The combination of entrepreneurship, innovation, and technology has become the source of disruptive business models that transform industries and markets.

The case of the French startup Luko is an extraordinary example of the combined strength of these three drivers in one of the most mature sectors of the economy: Insurance.

Identifying problems and creating solutions

Entrepreneurs are disruptors by nature. They look for latent challenges, problems, or needs in society, build a solution and adopt it with a new business model. Raphaël Vullierme, the co-founder of Luko, explains it this way:

“We started Luko with a simple statement and idea – we can use Artificial Intelligence to give people access to data about their homes, thus making homes a healthier and safer place. We decided to collect and analyze available home data to help people protect their home sweet home and optimize their energy use. It led us to partner with traditional home insurance companies: What is more logical than an insurer equipping their clients, so they can avoid damage and better understand how their home works? Unfortunately, (or should I say, fortunately?), we quickly learned how broken home insurance was; an industry built around a conflict of interest. The more claims that are denied, the more money insurers make. This leads to a terrible experience for the customer: unintelligible contracts and hidden exclusions, sales trying to convince him to take out guarantees he doesn’t need, slow and complex claims handling” (1).

The idea or solution to this challenge brought together different types of enabling technologies: smart devices or sensors (IoT), data analytics, and artificial intelligence. Luko individually monitors the energy consumption of multiple household appliances, using a device connected to a common electricity meter. This involved the development of a small piece of hardware that a person can attach to their home electricity meter without electrical contact and without connection to the grid. Luko is not the first company to do this, but it is the first to create a device that can be used by anyone without having to open a fuse box or manipulate wires. Partially as a consequence, the data collected by this device is less accurate than that collected by more sophisticated, alternative devices. It can detect the main appliances in the home, but not those with low consumption. It is here where artificial intelligence becomes useful. AI can identify the energy footprint of different appliances as each consumes electricity in a slightly different way, for example, a heater does not consume electricity in the same way as a garage door.

The same principles and ideas have been applied by Luko in the protection of houses (for example, doors) and in the detection of water leaks through devices installed in the water inlet systems of homes.

Business model innovation

With its use of AI, Luko clearly constitutes an excellent example of service innovation.  Luko’s greatest impact is, however in its innovation of a new business model. As the company’s website says: “Preventing claims from happening is even better. Get peace of mind with our prevention measures” (3). From this premise, Luko configured a very innovative value proposal called “Giveback”. When the insured pays their premium, the company takes 30% to cover fees, and 70% is pooled with other premiums to ensure that they can be reimbursed if a claim is filed. Then, if money is left at the end of the year, the company returns it to charities chosen by the client. By so doing, customers know that Luko will not try to find excuses to avoid a refund of a claim since the company does not keep the money. In this way, Luko creates a transparent and trusting relationship with the client.

Data-Driven Innovation

The analysis of the Luko case also exemplifies the importance of the development of new organizational capabilities. In this case, the capabilities relate to data management and its utilization in a competitive digital environment.

Dykes talks about this in terms of an Analytics Value Chain. The venture must first generate or capture the data, then the data must generate reports which should in turn lead to deeper analysis. The analyses must be made available to the decision-maker who incorporates them in a decision-making process. This is a data analytics value chain: Data informs a decision that then changes the strategy or tactics and ultimately has an impact on the organization and its customers, creating value.

In the Luko case, the application of this data analytics value chain is shown, starting with overcoming the challenge of capturing data in the home with smart sensors, using artificial intelligence to analyze that data (analytics), and taking decisions that lead both to tactical recommendations for customers (new consumption behaviors) and to strategies for the company through new business models and monetization. Ultimately, this adds up to high value for customers, the company, and society more widely because of improvements to energy and resource sustainability.

Final thoughts:

Some key lessons for entrepreneurs and business managers emerge from this case:

Data-driven innovation requires data, of course, but more importantly, data-driven innovation requires a combination of different organizational capabilities. It shows that entrepreneurial leaders embrace the principles of innovation (problem identification, ideation of solutions, generation of new business models) in combination with the exploitation of new technologies (intelligent sensors, artificial intelligence, etc.). The most valuable solutions are those that are scalable, and technological capability is the main lever to achieve this. Luko’s goal was to develop a small piece of hardware that anyone could install, without prior knowledge or tools, and without security concerns. Then artificial intelligence would do the rest of the work.

(1) The innovation of business models combines a differentiated value proposal with key technological levers, and a highly sustainable approach. Disruption changes the rules of the game, affecting how competition is pursued in the marketplace.

Reference:

Lorenzo, O., Kawalek, P., & Wharton, L. (2018). Entrepreneurship, Innovation and Technology: A Guide to Core Models and Tools. Routledge.

This Case study is part of what you will learn during the course in Entrepreneurship & Innovation: Practical Models and A Roadmap for Immediate/Effective Application.

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