QUESTION 1

1. This modern society is no longer unknown to sharing economy which is also known as collaborative economy, collaborative consumption or peer-to-peer economy(Ke, 2017). With more and more people swaying away from private ownership towards sharing resources, information, ideas, services etc, sharing economy business model is becoming popular. People prefer sharing over ownership based on social reasons (for sharing experiences or meeting new people), economic reasons (for saving money), practical reasons (for saving time) and sustainable reasons (for saving resources and protecting environment) (Stark, 2017).

In the last few years we have seen several sharing economy examples. The selected three services are:

• Airbnb is providing apartment and house renting services. It is a type of renting solution offered to people who need a place to stay during travelling. Bookings are made through web-based IT systems or applications.
• Uber is offering shared rides and renting of cars. This service allows people to temporarily use a vehicle owned by a for-profit organization by using an IT based application.
• TaskRabbit aids in inviting handyman to houses. This allows people to share knowledge and talent. The services can be booked over phone or applications driven by IT.

Source: (Stark, 2017)

1. In annual update of Mobile is Eating the World, the mobile expert Andreesen Horowitz argues that we are going into a new deployment phase(Benedict Evans, 2016). It’s not a question of whether the mobile will work, but what will be built off of it in future. Horowitz claim is based on the evolution of mobile industry that has taken place over past decade. In last 9 years, since the launch of first iPhone, the mobile phone has gone from nice to have communication and work tool to a “must have” for everything from entertainment to shopping to games(Zhu, 2016). If we take a look around, we can see that people are constantly looking down at their phones on the street and are raising their phones to take a selfie. With a diagram below, we can see that since past several years, PC have been showing an increasing trend until recently as it has started to decline. More and more users are now opting mobile phones instead of buying PCs. Smartphones have now replaced the PCs ownership in recent years as mobile phone users have surpassed PC ownership and is touching for 5 billion + users (Benedict Evans, 2016).

The venture capital firm Andreesen Horowitz claimed that “Mobile is eating the world” and its not very hard to see why. Demand for the mobile software is at an all time high with android and iOS completely dominating the mobile market. Due to its open nature, android has become an obvious choice for device manufacturers for developing industrial gear (Zhu, 2016). The low-cost, customizable operating system is expected to have a massive impact on the internet of things. Mobile is not just a type of device, its an entirely new ecosystem of technology. We can see that it has brought a huge shift in scale in multiplying what technology can help people achieve. As the mobile ecosystem has taken over the PC ecosystem, the new mobile components have risen for different use cases powered by software. According to Horowitz, smartphone is like a drone that flies and is going to create a Cambrian Explosion of new products i.e. the Internet of Things, wearable devices, smart home monitoring systems, connected cars and virtual reality  (Zhu, 2016).

Smartphone have also taken over how we interact, how we eat, how we travel, how we pay and even how we commute. The most exciting and widespread implications of the mobile ecosystem is the rise of driverless cars. These cars are poised to become smart phones with wheels – within a few years, they will be electric, on-demand and autonomous. Whether it’s Chevy Bolt or Tesla model 3, the technology is likely to be unstoppable (Broadbent, 2017).  Similarly, mobile phone has changed work and productivity in ways that we cannot imagine. Instead of making PowerPoint presentations, the work of the future will allow people to present their ideas in more unimaginable ways. Mobile technology will make work more efficient by saving time and reducing effort and helping people get directly to the root of the uniquely value proposition that human knowledge workers can add – creativity, discretion, ingenuity and critical thinking.

For an IT manager working in consumer product enterprise, this phrase is helpful. Since mobile has finally surpassed desktop search, the managers now look at things differently. The IT manager can use Google application and push mobile search optimization as the future marketing tactic. A growing number of enterprises are building fancy apps and designing their websites that are mobile friendly. For an IT manager of Consumer Company, internet strategy and application development has to be a top priority. According to Broadbent (2017), mobile ad spending will likely grow by more than 50% this year to reach $28.48 billion and then grow another 41% to reach $41 billion by 2018. Now “mobile” doesn’t really mean mobile, it means universal access to the internet at any time (Broadbent, 2017).

