innovation workshops and data labs

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New principles must be established to promote precisely this mindset within the company. The organizational change and the associated availability of information at the level of the specialist departments pave the way for this.

However, a data-driven mindset also means relying on data when making decisions, rather than trusting your own intuition or, rather, your gut feeling. This may be met with some resentment in an industry such as insurance, where all of your belongings and your own health can be insured. Due to the transfer of risk, trust on the part of the customer plays an enormous role, as the policyholders are dependent on the promise of protection and thus on the performance of the insurance company in the event of a claim. The refusal to pay a claim can mean financial ruin for many insured persons.

So, with such an emotional and trust-dependent product, why rely more on data rather than on the experience and intuition of the employee?

The mindset is deliberately called data-driven and not data-based. In the insurance industry, or rather in individual processes and sectors, a certain amount of leeway is required between data and intuition, as well as the ability to analyze and accept errors.

In the past, many projects in the field of machine learning were started cayman islands consumer email list​ in too small a way and with too little focus on the solution space, with too much focus on the technology. As a result, many of these solutions never left the proof of concept stage, but rather fizzled out.

But how do you proceed and “start the journey”?

It was already mentioned at the beginning that the classic boundaries are blurring both within the organization and with the outside world of the company. This fact must be taken into account when considering and planning data-driven business models. It is necessary to create an understanding of current technologies and future trends. Looking into the future opens up the space for innovation and possible solutions.

This approach can be illustrated by conducting an innovation workshop and is carried out by an interdisciplinary team. The workshop is divided into three phases.

1. Understanding
2. Idea generation and development of an innovation roadmap
3. Validation of possible solutions and decision making
The format described above serves to initiate an innovation project and is the preparation for setting up a data lab that offers a permanent and company-wide place for innovation, with the aim of providing ideas in the form of MVPs within the shortest possible time. As an internal unit, data labs enable close interdisciplinary collaboration with the various specialist departments, knowledge developers and data scientists, who in turn develop and test prototypes and ideas and thus provide data for evaluation. They are the permanent establishment at the insurer in order to build new data-driven business ideas.