A Comparative Analysis Framework for Industrial Blockchain Use Cases
For industrial research projects like iBlockchain, it is vital to create insights that are not only well-documented but also establish their own value after the conclusion of the project. For this to happen and in order to guide the reader through the use case selection process of the iBlockchain consortium, this chapter captures requirements and condenses them in a comparative analytic framework which can be utilized to evaluate future consortial projects or just to compare use cases from a project standpoint.
Authors: Marcel Kaiser, Philipp Sandner
Motivating a framework for comparative analysis
Looking at the usage of a framework from an academic perspective, it becomes clear that such an endeavor can not be tackled without a clear research question. Use cases were built using the question Where can decentralized approaches to industrial processes be realized under utilization and improvement of network effects?. We chose the approach of Failure Mode and Effects Analysis (FMEA) while tweaking some features. A set of general requirements for blockchain projects, and an evaluation scheme, were added. These can be adapted to the project into consideration. In the following subchapters, our procedure will be described and our results will be presented.
Failure mode and effects analysis
What is FMEA?
Quality and risk managers around the globe apply this framework in order to prove and explain the validity of their decisions, mitigate occurring risks, and minimizing costs caused by negative externalities of processes (Dittmann, 2007). The method usually employs many analytical steps to identify and quantify factors that can help to sharpen the results and the model. Since we want to apply it to a more abstract project whose processes are not yet up and running or creating profits, we could reduce the scope of some steps.
The procedure of FMEA application
We adhered to the framework in terms of its basic steps: Define risk groups, which are defined below in the section Catalog of requirements. From those risk types, we derived examples which can be considered realistic for DLT and Blockchain applications. We then tried to associate a criticality of consequences which was, again, validated in the iBlockchain consortium. Moreover, the likelihood of occurrence and the likelihood of detection of risk was estimated based on estimation and knowledge obtained from externals.
To make sense of these values, we applied the logic of FMEA in the following equation:
where Π is the risk index, and C the criticality, p represents the probabilities. This risk index will then be multiplied with the perceived control E over the risk to obtain the priority index Φ.
Φ matches higher priority risks with a higher number but has no unit.
Catalog of requirements
In the following, prior to any FMEA analysis, the consortial catalog of requirements is established and a mainly qualitative ranking of use cases is established. For its discussion, an internal workshop has been executed. Please take into consideration that this article cannot reflect each aspect discussed at the workshop but can only give short insights. For each of these criteria, we apply a scale from 1–5 points where 5 points represent the optimum. This scale and its estimation is partly based on the sentiments and statements of the partners about each use case but can generally be verified with the framework at hand. An official survey has not been conducted.
Categories
Congruency
Are participating partners in harmony about interest in the case? This value is easily quantified. Each point given represents roughly 1/6 share of consortial members (4 points are 4 or 5 out of 6 members, otherwise) each point is one consortial member or institution increment. Being in line with the project’s dynamics is a crucial factor and has thus been included in the framework.
Correctness
Are assumptions about the scenario reasonable and possible? Is it required to make several assumptions about the world which are not commonly expected to be fulfilled at some point (i.e. digital Euro)? For each assumption concerning topics which can not significantly be influenced by the consortium, one point is deducted.
Feasibility
Is a sensibly defined goal reachable within a reasonable time frame and with a reasonable effort? Here, several benchmarks are taken into account: Is a comparable project (in terms of scale) already realized (2 points)? Is a comparable or compatible project in the sector already implemented or on its way (1 point)? This benchmark analyzes if the project is proven as applicable in the field. Is the consortium well-staffed and well-equipped for the project (1 point)? Can all participating companies profit from the learnings in this project (1 point)?
Relevance
Is the topic relevant for partners, their customers, and the respective markets? This value adds up by estimating the subjective relevance of the topic for the consortium and their customers and partners (1 point for each aspect), the society as a whole (1 point), and expected longevity of the project (2 points).
Novelty
Is the project already implemented elsewhere? In contrast to the aspect of feasibility, here points are given for novelty. If this project is already described in large detail but not implemented, one point can be reached. If its outline is already often defined but not central to a project, up to three points are given. If the consortium adds new aspects, four points are given and a complete novelty is rated with five points.
Network coordination function effect
A rough estimation of how much value is created by the quality and quantity of the interactions the given project can enable. The scale is defined by the weight of the central coordination point of the network at hand. If a platform, rather than a tool is created, there are network externalities and resulting which the given project will create for its users. Here 1 point is given for benefiting (some) individuals, 3 points are given for benefiting sectors, 4 points are given for coordinating processes in multiple sectors, and 5 points are given for globally relevant infrastructure across sectors. The true potential of the network effects for each use case can not easily be assessed without proper models. Understanding these (often very dynamic) processes is still part of contemporary research and often requires complex modeling approaches (Herd, 2018).
The legal aspect of the project
Will there be high dependencies on the regulator? Since we are no legal experts and there is, in most cases, barely legislation about related systems (especially across borders), an estimation is made based on prior legal experience with related projects based on a list of over 80 use cases. If a project is too invasive in an existing system and therefore made illegal, 0 points are given. If related projects exist (or existed) and their projected goals face persisting legal barriers, two points are given. Three points are given if a legal situation is not yet defined and five points are given if there are no obvious signs of legal barriers in affected countries yet. A legal assessment with more detail will be provided in a later work package.
