The AI conversation is almost entirely about value created and how to capture it. What if AI destroyed value? What do we lose when the technology is used at scale? Which are the second-order effects that don’t show up in any business case? And more importantly, what are the questions you should ask about your...
As part of the 2024 ESCP Impact papers series, my colleague Howard Zhong and I were happy to contribute with a piece pleading for augmentation over automation.
When it comes to sustainability, the Internet of Things (IoT) stands out as a beacon of promise and paradox. As we chart a course towards a more sustainable future, IoT technologies emerge as both a key ally and a formidable challenge. How to advance sustainability goals while mitigating environmental footprints in the age of IoT?...
Massive value can be created by leveraging data: reducing costs, generating revenue on the existing business model, and launching new business models. However, for this value to be captured, one element is key: digital infrastructure. Not only is it key for data users but it also concentrates significant value of the data economy. When looking...
While the current trend emphasizes the crucial role of data in decision-making, there are scenarios and contexts where not using data may be beneficial. In a world obsessed with data, could deliberately ignoring it actually become a secret weapon for innovation, agility, and intuition?
A great deal of performance improvements through AI stem from automating tasks and moving labor from humans to machines. However, recent research highlight that the reality is more subtle and that human resource is a major component and pre-requisite for leveraging performance improvements through automation with AI. Additionally, using AI has significant impact on staff...
Over the last years, numerous reports have highlighted the gap between the promises of value creation associated with AI and the value captured by companies in reality. A recent research has investigated the drivers influencing success of AI initiatives and concludes on 4 drivers which ensure AI influences performance. Interestingly, they are not directly related...
Selling data can be a major revenue opportunity. However, navigating the business ecosystem of data trading is not a catwalk. Which is the best option: monetizing directly or through brokers ? Beyond the revenue opportunity some key strategic considerations are to be analysed for data generators who want to monetize their data.
When it comes to offering data-services, selling data assets, entering into partnerships and data-sharing agreements, agreeing on the value of data is critical. What are the methods to discover the value of data? Which strategic implications?
Cars, tires, drilling machines, industrial equipment and many other objects are now full of sensors that capture data in real-time. It opened an opportunity for product manufacturers: launch service-based offers. Though very attractive on the paper, research shows the implementation of these business models is challenging and that the promised profits are not always cashed...
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