Decision Support System and Smart, Connected Products Analysis

This report examines the application of Decision Support Systems (DSS) in evaluating the viability of a cloud software project for YourCloud Pty. It utilizes Analytical Hierarchy Process (AHP) and Net Present Value (NPV) calculations, along with Monte Carlo analysis to assess risk and potential returns. The report demonstrates the project's financial feasibility, with an NPV exceeding the initial investment and analysts' expectations. Furthermore, it explores the transformative impact of smart, connected products, driven by the Internet of Things (IoT), on business competition and strategy. The report discusses how IoT influences competitive factors such as buyer and supplier power, barriers to entry, and the threat of substitutes, emphasizing the need for companies to adapt their business models and strategic positioning to remain competitive in this evolving landscape. The report also provides insights into the challenges and opportunities that arise from the integration of smart, connected products, including data management, product design, and after-sales services.

DECISION SUPPORT SYSTEM:
NAME
DATE

Part A
Question One
Introduction
Making production/ manufacturing decisions need to be done in a logical way, with justifications
for a given investment determined, using various tools. In this case, YourCloud Pty company,
located in Brisbane, is interested in developing a new responsive cloud software that analysts say
has a Net Present Value (NPV) of $ two million. Market conditions have created some bad software
investment decisions, hence the caution in deciding ot produce the cloud based software. This
section uses Decision Support Systems (DSS) to determine the viability of the proposed projects.
In computing the NPV for the coud based software, the following factors are taken into
consideration;
The annual cash flows from the production, which are determined by considering the:
 Any overhead costs/ fixed costs per year
 The cost of producing the products
 The selling price for the products
 The initial investment is also considered, along with the discount rate
In determining the NPV, the general formula
NPV = C x {(1 - (1 + R)-T) / R} − Initial Investment
Where C represents expected cash flows per period, T is the number of periods, and R the required
rate of return. In the valuation of equity investments, the required rate of return is the discount rate
and so the value used is 12%. Before determining the NPV, the cash flows for each year are
determined; This is done by subtracting the expenses, including overheads, from the expected sales
for each year, factoring in the annual growth in sales from annual growth in demand. In the year
zero, only the initial investent and the fixed costs are considered in determining the cash flows,
while in subsequent years, the market demand plus the fixed costs are considered. These were
computed in a spreadsheet, and then the NPV determined using the software
Year Cash Flows (Net)
0 -1960000
1 10430000
2 14280000
3 16453500

4 18953025
The NPV was established to be $2,958,025.58
DSS

The DSS uses an AHP (Analytical Hierarchy Process)
In determining whether to go ahead with the new project, the cash flows were evlautaed; whether
they are positive or negative, and then used to compute the NPV. The NPV is foud to be positive
and higher than the initial investment plus the overhead costs. This implies that the project is viable
and based on the DSS, should be undertaken. Based on the findings, the claim on the NPV being
above $ two million is correct as the calculations show an NPV value of $2,958,025.58, which is
above the analysts level of $ 2,000,000, meaning discounted to the present rate, the value of the
project is high relative to the investment and overhead costs. As such, the analysts figure is correct
Question Two
The management should proceed with the project; this is because the chance that the NPV for the
cloud software being less than $ 1000,000 is less than 20%; the calculations from the Monte Carlo
Analysis show that the NPV at the worst case scenario will be $ 1,300,000.
Question Three

There is a more than 80% chance that the NPV for the project will be greater than 1,850,000; the
results from the analysis show that the manager should proceed with the production of the software,
based on the decision model and the criteria for the results
Part B: Dashboards

Demonstration One
The
countries where the DB9 has the highest price is in the USA
With power Bi, business assumptions can be validated by running a correlation analysis of the
available data. This will give grater insights and enable cause and effect aspects to be ascertained;
something that correlations alone cannot ascertain. Importantly, Power Bi enables an analysis to
have various angles and insights into to data: an analyst is able to mine more data with different
aspects. Further, more than two parameters can be evaluated; for instance the labor costs can be tied
down to vehicle models, address codes, customer, and country ISO codes. Several views can be
made, a single KPI at a time, and then a combination of related KPIs developed to give an analyst
several clear insights in the car sales business.

Demonstration Two
The sectors that receive research fellowship funding include 41 institutions, accounting for 18.39%
of the total committed funds. The recipients of the research fellowship funding are Universities and
institutions of Higher Learning. The sectors include the environment and oceanology (The Great
barrier Reef), health care and social assistance agriculture forestry and fisheries, professional
scientific and technical services, electricity gas water and waste services, renewable energy, mining
and resources, information media and telecommunications
The challenges faced in data validation include problems with the data entered at the source; there is
no way of validating such data; it is not possible to validate proper inputs for the data. Creating
dynamic drop down lists from the available data based on the fields is also potentially problematic
especially where a dynamic formula needs to be used in merging ranges so that drop down lists can

be updated automatically. Because of different names and headers in tables, using features such as
the INDIRECT function for absolute referencing when creating tables presents potential
challenges. In cases where there are different sheets containing related data, and with such large
data sets, data validation becomes a challenge, especially when using the various functions in
spreadsheets such as Offset(). The use of spaces in names during validation will create problems, as
well as trying to create single column tables using applications such as VBA (Govier, 2018)

