Discussion

The contribution to existing literature is quite limited in this thesis, as the thesis project was mainly oriented to find a solution for the supplier company’s existing problem, using

methods, frameworks and theory already known. Thus, the main contribution to literature is, more or less, applying this kind of iterative value identification process and combining it with the quantitative multi-criteria decision-making tools to simulate customers’ deci-sion-making to gain insight for the business model generation. The method gave promis-ing results in terms of feedback from the actual projects and sales leads. Also, the method proved out to be quite cost efficient. It might also be possible to undergo a similar process in future in quite a rapid phase, as the process is now well documented and all the forms and templates are ready for future use. However, it can be expressed that the text did not contribute to the existing literature with new theoretical input, as no new theoretical frameworks or propositions were made. This text was, more or less, an application case of customer value identification and quantitative multi-criteria decision-making tools.

Thus, answering the research question by utilizing the three step iterative customer value identification process, customer decision-making simulation and providing a Business Model Canvas provides an application example of these tools with analyzed advantages and disadvantages in this case. The application case and its connection to existing litera-ture is further discussed in this chapter.

In their text Kothari & Lackner (2006) argue that companies should view the market within the company from outside in. In essence, this would help the company to focus on developing their operation to answer customer needs by developing value components that customers currently value and thus to shift away from product-centric viewpoint.

This is important, as the value components the customers value might be changed from the initial value components with which the company begun its operation. Keränen &

Jalkala (2013a) also address this matter in their text by arguing that the customer value identification should be continuous process and occur before, during, and even long after the delivery is done to the customer.

In this text the market was, indeed, attempted to view from outside in and thus to objec-tively identify the value components the customers currently might value. This would then help the supplier company to select geographical locations where their offering’s value components will have positive demand. However, the suggestion of continuous customer value identification suggested by Keränen & Jalkala (2013a) was not adopted into this thesis due to the timeframe limitations. On the other hand it was also noted that the discrete value identification executed now during the thesis project will most probably provide sufficient reliability for some near future as well. This was due to the fact that the energy- and waste industries are mainly affected by political decision making, invest-ments are made for decades, and in general these industries are very slow in terms of change. This is especially if compared to, for example, information technology industry.

Thus, it was not seen important to utilize continuous value identification as suggested by Keränen & Jalkala (2013a) and to include it into the recommended future actions, as it increases the complexity and therefore the marginal benefits are outweighed by the costs.

Anderson & Narus (1998) suggest two methods for customer value identification and assessment. These methods are customer focus groups and field assessment (Anderson &

Narus 1998). The first method, customer focus groups, was not directly seen as possible alternative component in the concluded iterative three step customer value identification process. This was due to the reason that interviews and all other direct involvement of customer was not allowed due to project reasons of the supplier company. However, the second proposed method, the field value assessment was included as one step of the three step iterative process. In their text, Anderson & Narus (1998) suggest creating a value assessment team of various professionals. However, in this thesis project the value as-sessment team consisted only of the author and an Eera consulting company representa-tive, who was also present in the final step, the professional workshop. It was decided, that considering the resources available and the deliverables generated during the field value assessment, the generated value assessment team was sufficient. Thus, even though it might not always be possible to form an ideal value assessment team including repre-sentatives from sales, product management, and marketing, as suggested by Anderson &

Narus (1998), in some cases important results can also be achieved with a smaller value assessment team. Also, the documentation of the observations was seen as very important factor of the value assessment on the field, as the assessment can last for quite some time.

In this case a diary type travel memo relying on chronologically organized bullet points was seen as sufficient method. Also, the very low level of order made it easy and encour-aging to write down even the smallest observations, thus enabling comprehensive docu-mentation in chronological order.

As mentioned before, the customer focus groups method was not directly seen as suitable.

However, elements of it were utilized in the third step of the three step iterative customer value identification process. In this third step a professional workshop was held, based on the results from the two previous customer value identification steps. Thus, it could be called, for example, professional focus group. However, this group had only one work-shop meeting as opposed to several focus group meetings suggested by Anderson & Narus (1998). As this was not ideal, some results were still gained with lesser costs and utiliza-tion of resources, of which the time of the several professionals was undoubtedly the scarcest. Thus, even this kind of adaption of the customer focus groups method could provide sufficient results, when customers are ruled out from the customer value identi-fication and when the time resources of the decision-makers are very limited.

