Business Analytics and Risk

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This study evaluates the effectiveness of business analytical tools implemented by Carnival Corporation & Plc, the world's largest leisure travel company, to manage revenue and allocate inventory. It critically analyses the strengths and weaknesses of the implemented approach and discusses the appropriate use of relevant frameworks like DELTA model, BADM, and CRISP. The study also provides insights into the advantages and limitations of these models and their impact on the company's financial performance.

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Business Analytics and Risk

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TABLE OF CONTENT
INTRODUCTION...........................................................................................................................3
Critical analysis of strengths and weaknesses of implemented approach at Carnival.................3
Appropriate use of relevant frameworks to evaluate business analytical projects like: DELTA
model, BADM and CRISP ..........................................................................................................6
REFERENCES................................................................................................................................9
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INTRODUCTION
Business analytical is methodical exploration of companies' data with focus on statistical
analysis (Wang and Byrd, 2017) This study is based on Carnival corporation & Plc that is the
world's largest leisure travel company. It provides the best holiday experience at affordable
prices. It is facing numbers of problems regarding allocating inventory and deciding prices of
cabins. It decided to use some analytical models and management systems by which it can decide
prices as per the different cabin types. This present study is going to discuss effectiveness of
business analytical tools. There are numbers of statistical business analytical tools that this study
will discuss in detail. This company faced many problems regarding managing revenue so, it
implemented YODA (Yield optimization and demand analytics) management system for better
revenue management. This study aims to help company in knowing advantages as well as
disadvantages of implemented tool. It will further critical evaluate all other effective business
analytical models such as: CRISP, DELTA and others. The main aim of analysing all these tools
in a critical manner is helping out company in selecting the best one for managing revenue and
taking competitive advantages.
Critical analysis of strengths and weaknesses of implemented approach at Carnival
Before discussing effectiveness of business analytical models, it is important to know
about this term as why companies use them and how they can improve their overall performance
with business analytical. In regard to this term, it can be said that it is a process by which
companies make use of statistical methods as well as relevant technologies in order to analyse
historical data. It helps the out to gain a detailed new insight about business and accordingly they
can improve their strategic decision-making. It helps in analysing numerical data or historical
data such as: the numbers of sales, the numbers of customers who visited website, sites and
others. It can make use of Nectar card in business analytical as it can help this company in
maintaining real time information related to stock levels and providing them as per the demand.
It will be great for cruise management.
In regard to Carnival corporation & Plc it is stated that it was finding problems and
business loss only because of price dissatisfaction. Allocation of inventory to client was the other
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main problem. It faced numbers of problems in being in the competition so, it decided to make
use of statistical modes. It made use of yield optimization and demand analytical tools. As with
the name, it can be said that this tool is all about analysing the number of demand and making
changes accordingly (Richards and et.al. 2019). This model has featured by which it can help this
company in determining prices of its cruises and allocation of cabin inventory to multiple
cruises. With learning algorithm, it helps in predicting demand. Price recommendations is being
used to price voyage on 65 carnival ships. This leisure travel company is known for providing
extraordinary holiday experience at exceptional value to all its guests.
So, in regard to effectiveness of advantages of this implemented (YODA) management system,
it can be said that:
It can help this company out in increasing sales.
It can decrease operational and additional inventory cost by Allocating cabins as per the
current numbers of demands (Studer and et.al. 2021).
As this system or model generates millions of price recommendations so, this can help
Carnival corporation and Plc in providing valuable services at affordable price and can
grab attention of customers to the great extent.
This model is effective to the great extent as company proved that after implementing this
model they have generated 1.5%-2.5% incremental uplift in net ticket revenue.
This YODA management system has numbers of characteristics that can make each
brand able to manage its own nuances during maintaining a consistent approach with its
sister brand.
Its ability to manage pricing of all Caribbean cruises can help in deciding specific time to
which, 2 ships can have positioned in the areas.
Along with some advantages, it has some limitations and company needs to focus on all these
areas for better improvement such as:
Disadvantages: It is true that before implementation of statistical tools, company faced
numbers of problems in managing revenue and determining prices of cabins. Manual process
was time-consuming.
This tool is not beneficial for customers as in yield management regular customers do not
receive preferential treatment because it works same for all.

