Business Intelligence

This report discusses the roles of smart and connected products in business analytics and transforming commerce through the usage of business intelligence. It also highlights the contributions of smart, connected products in transforming businesses.

Running head: BUSINESS INTELLIGENCE
Business Intelligence
Name of Student:
Name of University:
Author’s Note:

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Table of Contents
Part A...............................................................................................................................................2
Answer 1......................................................................................................................................2
Answer 2......................................................................................................................................3
Answer 3......................................................................................................................................4
Part B...............................................................................................................................................6
Demonstration 1...........................................................................................................................6
Demonstration 2...........................................................................................................................8
Part C.............................................................................................................................................10
How Smart, Connected Products Are Transforming Competition................................................10
Introduction................................................................................................................................10
Smart, Connected Products........................................................................................................10
Contribution of Smart, Connected Products in Business Analytics..........................................11
Contribution of Smart, Connected Products in transforming businesses..................................12
Conclusion.................................................................................................................................13
References......................................................................................................................................13

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Part A
Cloud Private Limited is an organisation involved in developing cloud-based software
operating in Brisbane, Australia. The organisation has made a plan of bringing an application of
cloud-based software in the market. In the current time, competitive and active approach has
resulted in ineffective investment decisions related to software. It is highly critical for the senior
manager to carry out effective assessment of all the new products initiated in the market. The
intention here is to recommend the top-level management regarding the viability of the new
product. The technique of Monte-Carlo simulation and visual DSS software are used in order to
undertake significant decisions before the software is launched in the market.
Answer 1
Based on the decision support model, which is formulated with the help of visual DSS,
the net present value (NPV) is computed as $5,440,551. In this case, the NPV obtained is higher
than $2,000,000 and hence, it is possible for the manager to undertake decision regarding the
launch of the product in the market. Hence, the decision that has been undertaken for bringing
the software in the market is right.

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Answer 2
In order to conduct the risk evaluation, it is necessary to evaluate the effect of variation in the
share of the market, production cost and initial outlay on NPV.
The share of the market would vary between 5% and 15%; more specifically, it has a
probability of staying around 10%
Normal distribution is formed on the part of unit cost having standard deviation of $12
and mean of $30
The interval of the cost of overhead could be between $15,000 and $35,000. However,
the overhead cost would probably be under $215,000 each year
There is uniform distribution of the requirement of initial outlay from $1,000,000 to
$2,000,000

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In this case, the decision that needs to be taken is to ascertain whether launching the software
would be correct, since the probability is 20% or greater that the NPV of the project would be
lower than $1,000,000. In case of 20% probability, the computed cumulative NPV would be
$2,908,313, which is more than $1,000,000. Even if the probability of 10% is taken into
consideration, the cumulative NPV is obtained as $2,244,173. Hence, it could be found out that
the risk levels of 10% and 20% signify the NPV, which is higher than $1,000,000. It could be
assessed that the organisation would find it easy to launch the product in the market in relation to
NPV of $1 million having risk level of lower than 10%.

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Answer 3
After the CEO of the organisation has obtained the evaluated results, concerns are raised
regarding the assumptions that are hypothecated in the model of NPV. However, concentration
has been placed on few uncertainties of the model, which are enumerated as follows:
The distribution of selling price is made between $45 and $65
There is normal distribution of unit cost having standard deviation of $5 and average of
$25
The CEO has provided green signal to launch the software, if the probability of NPV is
80%, which would be more than $2,500,000

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Based on the evaluated model of visual DSS, the cumulative NPV having above 80%
probability is at least $6,222,640, which is way too greater than $2,500,000. This
signifies that the software is highly credible of being launched in the market.
Overall interpretation:
In accordance with all the market uncertainties and assumptions related to market value,
it is evaluated that the product has met all the criteria along with clearing the checkpoints. The
assessment of the above-stated three questions clearly sheds light on the fact that it is necessary
for the CEO of the firm to accept the proposed production, as the product fulfils all the decision
criteria requirements.
Part B
Demonstration 1
Figure 1: Complete Car sales
Based on the analysis of the above figure, it is found that information is provided
regarding sales of various car models. The cost of labour of various nations is evaluated in the

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top right-hand side. The cost of labour is most in UK followed by US. Moreover, the
organisation has sold 495,000 spare parts along with providing information regarding the
delivery charge of various car models. It has been further identified that there is variation in
delivery charge across models. The top right-hand side supplies information regarding the selling
prices across the nations. It has been found out that the selling price is maximum for UK, which
has amounted to $15,725,000.
Figure 2: Car Sales DB9
The image above is obtained from data filtration in Power BI. The presentation is made
for DB9 model. The organisation has sold the spare amounting to $44,000. As identified from
the top left side corner, the maximum amount of selling price is generated from US. The selling
price in US is $3,609,410.
By analysing the power of BI, information is evaluated on selling cars depending on
models and spare parts. The data comprise of detailed information on the sales of spare parts
throughout the nations, year and models. In the above evaluation, effective use of filtering tool
was made. With the help of this tool, a particular model has been chosen. This has helped in
obtaining the adjoining information associated with the specific model. In the current case, it is
crucial for the organisation to obtain spare sales information throughout the nations, timeline and

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models. By using Power BI, the information is segregated and thus, crucial information about
various spare parts has been obtained based on models.
Demonstration 2
Figure 3: Information on Funding Recipients
The figure above depicts information about the research funding at Queensland. The
image in the top right side corner supplies information of the funding that the department has
obtained. The information on the receipt of the quantity funding is provided as well.

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Figure 4: Research Funding’s on Research Fellowships
Forest, agriculture, fisheries, art and recreational sectors are available for funding
related to research fellowship. The Queensland government has contributed $9,300,000 for
research fellowships.
The second figure evaluation states that the funding supplies information regarding the
commitment of the government. However, the image-related information is vague. On the top
right hand side, the departments receiving funding are shown. The department that has received
fund for research fellowship is highlighted in dark colour; however, the validation of information
could not be made easily. The information that is provided is the overall amount of funding.

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Part C
How Smart, Connected Products Are Transforming Competition
Introduction
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.
Smart, Connected Products
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:

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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.
Contribution of Smart, Connected Products in Business Analytics
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

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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.
Contribution of Smart, Connected Products in transforming businesses
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:
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

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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.".

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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.