Читать книгу Service Design - Ben Reason - Страница 24

One of the things that hampers product innovation in insurance is the time delay. Organizations only find out whether an innovation will make or lose them money after they see the level of claims, which can take several years. Thus, the insurance industry traditionally is conservative about innovation. The customer insights gathered by the design team helped inspire confidence in bringing new ideas to market.

Using the material from the insights research, Gjensidige ran co-design workshops with different groups within the company and generated 97 ideas, five of which were chosen for further development. Finally, the team came up with one new service proposition.

Gjensidige had about a dozen products for everything to do with people, from individuals to families. From an insurance point of view, this meant that they had a fantastic array of tailor-made products for different eventualities. From a customer point of view, this meant that people felt like they were faced with impossible life insurance choices, such as gambling whether they would die of cancer or in a car accident, because nobody could afford to buy all of the policies and be 100% covered. Customers faced the same dilemma when choosing which possessions to insure—the dog or the laptop?

The breakthrough concept for Gjensidige was to go from offering 50 products to just two: one to cover the individual and his or her family, and one to cover everything they own. From an insurance point of view, this was very radical, but in an example of the value of the expertise that exists inside organizations, the basic idea came from Gunnar Kvan, a very experienced Gjensidige actuary, during a series of design workshops. He suggested that it was possible to think about the company’s offerings in a dramatically different way. He had been working on this idea for five years, but had not been able to get people to see his point. He had no way of expressing his view in terms of what it would mean as an experience for customers, but he knew the financial algorithms could be modeled differently. The design team sat down with him and went through how such a service could be put together. It would require hard-core mathematical engineering in a huge spreadsheet running in the background to make it happen.