SEA: A $140 billion hidden Alibaba?

Choosing a CEO is a crucial decision for any company, but it becomes particularly complex in family businesses. This difficulty stems from the need...

Family businesses often have not only financial wealth but also nonfinancial values that make them different from nonfamily companies. For instance...

Leadership presence (LP) is widely acknowledged as a foundation of effective leadership. Historically, LP has been conceptualized as a collection o...

Observe and rethink until you find a pattern

With organizations of all sorts facing increased urgency and unpredictability, being able to ask smart questions has become key. But unlike lawyers...

IMD produces a yearly Smart City Index offering a balanced focus on economic and technological aspects of smart cities on the one hand, and “humane...

While a CDO can offer substantial benefits in steering digital transformation, fostering innovation, and achieving competitive advantage, organizat...

How IMD navigated the trade-offs when implementing the institution’s AI strategy.

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.

What does it mean to be excellent, not perfect, in 2024, and why should luxury brands weave the answer into their strategy?