Unilever: Opportunities in the white spaces

Nespresso, the global leading brand in portioned coffee, is facing an existential threat. The company’s current market base, which consists primarily of aging consumers, is likely to decline in the medium to long term. To compensate for the certain shortfall, the company needs to attract young coffee drinkers among Millennials and Generation Z, whose consumption and values are significantly different from the current base. Management is being forced to reset its historically successful strategy for a new era when today’s young consumers will soon account for the bulk of the global coffee market.

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No company can grasp the potential of AI until it has set up a data-driven culture enabling employees to create value from the insights that emerge from data analysis. This means that before setting up an AI strategy, organizations must transform and prepare their infrastructure and culture for the AI age. This case study discusses the initiatives developed and rolled out by Marianne Galvin, initially Head of Data Office and then VP of Digital Transformation, as she worked to turn Civilia Engineering into a data-driven company. The case explores what Marianne put in place over her first 22 months with the company. This included: Governance structures and an educational program that proved to be highly popular. As the initiatives took root, Marianne and her team began to gain acceptance of use cases and dashboards for data-driven decision making but there were still several challenges to overcome, in particular how to work with an IT team more focused on architecture and improving legacy systems. The case closes as Marianne looks ahead to 2024, outlining what still needs to be done to gain digital and data maturity. The case provides a comprehensive understanding of the critical aspects of building a data-driven organization, particularly focusing on the interplay between value, data, and people. Through this case, learners will develop a nuanced understanding of the three pillars that sustain data-driven organizations, how to create a data-centric culture, how to avoid pitfalls in data-science projects and the nuances of digital transformation in non-digital organizations. They will be equipped with the knowledge and skills necessary to effectively lead and contribute to the building of data-driven organizations, fostering an environment that embraces data-centric decision-making and successfully navigates the complexities of digital transformation in an increasingly data-driven world.