Part C
How Smart, Connected Products Are Transforming Competition
Introduction
Tha past fifty years has seen two instances when information technology transformed industries and
compan ies, ad therefore, their competitiveness; subsequently, the products manufactured by
compoanies, how they are manufactured, their fatures, and their marketing changed. The 1960s and
1970s heralded the first IT wave led to automated individual activities within the value chain. The
second wave of 1980s and 1990s led to integration and coordination across individual activities. In
this reprot, the third IT wave, the internet of things, and how it will affect competitiveness and
conmpetition among produsers is discussed, and conclusions drawn.
Discussions
The advent of the internet of things, powered by the ubiquity and low cost internet has created a
new set of products that are interconnected; the important aspect in these internet of things is the
things. The ‘things’ are devices with a physical component, smart components made up of sensors,
software, control systems, micro processors, storage, and embedded operating systems, and
connectivity. These features have led to the development of smart, connected products, for instance,
medical monitor equipment that users wear and gets their health data taken and procesd (and stored)
in cloud platforms, and used by physicians to monitor health and prescribe remedies that are
automaticaly processed by pharmacists and delivered by courier companies. These developments
will create (and are already creating) new business models, from how manufacturers design
products, their development, and distribution and after sales services, resulting n new competitive
models that frims ought to consider; in many cases, forms are forced to consider this new impact of
IT and change their strategy and competitiveness accordingly. The advent of the internet of things
has created a new technology stack, consisting of new prodct hardware, ts embedded software,
connectivity, product cloud, security tools, and an external communications gateway. With these
developments, new product communities such as smart grids, smart homs, smart cities, and smart
product communities have come up. This requires a paradigm and strategy change, especially
among manufacturers (Porter and Heppelmann, 2014).
Wth the ability of smart products to monitor the environment, control their functions, optimize
performance, and run autonomously; new products will be very different, and a drastic departure
form the mechanical and electrial system products society has become accustomed tp, such as the
standard car to an AI (artificial intelligence) enabled car that can self drive and pack. The
determinants of competitiveness of companies include the bargaining power of buyers and sellers,
level of competitiveness in a sector, barriers to entry, and availability of subsitutes. The advent of
connected products radically shifts or impacts these factors: by creating greater customized value

among a range of products, buyer bargaining power can be drastically reduced. In some cases
however, it can increase because customers will have greater knowledge of product performance,
and so have high expectations. Further, buyers will have severl choces, with underlying systems and
functionality being offered by a single supplier, increasing their bargaining power. Supplier power
can be reduced as well; with new product lines that suppliers are not accustomed to; such as
proprietary software applications. The technology, time, and cash investments required to build
connected products is steep; this wil have the ikelihood of creating larger barriers to new entants in
the industry sector. However, nimble start ups with specialized knnowledge, such as sensor
manufacturers or software developers will easily enter industries where suh products are crucial for
the achievement of the connected products. An example is Google, a company just barly 20 years
old, but which has become ubiquitoues with everything internet, and now has ventured into
producing free Android Operating system and other products like Google maps, courtesy of their
technical knowhow; older firms such as general motors and Ford, much older firms, now use
Google products in a bid to develop connected products to meet new customer needs and remain
competitive. The threat of substittes can be minimized by the advent of internet of things; the cost
of shifting to new products can be high for customers because of connectedness; alternatvely, it can
be easy to switch producs for certain class of products given the connectedness of products will
result in almost similar products being made. The internet of things will affect competitiveness; it
can increase or decrease the level pf competitivness, especially where firms are forced to work
interdependently (decrease competition). All these factors will drastically change the industry
structure for many manufacturers (Porter and Heppelmann, 2014).
These changes will reshape industry competition, given its ability to change and expand industry
boundaries from product systems (say a maker of mobile and computer devices) to system of
systems where cars, home electronics, medical care, and retail systems are interconnected with
computing and mobile devces, creating a system of systems. The smart connected devices will
create competitive advantage among producers from design, marketing, after sale service, human
resources, to security. Firms, therefore have to change their strategy, either to organizational
effectiveness (OE) or more fittingly, to distinctive strategic positioning. Companies must decide
which of the set of smart connected device features and capabilities they should pursue, the level of
functionality embedded in these products Vis a Vis those in the cloud, whether the systems should
be open or closed, or whether the company should develop the wholse set of smart interconnected
products and their infrastructure themselves or outsource some elements to specialists. The
companies must decide on the data to capture, store, and use, and the rights to such data as well as
how these will maximize its product offering. Firms must also determine if they will
disintermediate fully or partially the service networks and distribution channels, whether they must

change their business model, or enter new business, for instance, monetizing the data it collects that
other forms can find useful. Companies must also consider whether they must expnad their scope
Conclusion
The internet of things and interconnectivity is, and will contiue to rsadically change how companies
operate, and importantly, their distinctive strategic positioning and business models

References
Govier, R. (2018). Excel Data Validation Dependent Lists With Tables and INDIRECT. [online]
Contextures.com. Available at:
http://www.contextures.com/exceldatavaldependindextablesindirect.html [Accessed 8 Apr. 2018].
Porter, M. and Heppelmann, J. (2014). 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 8 Apr. 2018].