Disruptive Innovation Case Study: Robotic Surgery – Da Vinci Surgical System / 2018 / Dr Jason Watson

Executive Summary:
On the authority of Lanfranco, Castellanos, Desai, and Meyers (2004, p. 14), a significant promise is held by surgical robotics which has appeared as a brand new disruptive technology. As claimed by most of the scientist, robotic surgery is often addressed as a new revolution or a new trend, and it is undoubtedly one of the most critical and controversial subjects in operation today. At this stage, although people always discuss it regarding future market, however, it is also necessary to look at the development of these robotic devices and to explain more in-depth as robotic surgery will become a critical application and this technique is still evolving in the surgical armamentarium.

This essay will firstly introduce robotic surgery regarding its definition and history. Then, it will explain why robotic surgery is a disruptive innovation. The next part is using the diffusions of Innovation theory which stated by Everett Roger to indicate how this innovation: robotic surgery can be divided into 5 group in theory. Thirdly, analysing robotic surgery by applying DSR evaluation methods selection framework. The fourth section is evaluating their design and giving appropriate strategies to the innovation. Finally, Business Analytics will provide insight with supporting the efficient management in the end.


1. 
Describing Robotic Surgery
1.1 Introduction of Robotic Surgery:
According to Tan et al. (2016, p. 4330), robotic surgery has been applied to medical treatment for almost 30 years, and the scientists draw an advantageous conclusion to indicate that robotic surgery has contributed positive outcome in the clinical research. Although the more extended operative period is still considered as a single drawback, however, robotic surgery showed the promising potential as a disruptive technology, and it achieved high-quality performance for the patient in healthcare technology. As more large investments have been made in the research of robotic surgery, it is evident that this shortcoming will be improved soon in the nearly future. As a result, advanced surgical robots have been demonstrated its potential and importance as a disruptive innovation not only to accelerate lengthy operative procedures but also to provide excellent operative precision which can generate refined clinical outcomes and substantial corporate revenues. Da Vinci Surgical System is just one of the outstanding examples of robotic surgery.

Why is robotic surgery a disruptive innovation? According to Christensen, Raynor, and McDonald (2016, p. 4), the theory has been misinterpreted generally, and they addressed several points to explain it. 1. disruption is a process. 2. disruption produces the business model. 3. disruptive technology does not always succeed. Robotic surgery does meet these three requirements. First of all, the development of robotic surgery is a long process, it primarily appeared with the first pioneering clinical application of PUMA 560 in 1985,  then the surgical robots have kept evolving and refining after three decades until today’s Da Vinci Surgical System (Tan et al., 2016, p. 4347). Secondly, in this evolution of robotic surgery, it also produces a great business model since comparing the first prototype of robotic surgery which is limited to some certain patients in the past, today, the patients in the hospital worldwide have easy access to Da Vinci Surgical System. The market of robotic surgery has been growing expeditiously, as reported by GlobalData (2018), the global robotic surgical systems market is expected to grow 13.5 per cent annually and reach a market size of $2 billion in 2024. Thirdly, robotic surgery is still developing and has been criticised concerning lengthy operative period and its high cost. Thus, this scenario suits the third condition, there is still room for improvement concerning footholds the of low-end or new market (Christensen et al., p. 5).

1.2 Exploration of Adoption Categories:
Since innovation is a fascinating tool and has a huge impact on our mordent lives, therefore, we have accountability to know more detail about how does change get adapted. As claimed by Everett Roger (1962, pp. 249-250), the author of the Diffusions of Innovation theory, five stakeholders of groups are proposed to explain how innovation get adapted over time by different cohorts. These cohorts can be divided into 5 group by investigating their characters. These five categories of innovation adopters are: Group 1: Innovators, Group 2: Early Adapters, Group 3: Early Majority, Group 4: Late Majority, and Group 5: Laggards. The following table describes the name of the adopter category and how robotic surgery fit into the various scenarios (Rosemann, 2015).

●       Name of Adopter Category Describe the typical type of person likely to be in this category
Group 1:
Innovators -Venturesome
 
These are the 2.5% people who are willing to risk their lives to try robotic surgery. However, in theory, it is impossible to risk patients’ lives to explore the feasibility of robotic surgery. This is still in the test process and the patients need to wait for qualification of robotic surgery to be approved.
Group 2:

Early Adapters – Respectable

 

These are around 13% people who are the second wave and waiting for the initial first pass over. In this time, the product is maturing in its abilities and they get pleasure and satisfaction to purchase the products. For robotic surgery, it seems that theoretical and practical researches have been conduct well. Although there is still in the test process, the outcomes are very positive. Most of the patients have started accepting this new innovation and it seems that robotic surgery is helpful to assist doctors to perform operations.
Group 3:

Early Majority – Deliberate

 

These are the 34% people who take action when the product becomes widely known and mainstream. In this step, performing the robotic surgery is common and it has been widely used for the medical purpose. The qualification has been approved for a while. The patients generally are aware of this innovation and the researchers attempt to refine the robot regarding the accuracy and efficiency of clinical surgery.
Group 4:

Late Majority – Skeptical

 

These are the fourth group of people which presents 34%. They are more cautious in believing the products’ successes. They typically wait for reviews of robotic surgery before they consider to accept. For example, some patients

would like to wait until the surgical fee is decreased. Then, they have a opportunity to get discount or they want to have risk-free operation. It is understandable that medical treatment should have zero tolerance policy.

