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1.Develop a decision support model using Visual DSS using the variables described above. Include comments within your Visual DSS model to explain the variables and your calculations.

2.Based on the result of your model, what is the net present value (NPV)? Explain whether the claim regarding the NPV being above $2 million is correct or incorrect.

When the above analysis reached the Chief Executive Officer (CEO) of your company, he became very concerned about the assumptions made in the model. His experience has taught him to consider the uncertainty associated with selling price and production costs more thoroughly. He required further analysis to be done by incorporating the following uncertainties to Question 1 model:

  • You are required to use Visual DSS to run a Monte Carlo simulation (a Risk Analysis). Based on your results determine whether the CEO will proceed under these uncertainties.
  • Produce a cumulative probabilities report and graph for the question. Based on results and the decision criteria, will the CEO accept or reject the proposed production of the product?
  • Save a screenshot of the Dashboard.
  • Select DB9 in the slicer and save a second screenshot of the Dashboard.
  • Answer the following two questions:

Which Country has the most SalePrice (sum) of the DB9?

How can you use Power BI to validate business assumptions in this demonstration? (1 paragraph)

Develop a decision support model using Visual DSS using the variables described above. Include comments within your Visual DSS model to explain the variables and your calculations.

The global business frameworks and the commercial operational scenarios have been always influenced and effected considerably by the development and innovations of global informational technologies, which in turn have considerable implications on how businesses across the globe operate and on the strategic frameworks as well as on the level and types of competitions in the markets (Wortmann and Flüchter 2015).

The first wave of development in the IT infrastructure led to the implementation and wide-spread usage of computers in business activities, followed by the second revolution which encouraged widespread usage of internet, thereby transforming businesses hugely and internationally, enabling most of the businesses to go global. The third wave, initiating in the contemporary period, comprises of the inventions and implementations of the usage of smart and connected products, which is again expected to bring widespread transformations in the business dynamics (Hbr.org 2018). Keeping this into consideration, the concerned report tries to discuss the roles of these smart and connected products in business analytics as well as in transforming commerce though usage of business intelligence.

The basic notion behind the concept of smart, connected products is of developing commonly used products with embedded software, sensors as well as cloud connectivity for the purpose of storage and analysis of product and usage related data, in order to improve the functionality as well as usage of such products, thereby benefiting the users as well as the producers (Rowland et al. 2015).

In general, there are three parts in these types of commodities which are as follows:

Physical component- This comprises of the mechanical parts of the product itself.

“Smart” component- These are the additional installations of things like sensors, software, data storage, embedded operating systems, user interface and others in the product itself in order to enhance the performances, productivity and security of the products considerably.

Connectivity component- These are the wired or wireless connections which are facilitated in the product and have the provisions of one-to-one or one-to-many or many-to-many connections of the product with the users as well as with the manufacturers or other products (Slama et al. 2015). This facilitates exchange of information between the products and their users, manufacturers and operating system, thereby making the products more user friendly and catering better to the purposes for which they are created.

The increased innovation and implementation of such smart, connected products and their usage are expected to have considerable impacts on not only the lifestyle of people across the world in their household life but also on the operations and activities performed by the businesses across the globe, by making the operations more comprehensive, “intelligent” and easy and by transforming the businesses across the world.

Based on the result of your model, what is the net present value (NPV)? Explain whether the claim regarding the NPV being above $2 million is correct or incorrect.

One of the primary positive implications of the innovations and usage of smart, connected products in the aspects of commercial operations is that of the effects of the same in the business analytics. In any kind of business, decision-making is one of the most important components of the business operations, as the strategic planning as well as ventures of the businesses depend on the same. For the purpose of efficient and foresighted decision making, the commercial organizations need to have robust insight about their positions and prospects in the markets and the potential demand, cost, preference as well as economic trends in the market in which they venture or aim to venture in the long run (Evans and Lindner 2012). In this aspect, “business analytics” is used, which involve methodical exploration and statistical analysis of the empirical evidences related to the operations of the organizations and which help in the decision-making process of the companies, by providing data and analytical support.

