Delivery Inc.* is one of the main players in the parcel delivery market in the European country Oceania*. More information about the company and the market that it operates in can be found in this video. Delivery Inc. operates on the territory of three European countries and works with its international partners to provide courier services worldwide.
The company has a market share of around35% and its primary target group is corporate clients. Delivery Inc. focuses strongly on IT in order to ensure the highest quality services for its customers. Delivery Inc.’s information strategy is aligned with its current business strategy. The company brings value to customers through complex software solutions that help to deliver its business objectives. It uses an advanced ERP system to manage and coordinate orders, issue documents, and delivery schedules. Furthermore, the company’s main focus is courier service with an emphasis on expanding the range of its services and network, which is achieved through automated parcel stations. The main source of revenue for Delivery Inc. is its courier services, which account for 93% of the total 11m euros. Corporate customers are the majority users of its services, accounting for 88% of the total revenue.
Due to the fierce industry competition in combination with market growth trends as well as the increasing demand for timely and convenient solutions, the courier company needs to find new ways to respond to the changing nature of e-commerce and logistics industries. The main competitor of Delivery Inc. is Post Delivery* which has a very different business model. It uses franchise agreements and thus is able to provide a far larger network to better serve its main target group – individual clients. In terms of delivery time, Post Delivery scores higher than Delivery Inc.
To keep up with worldwide market trends and to gain a competitive advantage over its main competitor, the company needs to implement a new technology solution for real-time predictive delivery. This change will impact its operations, cost estimates and potentially will improve customer satisfaction, helping the company keep its market leader position.
We propose the company to implement a real-time predictive analysis software (RTPS) that will design the route of the courier in a way that guarantees every parcel to be delivered within a particular two-hour time frame which will be communicated with the customer prior to delivery. A two-hour time frame is chosen because this is the benchmark in the industry when such process is initiated for the first time. The RTPS should be implemented within the current operating software network. The idea is to use historical data about the Delivery Inc.’s operations and customers and combine them with real-time data, such as weather conditions or traffic congestion. RTPS will support employees by drawing the best possible route of the courier based on operational capacity and courier availability in the given region.
This solution will bring some risks, additional costs and efforts along with its benefits. The main associated risk is the possibility that the data stored by Delivery Inc. may not be sufficient to implement an optimal algorithm. However, the expected benefits will bring a significant value added for the company, thus it is highly recommended for the company to consider the proposed solution.
*Please note that fake names are used for this project to protect the company identity.
The Big Brother (Google) is Watching You
4
October
2016
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Source: Vordaan Advocaten
Imagine it’s 1984. The Big Brother is watching your every step and controlling every aspect of your life. You live in the totalitarian state Oceania where every citizen is under constant surveillance. Sounds familiar?
In 2016, the narrative described by George Orwell in his famous novel “1984“is still relevant but for different reasons. In the past, the role of the Big Brother was played by political parties and figures while today – the Big Brother is represented by large corporations with access to huge amounts of data. Such companies are Facebook, Google, Amazon and others, but this blog post will focus on Google.
Google
Google can possibly track one’s every movement online as one of its products is the most popular search engine, taking 73.02% of the global market share (NET Applications, 2016). According to Wikipedia, there are about 100 Google apps available on Google Play, although some of the apps might no longer be active or might have different names. As of 2016, Google has 7 products with more than 1 billion users: Gmail, Android, Chrome, Maps, Search, Youtube and the Google Play Store (Popular Science, 2016). I mean, this is the amount of world population using these 7 products!
All the information from these 100 apps and billions of users gets accumulated and stored by one company. All Google apps and products are interconnected so that the company can make use of the large amount of data for statistical purposes as well as to get customer insights by storing the information from each individual separately. Thus, information from all products is stored at a person’s Analytics account. By joining data sources, the tech giant is aiming at providing better and highly customized services.
Find out more about data privacy concerns from the following video featured on CBSN.
Customer- centric
Google is customer- centric indeed, but who is the customer? One would probably think that Google serves individuals and companies for free or for a very small fee. Although the tech giant does provide some of its services and products for free, it actually earns 95% of its revenue from advertising. This is how it works – AdWords enable advertisers to publish ads on Google search results pages as well as on the websites of Google affiliates (AdSense publishers).
Initially, Google management thought that revenue will come primarily from licensing and providing Internet services. However, as technology evolved, Google started using auctions technology to allocate ads, and thus completely changed its business model. So technically speaking, people are tools for acquiring revenue, and companies using the advertising services are the primary customers of Google.
