This blog entry concerns itself with the impact of the digital transformation on business models in general and the role of data specifically. I will discuss the meaning of a data-driven business model, the benefits of the implementation of one and the obstacles one has to overcome in the process.

Data-driven business models, maturity levels and obstacles

Data-driven business models are the result of the growing digitalisation and technologisation of the workplace and they will become an increasingly important factor regarding competition. More and more data can be collected, stored and in the context of digital connections be made available. This calls for a digital strategy to lead the way along the cycle of digital innovation, business innovation and rapid sectoral growth.

Reasons for the implementation of data-driven business models are primarily related to growth, profitability and competitiveness. Currently, incentives mostly come from the market. Here, it is possible to categorise along three maturity levels:

  1. Optimisation and Automation of processes, products and services,
  2. Expansion or Transformation of established business models,
  3. New Conception, i. e. the development of entirely new use cases.

At the moment, insurers still predominantly focus on process optimisation with the goal of minimising costs and improving operational excellence. But there are cautious advances, e.g. in the recognition of customer journeys or the use of intelligent analytical technology and algorithms tested specifically for the insurance industry.

The insurance industry has by now realised that there is a sense of urgency in regards to the use of data. New alliances, innovative business models and cross-industry ecosystems are constructed but some obstacles still remain, like the lack of use of digital possibilities, a shortage of technical experts and general uncertainty concerning data security. One main problem is that many businesses do not have a strategy for the development of data-driven business models and as a consequence, their potential remains unclear.

Conclusion

The digital transformation of one’s own business model still presents a great challenge for most. Every business should find a fitting strategy to integrate data into one’s model to raise efficiency. In the future, insurers should not only react to changes in the market but be proactive in furthering the strategic further development of the core business to move to a holistic service package within the scope of one ecosystem.