Evaluate the nine component model of doing business by applying the canvass approach.
Starsky Robotics is an autonomous trucking firm that is designed to manufacture driverless trucks in the market. Stefan Seltz-Axmacher who is the CEO and Kartiwik Tiwari, a co-founder wish to bring a solution to the logistical primary challenge in the trucking industry through having drivers move off the road and start working in offices. The company started in 2015 in Detroit, California and has 20-30 workers and 15 investors (Price, 2017). The firm has so far raised, over $3.75 million after making the Y combinatory, Trucks VC, Sam Altman data collective including various other investors uses a dual approach. It uses a software, computerized vision cameras, and radar to enable long haul trucks to move autonomously in the highway. The trucks then turn the driving job over to the trained drivers with the use of remote controls to take the trucks from the exit to the end destination.
The company is a startup for self-driven trucks which uses a business model combination and technology that makes the trucks autonomous by having them move on the highway without the need of a driver. However, the trucks get remote controlled to switch from the self-drive mode to that of a physical driver during the beginning and end miles. This model is quite different from the one applied in self-driving trucks from Otto and Embark firms that are also in the industry.
The company applies the nine building blocks as designed by Osterwalder & Pigneur’s (2010). The Starsky robotics applies the building blocks as per the building block canvas provided.
Customer segments
The company products which include the driverless trucks include such companies that depend on heavy commercial trucks for transporting bulky goods to other destinations. Other customers include transport companies like the Uber Taxis which transport people and goods using an online technology to identify customers. Many companies are also eyeing this move in highway technology as they strategize to reduce costs of operation by reducing the number of drivers for their trucks and replace them with technology.
Key partners
The company is entirely based on technology and makes use of the social media platforms to communicate their developments in designing the self-driven trucks. For instance the company has over 455 followers in twitter who increase by 3.4% monthly and 9.1% quarterly and more than 479 likes in its Facebook page who grow by 3.7% monthly and 8.5% quarterly (Poorsartep, & Stephens, 2015). The company is also depended on websites such as Webflow for designing purposes, the lever website for hiring, the gandi.net hosting to host its products and Openresty for servers, storage and networks. The company depends on these technological strategies to market and develop its popularity in the market.
Value proposition
The company was started with a view of achieving the following outcomes;
To automate the logistics industry by replacing the driver trucks with technological self-driven trucks for commercial purposes.
To help heavy commercial companies to reduce the cost of hiring people as drivers
To embrace the aspect of technological development in coming up with trucks that do not need people as controllers.
Key activities
The company is currently dealing with the manufacture and sell of heavy commercial trucks that are self-driven. Initially, the company began as a manufacture of heavy delivery trucks and other trucks (Fagnant, & Kockelman, 2015). The company is now involved in making improvements on the self-driven trucks to improve its workability on the road and see how the physical drivers could be got rid entirely.
Channels
The company has so far made a name locally especially in San Francisco where it has its headquarter office and Florida where the first unmanned truck tested the road autonomously. Currently, the company has not yet hit on the global market but through its efforts the company is first trying to sell some of the driverless trucks locally (Shladover, 2018).
Revenues streams
The estimated revenue annually, for the company is about a $1M. The company has a funding history that includes $3.8 M in 2017 that is unattributed that came from Y Combinator and some $16.5M in 2018 collected from Y Combinator, Shasta ventures, Fifty years and trucks venture capital (Jamasmie, 2009). The total revenue by 2018 was $20.3M
Cost structure
From the table it is notable that, values have an increasing trend from series A2 towards series A9. The table represents data for series A2 and A3 which indicate this trend. Currently the company is in its series A9.
|
Stock |
No. of shares authorized |
Par. Value $ |
Dividend rate in $ |
Original price issue |
Liquidation $ |
Liquidation preference value |
Conversion price value $ |
Percentage owned |
|
Series A3 |
140,013 |
0.0011 |
0.051 |
0.791 |
0.790 |
1x |
0.791 |
0.75 |
|
Series A2 |
134,684 |
0.0011 |
0.041 |
0.740 |
0.741 |
1x |
0.740 |
0.53 |
Key resources
The company resources include elements of manufacturing, logistics and transportation departments. The company has a lot of trucks including the ones that are driverless. All its resources are found locally in the U.S since the company is yet to go global. This year marks its first to successfully launch the autonomous trucks on the road.
Customer relationships
The company is entirely relying on its media platform followers as the number one customers. There are various customer companies in the local market that include Uber who have so far shown interest in some of the driverless by purchasing automobile trucks from Starsky robotics (Verevis, 2005).