Google Might Create a Problem
One problem that has been caused due to Google’s business model is personalization. Google claims that customization helps it better tailor ads and information to one’s needs. However, in the future, people might get more polarized as Google blocks their access to diverse opinions, i.e. as people fall in the so-called filter bubble. Since Google personally tailors results, two different people who search for the same word or phrase would get different search results. For example, as democrats tend to lick more on links with news about democratic views and democratic politicians, and republicans do the same – each group will get search results based on their interests and thus not have access to other opinions.
Find out more about the filter bubble issue in the following TED talk by Eli Pariser.
Google Might Create a Solution
On the other hand, a problem that Google can solve is the information asymmetry. Imagine that you are using the Google Fit app and Google starts selling health insurance companies people’s data. Health insurance companies would know how healthy one is and would be able to better predict diseases and potential health-related expenditures. This solution would reduce the information asymmetry, but it will also pose some security, privacy and ethics questions. Although currently the company does not provide personal information to third parties, there is no guarantee that it will not start doing it in the future.
Conclusion
The Big Brother will keep watching you and will keep collecting data about you. Sometimes its actions will favor you, sometimes they will favor corporations and/or other people. Although Google provides technological platforms, the data and decision related to the data usage pose ethical questions. As Google algorithms evolve, they might start making ethical decisions. But as people are not impeccable, and machines are made by people, machines can’t be errorless. It is indeed interesting to see how far Google and its algorithms can get.
Here you can find out more about the type of information that Google has potentially stored about you and where it is located.
Sources:
“Big Brother Google Is Watching You!”. Voordaan.com. N.p., 2016. Web. 4 Oct. 2016.
“Google Ads Case Study Analysis”. Ecommerce-digest.com. N.p., 2016. Web. 3 Oct. 2016.
“Google Has 7 Products with 1 Billion Users”. Popular Science. N.p., 2016. Web. 2 Oct. 2016.
Stiles, Jackson. “Google Is Watching: Find Out What It Knows About You”. The New Daily. N.p., 2014. Web. 4 Oct. 2016.
“The End Of Privacy “The Data Brokers: Selling Your Personal Information””. YouTube. N.p., 2016. Web. 3 Oct. 2016.
Technology of the Week – from Public Contribution to Price Discrimination – A Debate over SAS vs. R
29
September
2016
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The information goods market has experienced a substantial change during the past decade. A lot of new platforms and products have emerged that differ in terms of user interface, cost structure and content. Among the information goods with growing importance are data analysis software programs – platforms that are able to perform complex operations and process tremendous amount of data. The most widely used data analytics tools are SAS and R. The subsequent paragraphs examine and compare differences between the two programs, followed by a prediction for the two products’ prospects.
R Programming Language
R is an open-source programming language used for developing statistical software and data analysis. Since its establishment, it has gathered an entire community of professionals and academics that contribute to its development. Consequentially, the platform is also used by a growing number of data analysts who are part of corporations or academia. One of the greatest advantages of R is that it is open to innovations. Due to its open source nature, the program offers few barriers to entry for new techniques. An individual who develops a new technique can quickly incorporate it, even if the updated version has only niche appeal. This is a great example of the long tail effect in action.
SAS Analytical Tools
The main competitor of R is SAS, a proprietary software suite developed by SAS Institute. By using SAS, users are able to perform a number of different tasks such as report writing, data visualization, operations research, project management and more. This sophisticated data analysis software empowers enterprises by helping them gain valuable insights into their businesses. Another crucial benefit of SAS is that support is provided by experienced master’s- and doctorate-level statisticians who deliver a level of service and knowledge not often found with other software vendors.
SAS vs. R – Pricing Strategies
Besides the above-mentioned dissimilarities, the two programs also differ in their pricing strategies. There is no business model behind R as it was developed for academic purposes, while SAS is a product of a for-profit organization. The incremental total cost of ownership to download, install and use R is zero. It’s completely free which provides a great opportunity for start-ups and companies looking for cost efficiency.
On the contrary, SAS is price discriminating and targeting mostly large companies. SAS achieves higher profits through bundling and generates high marginal revenue from any additional feature a customer buys. SAS Institute has high costs to develop and update the platform but its reproduction costs are modest. For example, the SAS basic package starts from several thousand dollars, a lump sum that customers pay for the first year and every additional year they pay a subscription fee of only 30% of the initial cost. The longer the customers keep the software, the higher amount of the sunk costs they will recover. Most of the products can be divided into countless modules, once the customers configure their bundle, they can request a personal quote on SAS website or negotiate the price with one of the SAS representatives. This approach would not have been possible in the past when customers had to go to a physical store and buy a CD with the software for a fixed price.
