When you don’t know, run experiments

The effects of digitalization and other technological shifts cause companies to realize they need to change. This often leads to significant discussions in the organization as there typically are several alternatives being considered by different people. These might include topics such as business models, product implications, partnerships with suppliers and technology providers. Agreeing on the … Read moreWhen you don’t know, run experiments

How Digitalization Disrupts Companies

Although everyone talks about digitalization (software, data and AI) and the risk of disruption that this brings to companies, very few talk about how companies get disrupted in practice. Most treat it as an amorphous force that topples companies over like a force of nature that is unavoidable and where we are the victims. Of … Read moreHow Digitalization Disrupts Companies

Machine & Deep Learning: Experimentation Stage

This week I got the opportunity to speak at the initiative seminar organized by the Chalmers AI Research center (CHAIR). The key message in my presentation was that working with artificial intelligence (AI) and specifically machine & deep learning (ML/DL) constitutes a major software engineering challenge that is severely underestimated by companies that start to … Read moreMachine & Deep Learning: Experimentation Stage

It’s All About Your Digital Twin

As I have been writing about adopting data-driven decision making in the broad sense and data-driven development more narrowly over the last weeks, several people have reached out to me, discussed with me and more generally explored the subject with me. During these engagements, I realized that many products and services exist for the sole … Read moreIt’s All About Your Digital Twin

Data-Driven Development: Step 2 – Build Data Collection and Analysis Infrastructure

In last week’s blog post, I discussed the first step in adopting data-driven development (see figure below), i.e. modeling feature value in quantitative terms. Once we have described the value that we expect from a feature, the next step is to ensure that we can indeed measure and collect the necessary data in order to … Read moreData-Driven Development: Step 2 – Build Data Collection and Analysis Infrastructure

Data-Driven Development: Step 1 – Model Feature Value

In my research and consulting engagements with companies, one of the recurring themes is the ambition of companies to become more data-driven in their way of working. After working on this topic with a variety of companies, my fellow researchers and I defined an adoption process that companies go through when adopting data-driven development practices. … Read moreData-Driven Development: Step 1 – Model Feature Value

From Dozens to Thousands (or Millions) of Products

This week I spent time in Denmark at a summit organized by the Manufacturing Academy of Denmark (MADE). During the summit I met several people that expressed pride at the richness of their product portfolio. Some companies have a dozen different products, others may have close a hundred products. All these products are complicated including … Read moreFrom Dozens to Thousands (or Millions) of Products

Does Agile Kill Innovation?

Photo by Kristopher Roller on Unsplash During a recent conversation with a journalist, the downsides of agile came up in the interview. The questions were centered around stress levels of team members, the frustration with not being able to do a proper design before building features, the perceived reduction in innovation and other factors. During … Read moreDoes Agile Kill Innovation?