Grisselle Marie Rivera
Ride sharing apps like Uber and Lyft were so disruptive in nature and changed consumer behavior to such an extent that a new type of “sharing economy” seems to have formed around them and similar applications. The key features of the applications are their affordability and the access provided to this type of “on-demand transportation” that essentially became democratized. Despite the widespread use of these apps, their business models may prove unsustainable. According to the BloombergView, “Eighty percent of [Uber’s] $9.7 billion in quarterly revenue was eaten up by a combination of driver payouts and bonuses, along with discounts to riders. Toss in insurance costs, and you’re up to 90 percent—and that’s before spending on marketing, research and development, overhead and so on”. Without the aid of venture capitalists, Uber will be in huge financial distress in the future. However, the firm does not operate as one that is concerned about future financial uncertainties. In fact, Uber is one of the many firms conducting research on and testing autonomous vehicles. Could this be its long-term strategy that will make its business model viable? Will the firm be able to weather these challenges long enough to see its investments in A.I. pay off?
When thinking of technology companies, traditional players such as Apple, IBM, or Microsoft first come to mind, with overlapping and non-overlapping product offerings between them. Amazon, however, has carved a space for itself within this industry throughout recent years. At its inception, Amazon’s IT organization likely served as a necessary utility while also providing business value in maximizing the efficiency of its supply chain which the internet retailer leveraged to associate its brand with quick purchasing and delivery. As Amazon furthers what appears to be a jack-of-all-trades strategy in terms of its business, the firm has produced its own IT-reliant products such as the Echo device and has begun offering IT infrastructure services to both enterprise and non-enterprise clients with Amazon Web Services. By doing this, Amazon transformed its IT Organization into one that more directly generates revenue for the firm (IT ”is” the Business). What makes the firm unique in comparison to the above mentioned competitors, however, is the diversity of its lines of business that also require its resources. Can Amazon compete with other technology companies in the long term while maintaining a competitive edge in its other businesses?
A good example of an institution that could have, and can still, benefit from systems thinking is the United States government, particularly in its approach to foreign policy in the Middle East. In our reading, we learned that systems thinking is especially valuable in situations where the same problem persists or has been made worse by past attempts to fix it. My view on this is not meant to be an oversimplification of the cultural and political influences in the Middle East that are beyond the scope of US government involvement. It is more an observation that historic US involvement in the area can be characterized by huge blind spots in the systems thinking approach. These blind spots are summarized by Jamie P. Monat as “failure to recognize unintended consequences, failure to recognize and understand feedback loops, fixes that fail, poor root-cause analysis, and seeking the wrong goal”(article link). One commonly scrutinized example is the CIA’s involvement in the arming of civilians in the 1980’s to combat Russia’s occupation of Afghanistan. This approach demonstrated a fundamental lack of understanding of the underlying sentiments and values of the nation, leading to a failure to predict what would happen once the objective was met. The unforeseen consequences of this are still felt today, almost four decades later. Since then, the US government has persisted in its interventions in the Middle East with questionable success. In developing future foreign policy it would be incredibly beneficial to incorporate a systems thinking approach to better understand and solve complex problems and avoid unintended consequences.