Prediction for the Future
Taking into consideration the above-mentioned differences of both programs, it seems that R has the potential to outpace SAS in the future. The open-source platform is more agile to innovation and “cutting-edge” techniques. It keeps gaining more recognition among
academics that directly translates into more graduate students with R programming skills. Due to the fact that SAS Institute offers too many different interfaces, SAS tools tend to be more difficult to integrate. On the other hand, R poses a risk of delivering inconsistent and unverified packages as there is no governing body to assure content quality. Moreover, R is vulnerable to the discretion of the community to contribute. At some point, the community may lose interest and the platform could vanish. This scenario provides an opportunity for SAS, however, SAS needs to keep up with the speed of technology advancement to preserve its market leader position.
Here you can find a link to the video we created on this topic.
References:
Bansal, Sumeet et al. “SAS Vs R Vs Python – Analytics India Magazine”. Analytics India Magazine. N.p., 2016. Web. 20 Sept. 2016.
Burtch, Linda. “SAS Vs R Vs Python: Which Tool Do Analytics Pros Prefer?”. Kdnuggets.com. N.p., 2016. Web. 19 Sept. 2016.
Dinsmore, Thomas. “2015: Predictions For Big Analytics”. The Big Analytics Blog. N.p., 2015. Web. 18 Sept. 2016.
Dinsmore, Thomas. “SAS Versus R Part Two”. The Big Analytics Blog. N.p., 2014. Web. 19 Sept. 2016.
Python, Infographic:, Infographic: Python, and Manish Saraswat. “Infographic: Quick Guide On SAS Vs R Vs Python”. Analytics Vidhya. N.p., 2015. Web. 18 Sept. 2016.
“R Statistics And SAS Statistics Job Trends | Indeed.Com”. Indeed.com. N.p., 2016. Web. 18 Sept. 2016.
R vs SAS, why is SAS preferred private companies?. “R Vs SAS, Why Is SAS Preferred By Private Companies?”. Stats.stackexchange.com. N.p., 2016. Web. 20 Sept. 2016.
Rita L. Sallam, and Josh Parenteau. “Gartner Reprint”. Gartner.com. N.p., 2016. Web. 17 Sept. 2016.
SAS Institute Inc.,. SAS® Does Data Science: How To Succeed In A Data Science Competition. 2015. Print. Paper SAS2520-2015.
“SAS Vs. R (Vs. Python) – Which Tool Should I Learn?”. Analytics Vidhya. N.p., 2014. Web. 19 Sept. 2016.
“The Popularity Of Data Analysis Software”. r4stats.com. N.p., 2012. Web. 17 Sept. 2016.
“Why Is SAS Insufficient For Me To Become A Data Scientist? Why Do I Need To Learn Python Or R?”. Quora. N.p., 2016. Web. 18 Sept. 2016.
The Future of Fintech – Collaboration or Cannibalization?
29
September
2016
4.92/5 (12) Source: Fintech Investment Financial Internet Technology Concept
According to M. Porter: “the “new economy” appears less like a new economy than like an old economy that has access to a new technology” (Porter, 2001). While this statement may be true for some industries, it is not entirely valid for the banking sector which got completely transformed through IT advancements during the last 30 years.
Before the advent of digital computers and the rise of the Internet, employees in financial firms had to keep record of all transactions on paper. Job hunting and advertising efforts were being conducted through newspapers. Nowadays every single bank department is transformed – through the introduction of various software programs, the Internet and IT enhancements in general (both software- and hardware-wise). Consequentially, new processes, jobs, and business models are continuously emerging.
Fintech
IT has helped financial institutions offer higher quality services and convenience, creating a potential for collaboration and mutual profit. There is a buzzword to describe the phenomenon – fintech.
But what gives fintech companies an advantage over traditional market players? The trick is that IT companies can engage in the banking business without having to go through strict regulations and complex processes. Exactly this window of opportunity threatens the old-fashioned and traditionalistic banks and favours technology firms.
So what new business models will emerge from the recent technology disruption? There are two major scenarios: banks will get stronger and improve their reputation through collaboration with tech companies or technology companies will get greedy and eventually start eating up bank’s market share.
