Product Thinking and DevOps are key to enable (Tech) Orgs increasing their ability to build better products at higher velocity. However, in order to continuously maximize the value exchange with the customer, we must consider all the socio-technical systems in the product development activities. All of these are continuously changing: customers, markets, organizations and teams evolve and products technical architecture will follow. Change is unavoidable, which means organizations must strive for operating models and systems that embrace it.
In this talk I will discuss several interesting traits to consider on the different (socio-technical) systems in order to maximize the org's ability to cope with such changes and evolution. For each trait I will share patterns of evolution and use cases, e.g.: evolving Data Science & ML operating models as function of org size and complexity; evolving Platform Teams from operations to product mindset; evolving technical leadership from pure informal networks to the addition of structural enabling teams, etc. These are patterns and use cases I observed over the last four years while working in different initiatives to "scale and evolve" bol.com.