QUESTION 2

Big data is a data set that is so large or complex that traditional data processing application software is inadequate to deal with it (Gandomi & Haider, 2015). Big data is high volume, high velocity and high variety information assets that demand cost-effective, innovative forms of information processing for enhancing insight and decision-making (Gartner, 2014). Analyzing the big data allows analysts, researchers and business users to make faster and efficient decisions using data that was previously unusable. There are various new tools being used by analysts to analyze big data for firms. In 2017, the new best big data tools are:

• Mongo DB: It is a good resource to manage data that is frequently changing or data that is semi structured or unstructured. It is mostly used in mobile apps, product catalogs and content management.
• Cloudera: It is a company that makes commercial version of Hadoop. Cloudera is most popular developer of Hadoop.
• Hadoop: It has become a synonymous with big data. It is an open source software framework for distributed storage of large datasets on computer clusters. It means people have the ability to scale data without worrying about hardware. It comes with large amount of storage facility.
• Hive: This helps in facilitating, managing and querying large datasets residing in the distributed storage, Apache Hive provides a mechanism that aids in project structuring.
• Spark: It is an open-source data analytics cluster computing framework, Apache Spark fits into the Hadoop Distributed File System (HDFS).
• Tableau: It is a data visualization tool whose primary focus is on the business intelligence. With Tableau, users have more ability to create bar charts, scatter plots and maps without programming.
• Talend: It is also a great open source company offering data products.

Source: (Devi, 2017)

B: The most common definition of the difference between predictive and prescriptive analysis is that the former describes what will happen and the later describes what should happen  (Boateng, 2016).

Predictive analysis predicts what may happen in future. By combining the historical data with algorithms, rules and sometimes external data can determine the probable future outcome of an event. However, it does not guarantee a future event or outcome will occur. It enables organization to increase their profits and gain a competitive edge. It can detect fraud, improve marketing campaign and lead to operational improvement. The main goal of predictive analysis is to go beyond knowledge of what has happened to supply the very best analysis of what might happen in future (Boateng, 2016).

Prescriptive analysis, on other hand, can be likened to a crystal ball. By combining tools like machine learning, algorithms, computational procedures, business policies and several other methods, prescriptive analysis provide information not only about what will happen but also about why it will happen  (Boateng, 2016). It provides recommendations that allow organizations to evaluate the possible outcomes based on their actions. The most notable example of prescriptive analysis is Google’s self-driving car. During every trip, it is able to make multiple decisions about what to do based on predictions of future outcomes. To sum it up we can say that predictive analysis tells about what may happen while prescriptive analysis tells about what should we do?

C: Data visualization is viewed by many disciplines as a modern technique for managing the data. Visual data mining helps in dealing with flood of information while integrating the human in the data analysis process (Ajibade, 2016). It is used to communicate data or information by encoding it as visual object (e.g. lines and bars). Over the past few years, lots of visualization methods have been developed that enabled users to represent large information and as well as examine the data. These methods are various including scatter plot, bubble plot, time line, data flow diagram, Venn diagram, histogram, bar chart, cone tree, semantic network, tree map and parallel coordinates (Ajibade, 2016).

• Tree map: It has visualization technique that has attribute of showing data in hierarchy in a nested or layered rectangle form (Ajibade, 2016). It is a very effective technique used for visualizing structures of hierarchies. Users are able to compare the nodes and sub nodes at different depths to identify expected patterns.
• Parallel coordinates: It is a technique that makes use of concept of networking a multi-dimensional point to some axes and all of these are parallel to each other (Ajibade, 2016). In this technique, single data elements are being plotted across many dimensions and these dimensions are then connected to y-axis. The parallel coordinate is important if user wants to show a multidimensional data and a lot of these dimensions are being expanded by this technique.
• Scatter plot: It is a 2-dimensional plot displaying the joint variation of two data items. It is also called scatter chart or graph (Ajibade, 2016). It shows data in Cartesian coordinates in graphical display that shows relationship existing between two variables in which one is represented as a vertical distance and the other as a horizontal distance. A scatter plot displays the variables and how strong they are related (Ajibade, 2016).

