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The future for Humana and the insurance industry as a whole (Team 13 DTP)

Introduction

Humana Inc. is a Kentucky-based for-profit health insurance company. With over 13 million customers in the U.S., a reported turnover of US$48.5 billion, and over 57,000 employees, it is the third largest health insurance company in the nation. Humana’s value proposition is to bring health insurance to all consumers of the US at a rate that is at least 15% lower than that offered by the government. However, even with its current success, Humana and the insurance industry as a whole has been lacking in innovation. We propose a solution using smart wristbands in order to create a new service offering for Humana.

Proposed solution

The solution we proposed in our assignment was the introduction of smart wristbands that would monitor the activity, sleep, and potentially the heart rate of the clients in order to offer more accurate prices. Basically, they would be able to engage in first-degree price discrimination with the use of this technology. This addition to Humana’s services would also complement the feature where customers receive bonuses if they live a healthy lifestyle by actually tracking any sporting activity that the customer engages in.

The two wristbands we suggested where the Jawbone UP24 and the Garmin Vivosmart.

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The reason why we suggest using two models as opposed to just setting a standard of one model is that the heart rate monitor is more expensive to add and should be added only if customers have chronic heart conditions or are over the age threshold determined by Humana. This offers the possibility of another service offering: being aware of any episodes that customers with such conditions might have and the potential of alerting the right authorities (for example, an ambulance) to arrive faster than in a usual situation.

To better illustrate the technology itself, we have created a SWOT analysis. This analysis is summarized in the following table:

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Feasibility

When suggesting an ambitious project such as this one, it is very important to consider the feasibility before undertaking any implementation. First of all, we considered the financial feasibility of the project. This includes any significant costs that the project is likely to lead to and is then compared with the revenue of the company in order to see if it would be financially feasible. The costs are summarized in the following table:

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The main costs included were the cost of purchasing the wristbands (where we assumed that they could be bought while benefiting from a bulk discount due to the amount purchased), the cost of setting up a new set of servers in order to accommodate the new amount of data that will be gathered using the wrist bands, as well as the new hires needed. Specifically, the new hires will include a Data Scientist and two Data Analysts in order to take advantage of all the data being gathered and potentially provide new insights. Considering that Humana’s revenue was $41 billion in 2014 it is safe to assume that undertaking this project is financially feasible.

The project is also considered technically feasible, due to these products already being released commercially and tested for these purposes. In addition, legal feasibility is no issue since the Data Privacy Act in the US is not very restrictive and does not hinder the project in any way. Finally, the project is also operationally feasible since it already fits in with the systems that Humana has and can just be offered as a supplement, rather than a completely new offering.

Conclusion

We believe that this project will bring a number of benefits for Humana and at quite a low cost. We suggest that Humana makes sure that the project’s outcomes will follow the plan by first implementing it in a number of areas in order to test out the consumer response.

Humana’s website: https://www.humana.com/

This has been a summary of the Digital Transformation Project written by Team 13, composed of the following members:

Maximilian Wiedmaier – 366864mw
Claudio Corti – 372722cc
Alex Furnica – 375587af
Paul Leonard – 354502pg
Maxim Grgurevic – 372850mg

The rise of the errand boy: crowdsourcing job creation

Crowdsourcing means getting a large number of people to all focus on one task in the hopes that the outcome will be more valuable and successful than the endeavor of one man. As the saying goes: two minds are better than one. Or in this case: hundreds or thousands of minds are better than one. However, most people think this concept is new when actually it started quite a while ago.

Although the term “crowdsourcing” was coined by Wired writer Jeff Howe in 2006, one of the first crowdsourcing projects in the world actually took place in 1714 in England (although Philip of Spain offered a reward for anyone who could solve this problem in 1576). The longitude problem was that, back in that time, sailors had no easy way to calculate the longitude while at sea, causing long voyages to often get lost and result on the death of its crew. Thus, the British government offered £20,000 to the person who could solve this problem, which in the end was John Harrison. Clearly, crowdsourcing is not a new topic. But then why do people think it is so new?

