adesso Blog

Insurers are also modernising with cloud providers such as Amazon, Microsoft and Google. Global usage has increased thirteenfold since 2010. By 2025, revenues are expected to grow by 20 per cent to US$825 billion. In Germany, growth is estimated at 20 per cent. The use of cloud environments is standard, 'cloud first'. What are the challenges facing companies and how can they be tackled effectively?

Anyone thinking about agile software development concepts today often predicts improved performance, more robust software and happier employees. But is that really the case? And is the concept of "agility" really new?

Most decisions are made under uncertainty. The real world is an intangible system with a high degree of complexity and a multitude of dependencies. But how exactly does making decisions under uncertainty work? This blog post presents three main strands that are used in research for this purpose.

adesso employs all sorts of people, regardless of educational background. I myself used to be an academic philosopher of emerging technology. I found myself into venture capital and the startup environment, coming from the EU commission in policy and governance and now I am an agile project manager here at adesso. In this blog entry, I wish to examine some parallels in philosophy examining the nothingness on which everything is built and the agile methodology of managing business projects in areas of ambiguity, uncertainty and certainly, lack of knowledge.

For some time now, agility has been a guiding principle, a mindset, something akin to a philosophy to succeed in today’s business world. But with so many agile approaches to choose from, it is easy to lose sight of the big picture. We will therefore be taking a look at various agile methods from different angles. The aim is to help you choose the right method for you.

Agility and data science have both taken on a larger role in recent years. The use of agile methods and frameworks can be a key factor in the success of a company. In this and future blog posts, I will be focusing primarily on the question of whether and how agile approaches can be integrated into the field of data science. We will begin by taking a look at basic things you need to know about data science and agility.

How we work has changed fundamentally in recent decades, a trend that was accelerated by the COVID-19 pandemic. These changes require new forms of work in companies that are focused on the evolving needs of employees. The term used to describe this is new work. Agile working is a form of new work. We explain what this is all about in our blog post.

If we view organisation as more than just an administrative framework – namely a structure that has a purpose and creates value – then it becomes clear that finding a holistic approach to develop said structure is not easy. This blog post will introduce the 3⁴ concept for organisational development.

In the first part of our blog series on ‘Agile scaling and the challenges that come with it’, we took a closer look at the demand for agile scaling and the associated challenges that need to be overcome in order to generate added value for an organisation. In this next part, we will focus on the challenges that come with agile scaling.