In this text the customer value identification and analysis was executed in an iterative three phased method. The components in this iterative method were initial identification by the author, adapted field value assessment, and professional workshop with elements from customer focus groups method. Conducting the customer value assessment in three iterative steps proved out to be both cost efficient and reliable method. Also, the compo-nents of which methods each separate step is consisted of can be varied according to any specific case in question. This will ensure, that the method can be selected in a way that

the execution of the value assessment and identification is feasible in the first place, and secondly, in a way that it provides reliable results. Thus these methods can be, for exam-ple, direct interviews, questionnaires, methods suggested by Anderson & Narus (1998), or any other method that in future is considered feasible.

The customer’s decision-making was simulated in this text by utilizing quantitative deci-sion-making tools. These tools were Weighted Sum Method and ELECTRE III and those were used in an MS Excel tool called SANNA 2014 presented in his text by Jablonsky (2014). The method proved out to be extremely cost efficient and easy to use, as no aux-iliary software needed to be installed and, in general, the MS Excel user interface is fa-miliar to most of the decision-makers. On the other hand, some other decision-making simulation tools could be used in future as well to provide estimates about the customers’

probable decisions and to enforce the customer value assessment. For example, the busi-ness game concept presented by Laine (2012) could be one alternative. This alternative would also, at least in some depth, contain customer value identification and assessment functions internally, as that is a side product of the game when managers position them-selves to the customers’ managers’ point of view. Thus, this method could be a great way to combine customer value identification and assessment together with customer deci-sion-making simulation and to simultaneously receive many different outcomes, as mul-tiple teams would participate into the game. In addition, the game would most likely in-crease the overall understanding of customers’ business within the company’s managers, thus laying foundations for future actions to take customer and their value components better into account in everyday business. On the other hand, this method was not initially included into this thesis as a part of this iterative three step method. This is because when compared to the three selected methods, the business game method might end up being too resource intensive since the time of the professionals was one extremely scarce and thus limiting resource. However, as the methods should be selected case by case, the business game method might end up being feasible in some cases.

The amount of iterations in customer value identifying and assessment can vary also. In this specific case three iterations seemed to give reliable results with reasonable costs. In some other cases the amount iterations can be less or more. Also the selected methods might influence the amount of iterations. For example, if the business game method is utilized, the amount of iterations could be only two. The first iteration could be thorough utilization of customer focus group method and aim to create as realistic business game about customers’ businesses as possible. The second iteration could then be the business game played by the supplier company’s managers. This iteration would also simulate the customers’ actions and decision-making. Thus, the simulation results and refined under-standing about customer value would be achieved in the same phase. Also, the results might be easier to understand to the managers, as they have been participating in creating those results by playing the business game themselves. This might, however, not always be the case when utilizing the quantitative decision-making tools, such as Weighted Sum

Method or ELECTRE III, as the derivation of the results might not be easy to understand even though the result itself might be as user friendly as, for example, listed order of favorability of different alternatives.

In this case the use of Business Model Canvas was specified by the supplier company, as the output business model was wanted in the form of Business Model Canvas. However, the Business Model Canvas appeared to also fit well this case as most of the critique addressed in literature review chapter and presented by Kraaijenbrink (2012) can be mit-igated by taking into account the business the supplier company is currently operating on.

On the other hand, even though the Business Model Canvas enables an efficient tool to illustrate new business models and to present them intuitively, some other methods might be utilized as well, if seen necessary. However, currently the Business Model Canvas seems feasible solution, even if some components of the Business Model Canvas might not contain new or groundbreaking information for the company, as the business model is generated on the basis of existing business the company has. Because of this, it could seem rational to simplify the Business Model Canvas tool by creating default fields to, for example, Key Partners, Key Activities, Key Resources and Customer Segments. How-ever, this would probably result into a state where these components would always be left for the default state and thus those would never be re-assessed during business model generation. For this reason, it would probably be reasonable to maintain the Business Model Canvas tool as Osterwalder (2010) presented it and to force the decision-maker to recreate the whole business model each time.