This is because it has only recently become such a rich area of innovation. The concept of crowdsourcing has started to become implemented in very interesting places. Most recently, Amazon has launched its service called Amazon Flex. Most likely inspired by Uber, Amazon allows people to become flexible delivery workers for its Prime service. All you need to get started? A car and a smartphone. Two items which a lot of people own anyway these days. The great thing about services like this is that you are your own boss. You get paid for how productive you are, how much value you bring, as opposed to a set number of hours that you spend in the office.

This could give rise to a whole new area of workers: I like to call them errand boys. These people will most likely choose not to have a stable a job and instead fill their days with various, smaller paid jobs. For example, they could take on a web development job on freelance.com and when they need a break from working in front of the computer, they can take an Uber run. After their Uber run is done, they can potentially deliver a Amazon Flex package on their way home.

Do you think you might work like this someday?

References:

http://arstechnica.com/business/2015/09/amazon-flex-will-pay-you-18-25-per-hour-to-deliver-prime-now-packages/

http://blog.designcrowd.nl/article/202/crowdsourcing-is-not-new–the-history-of-crowdsourcing-1714-to-2010

https://en.wikipedia.org/wiki/Longitude_rewards

Quantum computing: technological holy grail or dystopian nightmare?

Our daily overdose of news shows us the myriad inventions that have the potential to revolutionize industries. One such invention that is subtly appearing, yet gaining fast popularity is the possibility of quantum computers. What is this technology and what is its potential?

As you may know, a classical computer uses binary bits to perform calculations. They are the smallest unit of information in a classical computer and can hold one of two forms: 0 or 1. A quantum bit (abbreviated as qubit) exploits one of the quirks of quantum mechanics, allowing it to be in a state of both 1 and 0 at the same time. This allows multiple simultaneous calculations, which is in complete contrast to current computers. As you can imagine, this means that a fully functioning quantum computer would increase the number of potential calculations by an almost unimaginable amount. There are still many issues which stop quantum computers from appearing in the next 5 years (such as coherence limits, phase errors just to name a few), however researchers are confident that the golden age of quantum computing will arise within the next 10-30 years.

So what does this mean for business?

Big Data and Quantum Computing

The possibilities that quantum computing present are endless. One field that would be impacted by quantum computing and bring huge contributions to the business domain is big data.

Big data is an advancing field, but it is meeting some limitations which have slowed down its rise to glory. Such limitations include:

  • integrating sets that have completely different structures
  • moving large amounts of data efficiently through a highly distributed network

Moore’s law is still in effect but for how long? Already since 2005 has this law still existed only due to changes in processor architecture, since it is not humanly possible to make transistors much smaller than they currently are. At this point, the quantum computer seems to be the only solution on the horizon. As explained above, the significant increase in computational volume would almost instantly solve current problems in the big data domain.

This is just one potential use of quantum computers. There are many more (for example drug discovery and design for pharmaceutical industries). However, can only good come out of quantum computing?

The Quantum Arms Race

Quantum computing could potentially be very dangerous as well. One form of danger it poses is its potential to crack many of today’s used forms of encryption. Should such powerful computers fall into the hands of the wrong people, companies’ records, users’ bank accounts and many more forms of private information could become publicly available. Events such as the Ashley Madison hack could become commonplace.

Even if this prediction is on an extreme level and might not happen, quantum computing will be an incredibly disruptive innovation in an industry that has only benefited from incremental innovations since the Web 2.0. Consider how expensive it would be for a company to replace most of their systems with quantum ones. Would all companies be able to afford such technologies? It is highly unlikely, and yet the corporate giants will upgrade and gain a considerable advantage against startups, potentially stifling innovation.

There is no way to tell if quantum computer evolution will follow the same growth path as classical computers did. Hopefully commercialization will happen faster. At this point in time, all we can do is speculate.

What do you think?

References

http://www.wired.com/2015/09/tricky-encryption-stump-quantum-computers/

http://www.fastcompany.com/3045708/big-tiny-problems-for-quantum-computing

http://www.wired.com/2013/10/computers-big-data/

http://fortune.com/2015/08/26/ashley-madison-hack/