Data-driven business models

Digitalisation in the energy industry makes it possible to implement data-driven business and decision-making processes throughout the entire value chain. Everyone that does so encounters new challenges in the process. A lot of companies these days complain that there are too many manually controlled processes. They want their business processes to be digitalised. At the same time, the main question being asked is how the large volumes of customer data and data on production, distribution and transmission can be collected, processed and utilised in a structured and efficient way.

Companies often work with several systems that are impossible to integrate due to insufficient interfaces or poor communication. The problem here is that only some data is stored redundantly. Companies can only create processes that are efficient, plausible and automated when they have a holistic view of the data – from collection, to storage, to evaluation. When developing software landscapes, the need for interfaces increases and the relevance of system interdependencies becomes more pronounced. Data is the basis for almost every new business model, as they often include data-based evaluations – as well as smart contracts or platforms.

We help your company create data-driven business models by applying our wide range of methods and tools to each of your respective situations.

Value-based maintenance (VBM) is about deciding which maintenance measures are to be carried out at the power plant and when the maintenance is to be performed. Factors such as the condition of the power plant’s components, the power plant’s operating state and the economic impact of maintenance measures and component failures are used as a basis for making these decisions. These factors are included in a risk assessment that factors in the economic impact of a given maintenance measure and keeping the power plant operational. The decisive factors for a VBM risk assessment are scattered throughout the various knowledge silos within the company. Forecasts on component conditions and economic developments are required to be able to plan maintenance work in advance. The exact maintenance costs are unknown and may vary. The exact amount of (economic) damage a power plant component failure entails is unknown.

adesso is building a central data platform in order to centralise the data from knowledge silos. adesso will use this data to build predictive models to do things such as forecast the service life of power plant components. In addition, we help digitalise engineering experience to better assess the damage potential of power plant components and the effort needed to maintain them.