Andres Perez's Profile

I am convinced that additive manufacturing will have a central role in the future of space explorations. As the article states, 3D printing solves the problem of sending large objects to the space. In fact, in the next decades additive manufacturing will be used to build satellites [1]. For me the biggest benefit of using additive manufacturing in the space is that crewed spacecrafts will have the possibility to build new artifacts that they did not know that they will need before going to the space. Quincy Bean, Principal Investigator for a 3D Printing Project at NASA, says “There is probably not going to be a resupply mission to Mars if they forget something or if they lose something” [2]. I believe that in the short-term the humanity is not prepared for a “space race” and the particular projects of different organizations and countries will be only specific events. Therefore, I think that it is impossible to predict who will win a space race. In the following decades, the countries should enact laws to agree on the ownership rules of the space territories.

[1] Prescouter, “What are the applications of additive manufacturing in space”, https://www.prescouter.com/2017/09/additive-manufacturing-space/, accessed on November 2018.
[2] Motherboard, “3D Printing in space is really hard”, https://motherboard.vice.com/en_us/article/4x3pzn/3d-printing-in-space-is-really-hard/, accessed on November 2018.

I completely agree that nowadays additive manufacturing generates important benefits to manufacturing companies in the automobile industry as well as in other industries and will continue increasing its impact in the following years. In the future I believe that additive manufacturing will be extended to the entire manufacturing process, but to do that it will be necessary to improve the current technology and invest in talent. In the one hand, nowadays the low production speed of additive manufacturing is a key restriction for the application of the technology in plants with a big production volume. On other hand, if the technology improves, companies will have to hire and train employees that will be able to understand and control the machines [1].

Since the future of the processes in an automobile manufacturing factory will be based in additive manufacturing, I believe that companies should develop R&D in-house, since it can be a competitive advantage. They should use the best technologies existing in the market, but at the same time develop their own additive manufacturing technology with focus in their particular needs.

[1] Deloitte University Press, “3D opportunity in automotive industry,” https://www2.deloitte.com/content/dam/insights/us/articles/additive-manufacturing-3d-opportunity-in-automotive/DUP_707-3D-Opportunity-Auto-Industry_MASTER.pdf, accessed on November 2018.

Modernization of states is a process that involves both changes in the structure of the government organizations and adjustments in the talent acquisition process. Although I believe that the proposal of develop more relationships with key stakeholders could help to maintain a culture of open innovation despite having changes of president every 4 to 6 years, I disagree that it is a sustainable initiative.

In other countries the governments have created a “Top public management system” [1], in which the managers of strategic public organizations do not depend on the political party of an elected president. In contrast, the managers are appointed for long-term periods and depend depend on their performance evaluations and therefore can develop long-term initiatives. By creating this type of mechanism in Argentina, the key strategic public managers could foster the open innovation and develop long-term initiatives based on both internal and external crowdsourcing.

[1] Ministerio de Hacienda de Chile. “Sistema de Alta Dirección Pública”. https://www.serviciocivil.cl/sistema-de-alta-direccion-publica-2/, accessed on November 2018.

Although I believe that iFLY has to continue expanding its methods to gather more information for generating high quality ideas, I disagree that the best option is to only expand its external crowdsourcing. I believe that to generate a sustainable business it is a key to balance both the internal capabilities and external crowdsourcing.

For obtaining relevant insights from external sources of information, it is a key to analyze cautiously the information taking in consideration since crowd participants are not always familiar with the company context. Only after a company processes the adequate information, external crowdsourcing allows companies to learn from different and perspectivees [1]. Regarding the internal crowdsourcing it serves as a perfect complement since the participants present more practical ideas and also increase the ownership of employees. In conclusion, I would improve the internal capabilities while increasing the external database only if it gives valuable information.

[1] A. Malhotra, A. Majchrzak, L. Kesebi, and S. Looram. Developing innovative solutions through internal crowdsourcing. MIT Sloan Management Review (Summer 2017): 73–79.

I completely agree that Walmart must use new technologies to remain competitive in the retail market. Machine learning is seen as a key to both increase customer satisfaction and optimize internal processes [1].

I believe that Walmart should focus in both customer-facing process and internal processes. To have a competitive advantage it is important to increase customer experience, but at the same to reduce costs and increase efficiency of internal processes. Although it is true that the main focus of Walmart has been the customer experience, it has also developed initiatives that affect its internal processes. To illustrate, Walmart has introduced robots to facilitate the process of restocking the shelves in the supermarkets. It has been proved that the pilot not only improved customer satisfaction, but also enhanced internal processes by reducing inventory turnover and improving inventory accuracy [2].

Walmart by operating more than 5,000 physical stores has to opportunity to use machine learning in the stores and have direct contact with clients. The self-serve kiosk tower mentioned in the article or the robot to replace inventories are some elements that Amazon cannot deliver to the customers, and then a competitive advantage of Walmart.

[1] Dan Wellers, Timo Elliott, Markus Noga, “8 ways machine learning is improving companies´ work processes.” Harvard Business Review Digital Articles (May 31, 2017).
[2] Retail Dive, “7 Ways Walmart is innovating with technology”, https://www.retaildive.com/news/7-ways-walmart-is-innovating-with-technology/525154/, accessed on November 2018.

I completely agree that machine learning will revolutionize the energy sector. The article describes that machine learning will help operator managers to predict when heat exchangers need maintenance. In a higher-level scale, machine learning, through the information gathered by thousands of sensors, will allow the operators of the electricity system to make better decisions on how to best allocate energy resources [1].

I strongly believe that big energy companies are willing to prove new technologies, despite having risk of losing money. In the one hand, new methods could allow companies to have a competitive advantage such as the reduction of costs of a project for both companies and clients. In addition, energy companies do large capital investments and then the test of new technologies (R&D) is part of their business model. To illustrate, during 2017 Chevron spent $864 million in R&D [2]. However, injuries or deaths of employees are risks that companies will avoid at any price. In general, both the ethical dilemma of exposing workers to hazards and the possible reputation damage, have led companies to put safety as a central pillar.

[1] Franklin Wolfe, “How artificial intelligence will revolutionize the energy industry.” Harvard Business Review Digital Articles (August 28, 2017).
[2] Reuters, “Chevron Corp”, https://www.reuters.com/finance/stocks/income-statement/CVX?stmtType=INC&perType=ANN, accessed on November 2018.