Establishing weightings
The main focus of the project is to circumvent and neutralize platform monopolists in the industrial sphere while creating value. Thus, network effects have to have a high valuation in a framework for comparison. A reason for this is especially the notion of moving into a platform economy (Kennedy and Zysman, 2016). However, especially in the blockchain space, feasibility and correctness deserve special emphasis. Therefore, the mentioned weighting of these increases to 1.5 so that a total maximum of 40 points is achievable. Moreover, the FMEA framework (see table 2) receives additional weighting depending on the perceived control over the problem. For this measure, we validated estimations within the consortium. We had to apply several discussions into the ranking whose contents can not easily be worked into said framework ex-post which is why we created an additional matrix that summarizes all the results.
Use case ratings based on the framework
Table 1 represents the results of the described process. It has to be mentioned that micropayments are considered a precursor for all of the use cases and thus do not have an own rating. The legal estimation of the use cases excludes the fact that micropayments are required.
Resulting use case
The resulting use case is a merger of the two best-rated use cases and was deducted from discussions resulting from the FMEA table for the two. The final use case is described and discussed in another article but a short explanation as to why it has been established like this can be given. The consortium has deemed the two equivalent use cases and their practical implementation very similar. Also, the FMEA analysis showed that challenges would have to receive similar attention, which is further analyzed in future articles. Moreover, further research and simulation about platform dynamics from a consortial partner (as can be seen Herd, Scharmann and Phelps (2018)) indicate that mutual distributed ledger technology promises an alternative to proprietary platform-based solutions and is therefore vital in the context of future Economies of Things. However, in order to avoid centralization and related effects and guarantee long-term stability, a well-defined governance structure is required which is woven into the final order-controlled production use case.
Distinction from existing frameworks
Existing blockchain evaluation systems are mostly guidelines on whether or not to use distributed ledger technology for certain problems. Wüst and Gervais (2017) developed a flow chart to determine whether a blockchain is the appropriate technical solution to solve a problem. Also B. Suichie, A. Lewis, and many more developed comparable frameworks for analysis if the application of blockchain makes sense for different business cases. Obviously, the use cases were created with these insights in mind. However, they do not help in the qualitative comparison of several sensible blockchain use cases.
Comparing our evaluation framework with existing project evaluation frameworks, we add another dimension by enabling multiple projects. It becomes evident that we are aligned with the OECD standards. Although some categories are not included (such as resource effectivity) since the consortium can not make these claims yet, others are subdivided for a greater potential of differentiation. In terms of weighting and scaling, this framework is special as it is imposing a quantitative evaluation on a qualitative topic and considers the most vital aspects of the overarching project’s goals as more relevant. Thus, this framework has a DLT focus without its criteria titles directly suggesting it.
Conclusion
We developed an evaluation framework which can help to analyze and compare several drafted blockchain projects. It is based on general risk calculation, FMEA, and observations from blockchain projects of the past. Managers can use it to gain insights into the realizability of blockchain projects after the conception of ideas. It has been validated within the consortium and is currently applied for project management and further analysis of the project’s goal of a decentralized IoT marketplace.
References
Dittmann, L. U. (2007): OntoFMEA. Springer-Verlag.
Herd, B., Scharmann, N., and Phelps, S. (2018): Towards the Model-Based Analysis and Design of Decentralised Economies of Things.
Kennedy, M., and Zysman, J. (2016): The Rise of the Platform Economy. Issues in Science and Technology 32, p. 61.
Wüst, K. and Gervais, A. (2018): Do you Need a Blockchain? 2018 Crypto Valley Conference on Blockchain Technology, Zug, p. 45–54
Remarks
This research and development project was funded by the German Federal Ministry of Education and Research (BMBF) within the funding number 16KIS0906 and implemented by the VDI/VDE Innovation + Technik GmbH. The authors are responsible for the content of this publication.
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More information about the iBlockchain research project can be found here.
More information about the Frankfurt School Blockchain Center can be found here.
Prof. Dr. Philipp Sandner is head of the Frankfurt School Blockchain Center (FSBC) at the Frankfurt School of Finance & Management. In 2018, he was ranked as one of the “Top 30” economists by the Frankfurter Allgemeine Zeitung (FAZ), a major newspaper in Germany. Further, he belongs to the “Top 40 under 40” — a ranking by the German business magazine Capital. The expertise of Prof. Sandner, in particular, includes blockchain technology, crypto assets, distributed ledger technology (DLT), Euro-on-Ledger, initial coin offerings (ICOs), security tokens (STOs), digital transformation and entrepreneurship. You can contact him via mail (email@philipp-sandner.de) via LinkedIn (https://www.linkedin.com/in/philippsandner/) or follow him on Twitter (@philippsandner).
Marcel Kaiser is a project manager and research assistant at the Frankfurt School Blockchain Center (FSBC). His expertise is primarily decentralized finance (DeFi) and industrial blockchain applications. He analyzes the impact of blockchain technology on the economy in his master thesis. He speaks at public events about topics like Libra, quantum cryptography, and blockchain in general. Feel free to contact him via mail (marcel.kaiser@fs-blockchain.de), LinkedIn, or Xing.