Group 5: 16%

Laggards – Traditional

 

These people are the final group and presents 16% of people. They are reluctant and do not prefer innovation and they are content about traditional surgical treatment. For example, some patients refuse robotic surgery. As long as traditional treatments are existing, they are satisfied with it already.

If we unite these five group of Diffusions of Innovation theory into a timeframe and according to their percentages, it will form a ball curve in a graph. However, if we accumulate this information across the ball curve altogether, it will become the well-knows-curve. This s-curve points out how innovation is related to the speed of adaption. In my opinion, the three most relevant innovation characteristics for this category of adopter which relate to Roger’s five innovation characteristics can be divided into three stages: the first stage: Prototype, the second stage: Maturing, and the final step: Refining. The table below explains why I selected these three critical features and justified the reasons how innovation is adopted regarding the speed of adaption and lists several stages.

●       Order of Priority Explanation (2-3 sentences sufficient) justifying your decisions
The first stage:

1. Prototype

There is a low growth, but many trails, errors and prototypes of many entrepreneurs and Stat-up companies. The most of innovation will never see the light here. These are the patients who are willing to risk and it is the first significant element of innovation. Without these  pioneers to test and to explore, the initial prototype of robotic surgery will not be fulfilled. Therefore, this first step is crucial to launch the primary prototype study.

 

The second stage:

2. Maturing

There is a exponential growth at this stage. There are already some solutions here. For example, the terminology has emerged, such as robotic surgery and surgical robot system. It is also called: Innovative Disruption. These are some patients who are the second wave and waiting for the more qualifications of robotic surgery to get approved. In this time, robotic surgery is maturing in its performance. The market started promoting this innovation to be widely known.

 

The Final stage
3. Refining
There is a slow growth here, and there will be no significant change in the stage. Considering robotic surgery as an example, the system has been well developed and it is mature enough to be widely accept. The high cost of robotic surgery is one of the problems which needs to be solved. Also, the medical researchers attempt to refine some tiny technical issues with it.

 


2. Retrospective Analysis of Robotic Surgery
2.1 Evaluation of their Design:
On the report of Venable, Pries-Heje, and Baskerville (2012), Design Science Research (DSR) plays a relevant role in researching some evaluating activities. However, since little guidance is provided in DSR literature, building evaluation strategies is critical. In light of this issue, the author proposes an enlarged DSR evaluation framework along with a DSR evaluation design method which assists the researchers to select a proper way for evaluation of the design artefact and design theories which generate the outcome form DSR. Consequently, the authors developed three extensions of comprehensive framework and method for designing the evaluation which can be applied to a particular Design Science Research (DSR) project. The following table indicates the second extension which pointed out a chart of evolutionary strategies to critical evolutionary methods (Venable et al.,  2012).

If there are no limitations of time and resources, artificial methods of evaluation is recommended for both Ex Ante and Ex Post For an Artificial Ex Ante (Before) phases of evaluation, since the users and problems are unreal in the period and a surgical system is existing. Moreover, the conducting the research is fast by applying this method, and it has low-risks to the participants who are current patients in the hospital. Also, it is suggested to use two methods of Criteria-Based Evaluation and Computer Simulation. One of the reasons is that Criteria-Based Evaluation uses score guides which can be utilised to measure the surgical robot’s performance and to enable researchers to separate standardised surgical objectives into small segments, In the end, evaluating the entire system’s performance on the fundamental range of criteria. Another reason is that Computer Simulation produces a great deal of useful mathematical models for robotic surgery system and the researchers can gain insight into the operation of systems. For an Artificial Ex Post (After) phases of evaluation, it is recommended to use two methods of Mathematical Proof and Role Playing Simulation. The reasons are that Mathematical Proof enhances the accuracy and the effectiveness of the surgical system and Role Playing Simulation can be used for patients in the simulated scenario to collect data for real surgery. It helps the researchers to build the potential database for the future.

DSR

Evaluation Methods Selection Framework

Ex Ante      (Before) Ex Post (After)
Artificial Criteria-Based Evaluation:

Using  score guides to measure the surgical robot’s performance and to enable researchers to separate standardised objectives into small segments.  Evaluating the entire system’s performance.

