With AI, algorithms are able to perform tasks much better, faster and with less errors than humans. A recent research concludes in a more subtle way: under certain conditions, humans perform better than machines when it comes to decision making. In which context humans beat the machines? What are the implications for strategy and resources...
What translates big data into business value? Beyond technical and data-related resources, study shows human-related resources and capabilities are more important. Then, how to leverage the human drivers of value creation through big data?
Sharing goes mainstream, and the news is full of data sharing agreements between companies and within industries. In addition, intermediaries are every year more numerous to position as enablers of data sharing. When taking a closer look at these initiatives, one immediately concludes that not all sharing agreements are equal and strategic motives govern each....
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...
Like any relationship, the one between data/AI and environment is complicated. The news is full of examples of how AI is used to preserve resources but is also full of news of the every day bigger energy consumption of data and AI. Are those technologies more beneficial than harmful when it comes to preserving the...
The time when industries were clearly delineated and competitors were looking alike ended. In many markets, companies from previously separated industries compete for the same customer spending and more intense competition is within value chains. Data is one asset in this competition transformation. What is at stake? What are the key questions to secure leadership?
It’s common to say that platforms aggressively compete with incumbents on value capture in non-digital-native markets. A recent research sheds light on the process by which big tech companies enter regulated markets and the role data play in this entry strategy. How do big tech use data to enter markets?
The Commission proposed new rules on who can use and access data generated in the EU. Jointly, these new rules are expected to create €270 billion of additional GDP by 2028. Which are the main value creation opportunities ? Where the future battles for value capture will take place? How to prepare?
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...
Because time-based competition increases pressure on constrained resources, What to do first? is a more important question to answer than what to do? Beyond the usual attractivity vs difficulty matrix, two other dimensions are important to take into account to prioritize data-driven value creation opportunities.
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