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QUESTION 3

The three concepts of GAFAnomics are:

• Make smart and meaningful things: GAFA is bolstered by a strong vocation i.e. to help people save time and effort (Faber Novel, 2014). Their products and services are more valuable because they are intuitive to use. Lets take an example of Apple. With Apple iPhone, listening to music has become 70 times faster as people can look for song titles on iTunes, buy it and then listens to it.
• Foster value creation rather than revenue: GAFA cares much about meeting customer needs that they sacrifice short term revenues and profits (Faber Novel, 2014). Let’s look at Google for value creation. Google creates value for users by giving them access to an almost infinite and time saving source of information. It captures value from these users by data aggregation about their product usages. These pieces of information are exploited for improving the search engine as a whole. Google creates value for businesses by allowing them to connect with users. First naturally, by referencing their content and creating a link between users and businesses through Google search. Second, artificially by allowing the businesses for advertising targeted users through Google adwords.
• Doing away with core business: Commitment is a scare commodity and magic lies in meeting and anticipating the customer demands in timely manner at risk of letting competitors gain a lead (Faber Novel, 2014). Jeff Bezos believes that there are two ways to extend the business. First make an inventory of what you are good at and extend from your skills out. Second, determine what customers need  (Faber Novel, 2014). Google has strived to control its infrastructure by providing internet facility, hardware, operating system, storefront, browsers, cloud and payment systems. Google has also indulged itself into Google Calico, Google Youtube, Google Play, Google Wallet, Google Hangout and Google Car for playing around with health, entertainment, shopping, payment, communication and commuting.

QUESTION 4

A:

Source: (Bly, 2015)

B: According to the IBM CEO, the pressure to exploit social media is getting fierce day by day. As the next generation for customer relationship management is rising, Social CRM is gaining momentum. Several traditional CRM strategies are focused on management solutions for channels like websites, call centers and brick and mortar locations (IBM, 2016). With Social CRM, these strategies are likely to account for the dynamics of the community based environment that defines the social media. Social CRM incorporates the customer and visitor engagement on social media platforms or websites within the larger processes of marketing, customer services and sales. The goals are two-fold: to interact with customers and potential customers on these platforms for improving their experience with company and to generate the data that can improve the business and its processes  (IBM, 2016). A social CRM approach requires a strong customer engagement strategy in which social media is a foundation for future customer experiences. In this way, social media becomes an enabler. However, moving to social CRM strategy is not linear as there are several challenges that are discussed below.

• There is no turning back: Feeling pressure for embracing social media is changing the way people do business. As a result, social media footprint has grown rapidly but there is still so much required of companies to fully exploit the benefits social media offers (IBM, 2016).
• Difficulty in integrating overreaching Social CRM strategy: Social media initiatives have sprouted up organically across the enterprise but the key characteristics of Social CRM strategy is executive sponsorship, integrated cross functional governance and sharing of customer insights to enhance innovation (IBM, 2016).
• ROI and Mitigating risks of social media: Applying analytics can help in tracking ROI but there are fears of negative brand exposure. There is no or little social media training of employees (IBM, 2016).

The top challenges as per the survey conducted by IBM in 2016 are failure to establish ROI strategy, inability of firms to monitor employees’ social media usage and negative brand exposure (see figure below).

Source: (IBM, 2016)

 QUESTION 5

SaaS model continues to gain traction across all corners of the businesses. It is also known as on-demand software (Sales Force, 2017). It eschews the traditional software installation and management approaches in favor of delivering cloud-based applications via the internet. The leading example of SaaS software is Microsoft Office 365 (Vladimirskiy, 2016).