Mathematical or Logical Proof:

It is paramount important because It can be used to enhance the accuracy and the efficient of system concerning robotic surgery.

 

 

Computer Simulation:

It produces a great deal of useful mathematical models for robotic surgery system and the researchers can gain insight into the operation of systems.

 

Role Playing Simulation:

It can be used for patients in simulated scenario to collect data for real surgical performance. Thus, the database can be generated through it.

 2.2 Evaluation of original Entrepreneurship and Start-Up Potential:

Assuming that an IT start-up company is about to introduce the disruptive innovation: robotic surgery, considering the strategies from the lecture, I think the following three approaches are the most applicable due to the different reasons which are listed below. The three recommendations are 1. Social media and online communities, 2. Cloud-based solutions, and 3. Virtual Agents.

  1. Social media and online communities:

Social media and online communities are particularly significant for larger businesses, such as robotic surgery. The patients and the medical researchers can use its internal and external channel to communicate with each other. The online community is influential because it has a considerable impact on the market and it can be used as the marketing strategy to promote the convenience and improvement of robotic surgery to the public as well. Successful marketing is influenced by their powerful social media and online communities in order to gain the trust from the customers. However, the challenges also emerged which include excellent management of community, encouraging contributions and commitment from the users, and starting having network effects with other members online.

Virtual Agents is originated by the computer system with supports of artificial intelligence (AI) system. Virtual Agent also provides services for online customers representative, and it produces an intelligent communication with all the users who address their questions and receive answers through the computer system with non-verbal behaviour (Chatbots.org, n.d.). The main reason for using virtual agents is that robotic surgery will combine with a great deal of extensive data and artificial intelligence to assist the surgeons to perform a successful surgical task. This is indeed a future-oriented trend for development of robotic surgery which will particularly connect with database and AI altogether. If a virtual agent is guiding a customer, it is better to transfer them to a real agent later

2.3 Evaluation of their Application of Business Analytics
2.3 (a) designing the innovation
In my opinion, the organisation which innovated robotic surgery will benefit from business analytics. Firstly, it is suggested that reducing the cost of robotic surgery is one of the essential requirements to meet. If a company can reach an agreement with the potential customers regarding the high cost and hefty fees, robotic surgery will become a real disruptive technology and replace enormous surgical tasks which performed by humans. It is also predicted that robotic surgery would happen not only in the hospitals but also in the individual clinics, as it is getting popular and accessible easily. The ultimate goal of robotic surgery after several generations will be a possibility to perform robotic surgery at home with virtual agents and artificial intelligence (AI) together. At that time, the Da Vinci surgical system might be similar to Smartphone regarding its convenience and popularity.

2.3 (b) supporting the efficient management of the innovation
The issue with robotic surgery is addressed as its high cost. However, there are more problems related to this innovation. The safety issue is the first crucial problem which needs to be solved. For example, there are few reports about the potential dangers of robotic surgery. Some critics indicated the accidents happened in the clinical surgery. It is one of the shortcomings which require a lot of researches to improve.

Secondly, as literature reviewed, longer operative time is the primary concern with this technology. Reducing the operative time will be beneficial to the clinical surgery. More researches are demanding to achieve this standard requirement. The customer service is also significant because it is about the reputation of robotic surgery and it could ruin the market if the status is not good enough. In addition to that, an efficient customer relationship plays a relevant role in the market. For the medical purpose, it is zero-tolerance for the clinical surgery. 100 percentage safety is basic fundamental, and more accuracy and improvement is needed to promote this technology.

Conclusion:
In conclusion, as Lanfranco, Castellanos, Desai, and Meyers (2004, pp. 14-15) briefly reviewed the literature to explain the definition, history and contemporary development of robotic surgery. Firstly, they have introduced that robotic technology is an advanced and rapid rising innovation which is replacing the humans’ hands and enhance the profession massively. Today’s robotic technology accomplishes a great deal of difficult tasks which are immensely specific, extremely precise, and highly risky in the industries. Secondly, robotic surgery is one of the examples of robotic technology. Historically, although the robot has been slow to reach the medical industry, the development of the application are outstanding. Da Vinci surgical system is one of the examples of Robotic surgery product, and it is highly recommended to keep observing this disruptive technology in terms of its potential market and its widespread prevalence in the future.

Appendix 1: Reference:
1. Christensen, C., Raynor, M., & McDonald, R. (2016). What is disruptive innovation? Harvard Business Review, 2015(December), .

2. Chatbots.org. (n.d.) Virtual Agent. Retrieved from https://www.chatbots.org/virtual_agent/

  1. GlobalData. (2018). da Vinci Leads the Way in Global Robotic Surgical Market, Data Show

Retrieved from https://www.mpo-mag.com/contents/view_breaking-news/2018-01-15/da-vinci-leads-the-way-in-global-robotic-surgical-market-data-show

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