In this aspect, the smart, connected products have provision of collection and preservation of relevant data in the cloud storages and also are capable of analysing huge numbers of real-time data collected while usage of the products. The instant analysis of the collected real-time data helps in enhancing the performances of these products, which are able to served their purposes more effectively (Chen, Chiang and Storey 2012).

The information collected by the smart, connected products, help the analytical systems embedded in the same to understand different aspects like the environment, the activities getting performed, the expectations of the users from the product, the relative magnitude of utilization of the same in different places and in different times and many other useful facts, which in turn helps the manufacturers to get an insight about the demand and preferential patterns, thereby enabling them to take productive and efficient data-driven decisions (Roblek, Meško and Krapež 2016).

Example: The recent Schindler’s Port Technology has this provision of analysis of real time data which reduces the waiting times of the elevators considerably by analysing and forecasting the patterns of trends of demand, time to destinations and allocating the elevators to their clients based on their analysis.

The IT wave of creation of the intelligent and self-evolving smart, connected products and their supply in the markets have considerable implications on the transformation of the businesses. Transformations in businesses are brought by these products in various ways, the primary ones being as follows:

Which Country has the most SalePrice (sum) of the DB9?

Better control- The connectivity features of these products enable their users to control their activities through remote commands, which enhances the user’s experience.

Optimization- The smart, connected products have the facility of collecting and analysing historical as well as real-time data, which in turn enables the businesses to utilize their resources more efficiently and produce and cater to the places where they are expected to face maximum demands (Hbr.org 2018).

Real time monitoring- The businesses are now enabled to monitor the activities and performances of their products as well as the different activities in their organizational framework, due to wired or wireless connections of such products with their users and manufacturers, which in turn help the businesses to know about the everyday activities as well as short term and long-term prospects, which in turn enables them to design their plan of action accordingly (Weinberg et al. 2015).

Clear communication channels- The production and usage of these user and manufacturer friendly smart, connected products lead to the creation of direct communication channels among the business organizations and their clients, thereby reducing the number of hurdles and intermediaries in these channels, thereby speeding up the productive and market procedures (Hbr.org 2018).

Conclusion 

From the above discussion, it can be asserted that the new era of smart, connected products have already started to bring transformational shifts in the different activities and operational frameworks of the businesses as well as in their prospects, competition and overall business environments. This is expected to increase even more with time and more widespread implementation and usage of these technologies and products in the global commercial scenario.

References 

Chen, H., Chiang, R.H. and Storey, V.C., 2012. Business intelligence and analytics: from big data to big impact. MIS quarterly, pp.1165-1188.

Evans, J.R. and Lindner, C.H., 2012. Business analytics: the next frontier for decision sciences. Decision Line, 43(2), pp.4-6.

Hbr.org (2018). How Smart, Connected Products Are Transforming Competition. [online] Harvard Business Review. Available at: https://hbr.org/2014/11/how-smart-connected-products-are-transforming-competition [Accessed 17 Apr. 2018].

Roblek, V., Meško, M. and Krapež, A., 2016. A complex view of industry 4.0. SAGE Open, 6(2), p.2158244016653987.

Rowland, C., Goodman, E., Charlier, M., Light, A. and Lui, A., 2015. Designing connected products: UX for the consumer Internet of Things. " O'Reilly Media, Inc.".

Slama, D., Puhlmann, F., Morrish, J. and Bhatnagar, R.M., 2015. Enterprise IoT: Strategies and Best Practices for Connected Products and Services. " O'Reilly Media, Inc.".

Weinberg, B.D., Milne, G.R., Andonova, Y.G. and Hajjat, F.M., 2015. Internet of Things: Convenience vs. privacy and secrecy. Business Horizons, 58(6), pp.615-624.

Wortmann, F. and Flüchter, K., 2015. Internet of things. Business & Information Systems Engineering, 57(3), pp.221-224.

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