Interrelations among the nine blocks
The company has integrated its operations by having many partner companies that have interest in the autonomous vehicle industry which have same efforts of manufacturing the driverless vehicles including the heavy commercial trucks. The various partners include the Hone capital company, fifty years funding company, hemisphere ventures, Point-nine Capital Company and Grishin robotics (Slowik, & Sharpe, 2018). The customer segments of the company include transport and haul business operators such as Uber Company. The operations of the company are supported by the business channels which start from the local market in California and Florida as more branches are to be opened in the near future. The manufacture of autonomous vehicles has created its revenues streams including the $21.3M. The revenue has been raised from the company resources that include the manufactured trucks sold to the local customers in the U.S. the cost structure identified explains ways of raising capital to cater for cost of manufacture that mostly comes from the shares of the various partners and sale of first driverless trucks.
Critical factors of success
The company was started in 2015 as a logistics and truck manufacturing company by Stefan Seltz-Axmacher who is the CEO and Kartiwik Tiwari, a co-founder. In 2017, the company had the idea of autonomous driverless trucks and managed to create a seed of $3.8 M and by 2018 created a total funding of $20.3M (Hrdy, 2017). The company seems to be growing very first with the following factors of success coming into play. First the company uses technology to support its innovation. The idea is to move with changes in technology and create machines which depend not on the efforts of humans. This innovation attracts the world. It calls investors from all walks of life including bigger companies to invest in the technology (Otmazgin, 2014). The other factor is partnership. The company partners with various companies who include fifty years funding and Y Combinator to raise funds to keep the company standing. This enables the partners to share the costs of operation in the company. Innovation and creativity is also a contributing factor since the autonomous trucks can only function through well-designed manufacturing and high-tech efforts.
Downside risks
The company is faced by various risks that include both financial and non-financial risks. Financial risks include market risk for instance, the number of competing companies in the autonomous automobile industry. Though the company has already taken one truck in the market, other companies have the same idea and can outdo Starsky robotics in the game. The other risk involves operational risks (Bartlett, 2018). The company wishes to remove human aid in the driving of the trucks entirely, an aspect that leaves many wondering whether they would be able to solve the problem of accidents on the roads. Technology risk is also a potential problem based on the fact that robotics cannot entirely work alone without the eye of humans since there are areas where human assistance would be needed to keep things in the right track.
Business model change
Considering the above technological achievements of the company, it can be said that the company has shown the potential of fully coming up with trucks that need no human control (Geiger, Lenz, & Urtasun, 2012). The company applies a combination of technology and business model in operations. If I were to work in the company, I would ensure that the company operates in specific roads that have no traffic for the time being before completely letting the autonomous vehicles on the highway without anybody manning them. This is to avoid and reduce the cases of a potential accidents occurring. However, it needs to have its operations insured so that in case of major accidents, the company does not risk going back to its downside level. The company also needs to partner with as money companies in the industry to spread the risks.
Conclusion
The Starsky robotics can be said to have made a technological step ahead of competitors in their manufacture and design of autonomous self-driven trucks that can haul goods for long distances. They have reduced the complexity of drivers being in control of the trucks for long distances which makes the transport so much exhaustible to the point of accidents being evidenced. The goal towards a technological controlled highway is almost about to be achieved. A mix of business and technology models has kept the company going towards the positive side.
References
Bartlett, J. (2018). The People Vs Tech: How the internet is killing democracy (and how we save it). Random House.
Fagnant, D. J., & Kockelman, K. (2015). Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transportation Research Part A: Policy and Practice, 77, 167-181.
Geiger, A., Lenz, P., & Urtasun, R. (2012, June). Are we ready for autonomous driving? the kitti vision benchmark suite. In Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on (pp. 3354-3361). IEEE.
Hrdy, C. A. (2017). Technological Un/employment.
Jamasmie, C. (2009). Lonely trucks in a lonely place: Autonomous trucks debut in Chile’s desert. MINING. COM a mine of information, 2, 23-24.
Osterwalder, A., & Pigneur, Y. (2010). Business model generation: a handbook for visionaries, game changers, and challengers. John Wiley & Sons.
Otmazgin, N. (2014). A regional gateway: Japanese popular culture in Hong Kong, 1990–2005. Inter-Asia Cultural Studies, 15(2), 323-335.
Poorsartep, M., & Stephens, T. (2015). Truck automation opportunities. In Road Vehicle Automation 2 (pp. 173-185). Springer, Cham.
Price, D. A. (2017). Robots for the long haul. Econ Focus, 1, 13-15.
Shladover, S. E. (2018). Connected and automated vehicle systems: Introduction and overview. Journal of Intelligent Transportation Systems, 22(3), 190-200.
Slowik, P., & Sharpe, B. (2018). Automation in the Long Haul: Challenges and Opportunities of Autonomous Heavy-Duty Trucking in the United States. Working Paper, (2018-06).
Verevis, C. (2005). Commerce. In Film Remakes (pp. 37-57). Palgrave Macmillan, New York
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