Scenario 1: Collaboration
The sweet spot called fintech offers new opportunities for collaboration between fin and tech companies as the fin part (financial sector) is highly regulated while the tech part (technology sector) is not. Currently, tech firms are mainly concentrating on providing complementary products and services that do not require banking license. In the future, as they exhaust growth opportunities, tech companies might lose interest in entering the complex areas (products and services) of the banking sector, which require proper infrastructure, processes, and sufficient capital. On the other hand, banks enjoy a good reputation in the financial world and possess a valuable know-how. Thus, a future collaboration between financial and technology companies seems like a profitable opportunity for both sides.
Start-up Programs
Banks have shown great interest in start-ups by attending entrepreneurship- focused events or even sponsoring fintech start-ups. Examples are Fintech Innovation Lab, Startupbootcamp and other. Some banks take part in programs that allow them to benefit from IT developments by getting involved in various types of agreements.
Partnerships
Banks are also interested in partnerships with established IT companies. Such partnerships allow financial firms to buy services and/or products and implement them under their own brands. Additionally, by participating in business networks, banks and IT organisations can provide complementary products and services that better meet consumers’ needs. Examples are online and mobile banking platforms which are often not developed by banks themselves.
Scenario 2: Cannibalization
Cannibalization is the perfect term to describe the other option for fintech’s future. The term refers to the process of one kind eating species of its own kind. Since technology companies have started offering financial services and products, they have been eating up the profits of banks.
Banks – too big to fail?
A comparison of the Fortune 500 firms from 1995 and 2015 shows that only 12% of the largest corporations still exist (Perry, 2015). This means that the largest banks of today might not exist in 10 or 20 years. On the other hand, tech companies have been very successful in offering better financial solutions that are time-saving, convenient and correspond to the latest customer preferences shifts. The tech giants have sufficient capital, human resources and the advantage of technology know-how so one could argue that they have the capacity to replace the traditional banks.
Financial products and services offered by tech companies
Customers no longer need debit/credit cards to make payments and execute financial transactions. Mobile payments have become easier with the recent hardware and software advancements. Companies such as Alibaba (its affiliated company Ant Financial Services Group), Google Wallet, Paypal, etc. offer mobile payment services, without keeping customers money under custody (in their own premises). Ant Financial Services Group sells insurance products online and provides small loans to business owners that use Alibaba’s retails website. As tech companies continue to offer convenient financial solutions, banks might abandon less profitable products and services, and focus on highly complex solutions.
Conclusion
In order to keep their market shares and for some – to survive, banks need to consider new business models that involve collaboration with IT companies. The future of banks depends on their adaptability as well as on their willingness and success in embracing new technologies. On the other hand, technology companies should as well evaluate the pros and cons of entering new areas of the financial industry.
In the long term, I expect the financial industry to go through continuous transformations in terms of hardware and software. My personal predictions are that robots will replace bank tellers, programs will completely replace financial advisors and mobile payments will make money obsolete.
What do you think – what does the future of fintech hold?
If you are interested in additional fintech analysis and prognosis, you can find more information on Deloitte’s Banking Industry Outlook.
References:
“Banking Industry Outlook | Deloitte US | Center For Financial Services”. Deloitte United States. N.p., 2016. Web. 29 Sept. 2016.
“Fintech’S Golden Age: Competition To Collaboration – Accenture”. Accenture.com. N.p., 2016. Web. 29 Sept. 2016.
“Future Of Fintech And Banking – Accenture”. Accenture.com. N.p., 2016. Web. 29 Sept. 2016.
Group, Ant. “Ant Financial Services Group: Private Company Information – Businessweek”. Bloomberg.com. N.p., 2016. Web. 29 Sept. 2016.
Perry, Mark and Mark Perry. “Fortune 500 Firms In 1955 V. 2015; Only 12% Remain, Thanks To The Creative Destruction That Fuels Economic Prosperity – AEI”. AEI. N.p., 2015. Web. 29 Sept. 2016.
Porter, Michael E. “Strategy And The Internet”. Harvard Business Review March 2001 (2001): n. pag. Print.
“The Challenges And Pathways For “Fintech” Companies To Break The Traditional Financial Model”. Centrodeinnovacionbbva.com. N.p., 2016. Web. 29 Sept. 2016.
“Traditional Banks And Fintech Firms: New Collaboration Models”. ICAR. N.p., 2016. Web. 29 Sept. 2016.
