. His aim is to help the rest of the business develop strong data skills.
“Part of this work is to develop capabilities in the teams,” he says. “That effort includes everything related to tools and solutions that could help us to make the research process easier and better. On a day-to-day basis, I’m helping the teams to use global frameworks and trying to raise the ceiling in terms of the insights we’re creating.”
Luna says one of the things he initiated when he first took on a global role three years ago was to create a brand-new insights ecosystem. He says this ecosystem uses software-as-a-service (SaaS) technology and Stravito’s enterprise insights platform to offer simple yet robust digital solutions to the data challenges the rest of the business faces.
“We’re trying to embed all this technology in the research process,” he says. “The development of this ecosystem is the most transformational work that I have been doing here at Heineken.”
Today, Heineken is using Stravito’s technology to share insights through an internally branded platform, known as Knowledge & Insight Management (KIM).
Heineken recently launched a two-year Evergreen Strategy for its business that’s focused on the creation of a consumer-centric mindset across the organisation. Luna says KIM is a core component of this strategy and the platform democratises access to data, making it easier for internal users to get hold of key insights quickly and effectively.
“When we’re talking about the embedding of technology, we can now be faster into the market,” he says. “We are reducing the times for the research process. But another key benefit is savings – and not only savings in terms of money, but also in terms of the time of the people who work for our company.”
Luna says his team’s data strategy and their implementation of KIM means employees spend more of their working day thinking about how to use insights to improve business processes, such as internal operations or customer experiences. The approach also helps ensure insight is shared globally and not hidden away locally.
“We’re focused on insight democratisation, which we are promoting by using all these tools now because we are centralising knowledge,” he says.
“We are trying to create harmonisation around the world. And, at the end, we are able to share knowledge to democratise all these learnings, not only in the insights community, but also across the business.”
Luna says his team has a series of priorities. The first element is to think carefully about how the business can use data to respond to macro-economic challenges, such as high inflation in the post-Covid age.
“We’re doing a lot of research around the world,” he says. “When it comes to capabilities, we are still looking at how we can embed more technology in the process. That’s about trying to jump fast into AI, generative AI and all these developments that we are seeing in the market right now. So, we are very busy and trying to understand what tools could be helpful.”
Luna recognises that staying one step ahead of macroeconomic and technological change is a big challenge, particularly given the scale of the business, which includes more than 90 operating companies around the world.
“We need to reuse, to learn, and to reapply. And it’s a huge challenge working across this size of company”
Lalo Luna, Heineken
“As I mentioned, Heineken is very decentralised,” he says. “The global team needs to be able to act as a consultant with the market. We need to convince them and we need to influence them in many, many ways. So, it’s not an easy task, but the tough times we’re in require a lot of effort.”
Luna’s preparatory efforts in terms of cloud-based applications and insight management platforms means that many of the digital systems and services are already in place. In many ways, it’s a familiar refrain – technology is the simple part. The real challenge comes from ensuring everyone around the business understands the value of data.
“As I always say, it’s about cultural change,” he says. “We are partnering with senior stakeholders in this journey because, as with any other change programme, it needs to start from the top. In this type of big organisation, we’re going to need stakeholder support. And fortunately, we have partners that are helping us to spread the word around our business.”
The key message, therefore, is that Luna has heavyweight support for his continued efforts to make the most of data. While some blue-chip enterprises might fear being left behind by the rapid pace of change due to fast-emerging technologies, Luna and his team are being encouraged to keep pushing their insights-led approach to digitisation.
“As part of the Evergreen Strategy, there are some iconic objectives for us related to data. As a data analytics function, we are collecting all this information. The long-term aim is to embed all this knowledge into the decision-making process, and that’s why we have a lot of stakeholders supporting this journey.”
In the first 12 months since going live, Luna says KIM has reached 1,300 users, 30% of whom log in and use the platform every month. Every day, people around the world are logging in to find research and are sharing and reusing insights.
Stravito announced recently that it has added a proprietary generative AI engine to improve the search experience on its platform. Luna says these kinds of developments will help his team to keep refining their approach.
“Our journey to build these insights and develop a best-in-class technology ecosystem is an ongoing effort,” he says.
“The plan is to make KIM the living heart of this ecosystem. We want to work with all our platforms to think about how to maximise the benefits of AI. How can we start using generative AI and allow people to digest the information in thousands of reports easier?”
With new developments relating to AI appearing every day, it can be tough work – even for an experienced data leader like Luna – to keep pace with the technology market. However, it’s a challenge he relishes.
“For me, from now on, it’s going to be all about how we can stay updated and relevant,” he says. “New technologies and new solutions are competitive advantages. So, it’s very clear that the companies that are adopting technology as part of their key strategic pillars are now performing better.”
Luna says the really successful data leaders will focus on delivering simplification in challenging times. Smart companies will use the tools at their disposal to translate disparate enterprise information into simple, clear recommendations.
“Now, with generative AI, we’re going to have tools that provide simple ways to digest all the qualitative and quantitative data information,” he says. “So, making sure our people get enough information is, for me, crucial.”