Jan Bosch
During the big data era, one of the key tenets of successfully realizing your big data strategy was to create a central data warehouse or data lake where all data was stored. The data analysts could then run their analyses to their hearts’ content and find relevant correlations, outliers, predictive patterns and the like. In … Read more
In reinforcement learning (a field within AI), algorithms need to learn about an unexplored space. These algorithms need to balance exploration (learning about new options and possibilities) with exploitation (using the acquired knowledge to generate a good outcome). The general rule of thumb is that the less is known about the problem domain, the more … Read more
Peter Drucker famously said that the purpose of a business is to create a customer and a customer is defined as someone who pays for the products and services the company offers. This perspective seems to be shared by many in business: as long as revenue and profits are generated, there’s no reason to bother … Read more
Over the last weeks, I’ve been to three different conferences where I heard presentations that were variations on a common theme: if we would just add more structure and more process to the topic at hand, if we would only introduce more steps, more checkpoints, involve more people, and so on, then all the problems … Read more
This week, I gave a talk at a company that’s starting with data-driven practices and A/B experimentation specifically. My talk was concerned with the enablers required for this, such as continuous deployment (or DevOps), the specific ways in which organizations can apply data-driven practices and A/B testing and the importance of value modeling so that … Read more
Before digitalization became a thing, the industry was divided into two types of businesses: those that sell products and those that provide services. Those that sell products have a transactional relationship with their customers, mostly consisting of selling one of their products. The service businesses tend to have a more continuous relationship with their customers … Read more
Last week, I wrote about the different types of use for data that we have available. That led to discussions with various people and I realized that there’s a problem around data that’s very typical in companies that have their roots in embedded systems or mechanical engineering: it’s actually unclear who owns the data from … Read more
If you’ve been reading my posts, you know that I feel data is one of the key ingredients of a successful digital transformation. It’s not just about adding software to your products or putting DevOps in place. It is as much about collecting, analyzing and storing data and using this data to improve a variety … Read more
This week, I spent two days in systems engineering workshops. Systems engineers are concerned with designing products and solutions including mechanical, electronic and software components. Systems engineers and architects address all requirements of a system, including regulatory constraints, such as functional safety, customer-facing functionality, such as the features that the customer uses on a daily … Read more
With data- and AI-driven development taking over the world, it may easily seem that the cloud is the place where everything happens. This is where the data is stored and analyzed, where the machine- and deep-learning models run and where all the value resides. The perspective of people living in this world is that all … Read more
