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The Story of Greeniant
Meet Geert Jan Dirven. He is founder and CEO of Greeniant. Before starting Greeniant, Geert Jan had been in the IT business for many years and learned that many elements of the firm’s process are being digitalised. In the supply chain it was of major importance to predict demand in order to optimally distribute resources, personal and machinery. The accuracy of your prediction correlates to whether you make a profit or lose money. Geert Jan and some colleagues realised that the possibilities of the huge quantities of data are almost limitless. It struck him that data might be the new oil. Using big data allows you to iteratively control the assumptions used to make the predictions about demand. This makes the predictions more accurate. This process can also help to de-aggregate information that is provided in bulk. As it happens, a new source of data was being rolled out nationwide, in several countries: the smart meter. Geert Jan realized this might be his business opportunity.
He hired some employees, very intelligent tech nerds, to develop a very smart, highly secret algorithm. This algorithm de-aggregates the P1 data from the smart meter and is able to recognize the specific energy-behaviour of all electrical devices in a home. For example, when the device is showing abnormal usage patterns you could be informed that repairs have to be done or a replacement is needed; a proper smart solution to many problems. Greeniant was founded: a company that provides smart services based on smart meter data. This data allows for services provided in three areas: information about energy use, information about appliances (e.g. for maintenance, hours operated) and behaviour. The data and smart meter are the main resources, along with the knowledge of what to do with them, the distinctive feature of the firm. But along the way, Geert Jan is facing some severe problems. His tech nerds know how to develop an algorithm, but they do not know what their users are really interested in. And Geert Jan realizes, he is not managing a tech business, but a service business. Providing a service to an enduser is hard if it requires a specialized solution; the firm would have to re-invent the wheel for every customer. To make this feasible Greeniant targeted firms with a large customer base, thus becoming a B2B2C business. These firms could then provide a service to their customers while Greeniant receives a service fee based on the number of end-users the service reaches. In the first years of business Greeniant provided services to a diverse group of clients: energy companies, insurance companies, an association for farmers and more.
The solutions took the form of an application or online platform where users can view their analysed data and what action should be taken. One of the key-activities is identifying what aspect of the data can help a user and consecutively designing an app or platform to make the findings actionable.
Research partners have played an important role in the development of Greeniant and its user oriented approach. Several partners helped them with research on these topics. Examples are Eneco, Essent and Eon, energy suppliers that are interested in energy services. This interest was partly generated by the energy efficiency directive which obliges them to reduce the energy demand of their end-users. Knowledge institutes (universities, high schools) also worked on this type of research.
Sensing user needs
Sensing user needs was seen as pivotal for the success of the firm as each client requires a different solution, but this came only later in the firms development. The start was very much focused first on creating this technological solution. A second issue was that greeniant found out through their turn to become a B2B2C enterprise, that when delivering a solution for a user that is different than the paying client two value propositions are required: one for the user and one for the client. You have to know the needs and wishes of both stakeholders. For this reason research was done with several partners and the client, but also the end-user is involved in the process of developing a solution; the information was thus not only based on big data.
For example, for one client (a farmer’s association) Greeniant had to provide a service to farmers that would result in a 2% energy reduction. During a presentation and meeting in the marketing phase Greeniant could directly interact with the farmers and the firm found out that insight in the energy use of their appliances did not raise any interest; what did raise interest was showing the cumulative use of a specific appliance. In this case the farmers all used vacuum milking tubes that lasted for a specific time (e.g. 150 hours of use). The cumulative time that a tube was used was kept track of only in the head of the farmer. Alerting the farmer that he had to change the tubes was a service that was needed and much appreciated and saved energy as well as the time to replace the tubes was much more accurately determined. And more importantly, replacing the milking tubes in time prevented wrong milking of cattle with all the illness following this milking. This showed Greeniant that they had to offer different value to their client than to the end-user and that the value that you provide to the end user does not necessarily have to have anything to do with energy or energy efficiency.
Sensing user needs was a well-developed capability, much needed to provide the unique and tailored solutions to the end-user and client. Greeniant has become aware of the context-dependent needs and wishes of its clients and users. In this sense it learned the capability of conceptualization.
The business model canvas of Greeniant. Template based on Osterwalder and Pigneur (2010).
Greeniant was founded with the assumption that providing information about appliances and its energy use is a valuable service. However, through interaction with family and friends and a research project with Eneco the entrepreneur was shown that his assumption was wrong: energy usage of electrical devices is a non-issue; people were simply not interested.
During the research with Eneco they decided to simply go to the end-user and ask what problem could fit to their solution. It turned out that Greeniant was actually too much focussed on technology: it’s not about the washing machine and its energy use, but on the practice that it is used for: washing. Washing is a process with many steps that can be made easier. Providing alerts as to when the machine needs cleaning or an inspection, again, turned out to be of more value than the information how much each wash costs in terms of money and energy.
It was clear that Greeniant and its employees knew how to develop algorithms and design custom solutions. They knew what their solution was, but their real challenge was to find problems that they could solve with their solution.
Understanding user needs was a skill that lacked at the start, but developed. The realisation that these user needs are important might have come too late for the firm, which went bankrupt end of 2015.
In the ecosystem of stakeholders there were matches and mismatches in relation to the usercentredness and service dominant logic Greeniant applied. A strong mismatch became apparent when Greeniant found an investor. Quickly they found out having an investor can greatly determine your agenda as investors are often financially driven. “You become less flexible and less of a pioneer” (Interview Greeniant, 2015). Besides that, the investor was not open to more user research and his product dominant logic impeded the user-centred business model. Greeniant noticed that the mismatch with the investor was a much broader problem. Similar mismatches are seen at various stakeholders, such as the local and national government, utilities, technology suppliers DSOs and other clients; they have not realised yet that there are more values to offer than energy efficiency alone. Often there is still a focus of delivering energy efficiency as a value to the end-user instead of solving their actual needs and pains which tend to be unrelated to energy. The only like-minded stakeholders in the ecosystem were the enablers of the business model; the research partners and several clients.
There is also a more general context that influenced the business model. As Greeniant did not serve only a specific market type a lot of different market contexts played a role. In the example of dairy farmers the agro covenant that says these firms should aim for a 2% annual reduction of energy was an important starting point (RVO, 2014). However, in all cases there is one important resource for Greeniant: data supplied through the smart meter. The firm is heavily dependent on the use of smart meters. “If the government were to decide we can only read out smart meter data digitally two times a year we would not be able to do anything anymore” (Interview Greeniant, 2015). The roll-out of the smart meter was also an important point of consideration when looking for other countries to expand to. Greeniant was aware of its context and the problems that can be created. However, orchestrating and aligning different actors in the ecosystem seems to be a skill that was underdeveloped.
Furthermore, finding a general formula for value creation is hard when working with many different types of customers in different markets. Scaling and stretching is another capability that required more development.