Transforming Companies: Business Analytics & Smart Products

This assignment is a case study focusing on the impact of smart, connected products on business analytics and how they contribute to transforming companies. It explores how the integration of technology into products is revolutionizing business strategies, enabling new functionalities, and enhancing reliability. The analysis covers the evolution of products into intelligent devices, the relationship between smart products and business analytics, and the strategic implications for companies. It also discusses the challenges of managing unstructured data and the importance of big data analytics in understanding patterns from sensor readings. The study concludes that while smart, connected products offer significant opportunities, companies must carefully consider the risks and new skill requirements when entering related product markets.

Running head: BUSINESS INTELLIGENCE
Business Intelligence
Assessment item 1 – Assignment 1
Student Name:
University Name:

1BUSINESS INTELLIGENCE
Table of Contents
Part – A............................................................................................................................................2
Question 1....................................................................................................................................2
Result analysis.........................................................................................................................3
Question 2....................................................................................................................................3
Result analysis.........................................................................................................................5
Question 3....................................................................................................................................5
Result analysis.........................................................................................................................7
Part – B............................................................................................................................................8
Demonstration 1...........................................................................................................................8
First dashboard.........................................................................................................................8
Second dashboard....................................................................................................................8
Answer to questions.................................................................................................................9
Demonstration 2...........................................................................................................................9
First dashboard.........................................................................................................................9
Second dashboard..................................................................................................................10
Answer to questions...............................................................................................................10
Part C – Analysis of Case Study....................................................................................................11
Bibliography..................................................................................................................................15

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Part – A
Question 1
NPV model
*Columns
*Years 2018,2021
*Rows
Initial investment needed(0) = 1750000.00 '.2
Market at time (0)= 420000
Market Growth = 0.15'.2
Market Share = 0.10'.2
Total market = Market at time;Total market(-1)*1.15
Sales Volume = Total Market*Market Share
Estimated selling price = 55.00 '.2
Cost of production = 25.00 '.2
Total Revenue = Sales Volume*Estimated selling Price '.2
Cost of Goods sold = Sales Volume*Cost of Production
Annual overhead cost = 210000
Cash Flow = Total Revenue-Cost of goods sold-Annual Overhead cost
Rate = 0.12'.2
NPV(0) = *NPV cash flow;rate

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Model Output
Result analysis
The Net Present Value (NPV) that has been calculated in the model is $5440551.00 and
the claim regarding NPV is correct. The NPV has been calculated for the first period only that is
2018 for decision-making using NPV (0) in Visual DSS. Hence, the claim that has been made
regarding NPV being above $2 million is correct.
Question 2
Monte Carlo Simulation Model
*Columns
*Years 2018,2021
*Rows
Initial investment needed(0) = UNI(100000.00,200000.00) '.2
Market at time (0)= 420000
Market Growth = 0.15'.2
Market Share = TRI(0.05,0.10,0.15)'.2
Total market = Market at time;Total market(-1)*1.15

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Sales Volume = Total Market*Market Share
Estimated selling price = 55.00 '.2
Cost of production = NOR(30.00,12.00) '.2
Total Revenue = Sales Volume*Estimated selling Price '.2
Cost of Goods sold = Sales Volume*Cost of Production
Annual overhead cost = TRI(150000,215000,350000)
Cash Flow = Total Revenue-Cost of goods sold-Annual Overhead cost
Rate = 0.12'.2
NPV(0) = *NPV cash flow;rate
Model Output

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Cumulative probabilities report
Result analysis
The senior management should accept the proposed production as the NPV calculated for
cumulative probability at less than 20% is $3090358.00. Thus, it is much greater than the
required NPV of $1,000,000 (1 million). Hence, it is feasible for the senior management to
accept the proposed production of report.
Question 3
Monte Carlo simulation Model
*Columns
*Years 2018,2021

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*Rows
Initial investment needed(0) = 1750000.00 '.2
Market at time (0)= 420000
Market Growth = 0.15'.2
Market Share = TRI(0.05,0.10,0.15)'.2
Total market = Market at time;Total market(-1)*1.15
Sales Volume = Total Market*Market Share
Estimated selling price = UNI(45.00,65.00) '.2
Cost of production = NOR(25.00,5.00) '.2
Total Revenue = Sales Volume*Estimated selling Price '.2
Cost of Goods sold = Sales Volume*Cost of Production
Annual overhead cost = 210000
Cash Flow = Total Revenue-Cost of goods sold-Annual Overhead cost
Rate = 0.12'.2
NPV(0) = *NPV cash flow;rate
Model Output

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Result analysis
Based on results and the decision criteria, it can be said that the CEO will accept the
proposed production of the product. It is evident from the fact that the NPV being calculated at
less than 90% cumulative probability is $6619214.00 which is greater than $1,850,000.00.
Hence, the decision by CEO to accept the proposed production of product is feasible in terms of
the calculated NPV.

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Part – B
Demonstration 1
First dashboard
Second dashboard

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Answer to questions
The dashboard has been designed by selecting DB9 in slicer from which it has been
found that the most SalePrice of DB9 is of USA.
Use of Power BI to validate business assumptions
The business assumptions can be validated by using Power BI as it offers data
visualization and graphical representation of data. In context to the demonstration with Car sales
data, it has been determined that Power BI will help to analyse the sales and profit.
Demonstration 2
First dashboard

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Second dashboard
Answer to questions
Research Fellowship funding are received by sectors as listed below:
 Health care and social assistance
 Renewable energy
 Agriculture, forestry and fisheries
 Electricity, gas, water and waste services
 Great Barrier Reef
 Professional, scientific and technical services
Potential issues in terms of data validation based on the fields
During data validation based on fields, there may arise potential issues as there maybe
blank data in the source from which data is being imported for validation. The source data have
to be checked properly and organized in a sequential manner to conduct proper validation.

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Part C – Analysis of Case Study
Introduction
This report is focused on smart, connected products for determining the role played by
them in context to business analytics and how they may help to transform companies with the
use of business intelligence. The businesses in this modern world of technological world are
revolutionizing and there is evolution of products into intelligent and connected devices. The
discussions being carried out in this report reflect that there is a relationship between the smart,
connected products and business analytics. The companies are transforming their business
strategy with the help of smart, connected products by utilizing the features offered by business
intelligence.
Smart, connected products contribute to business analytics
The new abilities and tremendous amounts of information that smart, connected products
offer are rethinking the exercises of the center elements of organizations here and there
fundamentally. As programming and cloud-based working frameworks wind up vital to items,
new item advancement standards rise, producing segments and procedures change, and IT
security turns into the activity of each capacity. As the capacity to open the full estimation of
information turns into a key source of upper hand, the administration, administration,
investigation, and security of that information is forming into a noteworthy new business work.
According to Porter and Heppelmann (2014), while singular sensor readings are
profitable, organizations regularly can uncover intense experiences by recognizing designs in a
large number of readings from numerous items after some time. For instance, data from
divergent individual sensors, for example, a car's motor temperature, throttle position, and fuel