The signature Microsoft productivity application like Word, Excel and Power Point are longtime staples of workplace. Recently, cloud-based Microsoft Office 365 has expanded the office suite’s parameters. The users are now able to create, edit and share content from any Mac, iOS, Android, Windows or PC device in real-time  (Vladimirskiy, 2016). It also allows customers to connect with colleagues and friends across a range of tools from emails to video conferencing and leverage a range of collaborative technologies supporting secure interactions both inside and outside of the organization. In the past, the businesses used to rely on packaged software solutions for covering spreadsheets, emails and communications or business intelligence. To use the example of a sales and marketing example, a business might have used an on-premises software for CRM or for managing its worksheets. However, as compared to using Microsoft Office 365, the business might have to buy on-premises software. This software is needed to be evaluated, bought, installed, kept secured, maintained and regularly upgraded on in-house systems by the internal IT department  (Vladimirskiy, 2016). A business could also end up needing the support of wide variety of systems side by side along with codes. Using the on-premises packaged software can place burden on IT team and be costly. The costs of the spreadsheets software might mean it is not affordable for small businesses and can be difficult for them to scale up quickly in response to growth or change. Hence, using a SaaS software like Microsoft Office 365 is beneficial for firms (Sales Force, 2017).

References

Ajibade, S. (2016). An Overview of Big Data Visualization Techniques in Data Mining. International Journal of Computer Science and Information Technology Research , 4 (3), 105-113.

Benedict Evans. (2016, December 9). Mobile is eating the world. Retrieved November 11, 2017, from http://ben-evans.com/benedictevans/2016/12/8/mobile-is-eating-the-world

Bly, R. W. (2015). The Marketing Plan Handbook: Develop Big-Picture Marketing Plans for Pennies. Entrepreneur Press.

Boateng, C. (2016, November 17). Predictive Analytics vs. Prescriptive Analytics – What’s the Difference? Retrieved November 11, 2017, from https://go.christiansteven.com/predictive-analytics-vs.-prescriptive-analytics-whats-the-difference

Broadbent, A. (2017). By the Data: For Consumers, Mobile is the Internet. Retrieved November 11, 2017, from https://www.startupgrind.com/blog/mobile-is-the-internet-for-consumers/

Clarity . (2017). ERP Configuration vs. Customization. Retrieved November 11, 2017, from https://www.clarity-ventures.com/articles/erp-configuration-vs-customization-fundamentals-of-erp-configuration-erp-custom

Devi, M. (2017). All the best big data tools and how to use them. Retrieved November 11, 2017, from https://www.import.io/post/all-the-best-big-data-tools-and-how-to-use-them/

Faber Novel. (2014). GAFAnomics: New Economy, New Rules. Retrieved November 11, 2017, from http://images.transcontinentalmedia.com/LAF/lacom/gafanomics.pdf

Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management , 35 (2), 137-144.

Gartner. (2014, January 29). Gartner Says By 2016, the Impact of Cloud and Emergence of Postmodern ERP Will Relegate Highly Customized ERP Systems to “Legacy” Status. Retrieved November 11, 2017, from https://www.gartner.com/newsroom/id/2658415

IBM. (2016). From social media to Social CRM: Reinventing the customer relationship. Retrieved November 11, 2017, from IBM Institute for Business Value: https://www.ibm.com/midmarket/uk/en/att/pdf/social_media_Part_Executive_Report.pdf

Ke, Q. (2017). Service providers of the sharing economy: Who joins who benefits? Proc. ACM Human Comput. Interact , 1-2 (57), 1-17.

NetSuite. (2017). NetSuite Two-Tier ERP Strategy Kit. Retrieved November 11, 2017, from http://documents.proteloinc.com/netsuite-advantage/Protelo-two-tier-erp-the-best-of-both-worlds.pdf

Sales Force. (2017). SaaS explained. Retrieved November 11, 2017, from https://www.salesforce.com/uk/learning-centre/tech/saas/

Scheer, A.-W., & Habermann, F. (2000). Enterprise resource planning: making ERP a success. Communications of the ACM , 43 (4), 57-61.

Stark, D. (2017, September 29). Sharing Economy and Collaborative Consumption: Definition, Statistics, Examples and 2017 Trends. Retrieved November 11, 2017, from https://lovata.com/blog/sharing-economy-collaborative-consumption-definition-statistics-examples.html

Vladimirskiy, V. (2016, October 10). 10 Popular Software as a Service (SaaS) Examples. Retrieved November 11, 2017, from https://getnerdio.com/blogs/10-popular-software-service-examples/

Zhu, P. (2016). Mobile Is Eating the World. Retrieved November 11, 2017, from http://www.licensinglive.com/blog/2015/05/mobile-is-eating-the-world/