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It considered different pricing strategies and recommendation but all these are not based
on types of people or different people (Verbeek, 2018).
There is a lack of competitive focus as the focus of companies is on profit maximization.
In addition, it is also found that this implemented management system (YODA) helped this
company out in selling the right product to the right customers at right price and in the right time.
Some people stay for 7 days at cruise and some stay for 14 and more days so, as per the staying
days, company needs to decide prices. So, it was one of the main reason of implementation of
this management system (Ren and et.al., 2019). This management system has helped this
company in managing revenue, identifying pricing as per the demand and the numbers of stay
days at cruise. It can help it out in making sure that cruise network aligns with contracted seats
on flights to transport guests to the ship. Inventory or cabin allocation is vital as it can help
company in planning that can be vital in deciding prices. Overall, it can be said that this
implemented management system was highly configurable with numbers of parameters available
that can help in leading the analytics toward specific outcome relied on business capabilities and
knowledge.
There are numbers of analytical tools that can be used by this company and some of them
have been used. For suggesting about the best tool and helping company to identify the area
where it needs to focus, all tools can be critically evaluated. It is also found that full world
cruises visit numbers of ports within 100 or more days. Selling these and dividing them into
sellable sector becomes quite difficult for this company that is creating inventory allocation
problem. Because of different regulations in different countries, prices of these differ that also
create problems in deciding prices. So, overall, it can be said that due to all these problems
Carnival corporation & Plc decided to implement some effective business analytical models that
can help it out in deciding process and allocating inventory (Perakis and et.al., 2020).
Other main element and report that supported this YODA management system and
helped company in getting positive outcome was: science health check report (HCR). This HCR
helped company in providing accurate results by looking at inputs and outputs of this model. It
increased business reliability and now on the basis of positive outcomes, better revenue
management, it can attract inventors and numbers of customers. Business analytical development
methodology, DELTA and CRISP. BADM are others effective and often used analytical tool and
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there are 3sub tools such as: descriptive, predictive and prescriptive (Hammer, Somers, Karre
and Ramsauer, 2017).
Appropriate use of relevant frameworks to evaluate business analytical projects like: DELTA
model, BADM and CRISP
DELTA plus model: It is one of the effective business analytical model that consists of 5
main elements. As per this model, companies require focuses on main 5 elements for becoming
success and analysing its overall financial performance. 5 elements of this model include:
Data quality: This element refers that companies can attract customers when they have
organized, accessible and high quality of data with them related to business information and
customers' information. It can be said that Carnival corporation & Plc needs to focus on
improving its ability to leverage unstructured data and influences the value of analytics.
Enterprise: Enterprise approach is also being used by some companies for managing
their systems. This company can manage revenue by advocating a single perspective for
analytics (Gouet Bañares, Lafuente, López and Sanz, 2020).
Leadership: Analytical companies including Carnival corporation & Plc have leaders
who helps company by leading their culture towards data driven decision-making. An effective
leaders guide employees about using analytical models for managing revenue and improving
financial performance.
Targets: Being equally analytical in all parts of business is not possible so, it needs to
target some specific areas that can be aligned with corporate objectives. By focusing on
purposeful use cases, this company can take business opportunities.
Analytical people: For analytics and using all models, employees require having some
specific skills such as: ability of spreadsheets to accomplished data scientist. So, it can be said
that by recruiting analytical professional and champions, Carnival corporation & Plc can solve
all problems that it is facing related to inventory allocation and pricing satisfaction.
There are numbers of advantages that this company might take by implementing this
analytical model and it can be aligned with its already implemented YODA management system
such as: It can help company in improving quality of data. As it is based on leadership so, it can
lead company about direction in which it should go and perform its activities (Le Huy and
Dzung, 2020). It can help in better data mining and making use of those data related to guests
and business for making price deciding and inventory allocation decision. After evaluating this
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model, some limitations have found that needs to be focused by this company if it wants to take
full advantages of this model such as: It may breach privacy of customers as company collect
information related to online transaction and others (KUMAR, 2019).
CRISP model: This Cross-industry standard process for data mining can also be
beneficial for Carnival corporation & Plc in better cruise and revenue management. It is an
effective process model and data mining methodology that can provide a complete blueprint to
companies. By making use of this model or implementing this, cruise management company can
determine business objectives in a clear manner and understanding business objectives is vital
for business performance. Flexibility of this model is one of the main key. It can also help in
producing a project plan. For taking advantages of this model, this company needs to follow all
main 6 steps such as: setting business goals as it can help in understanding business in an
effective manner (Huber, Wiemer Schneider and Ihlenfeldt, 2019). Data understanding, data
preparation, modelling, evaluating and deployment are some main steps. Overall, it can be said
that this model can help this cruise management company in managing and using customers’
related and business related data in an effective manner. Data preparation is the main step that
takes too much of time because for this, company will require collecting customers’ related data
then cleaning them. After that company will need to produce derived attributes or transforming
values for existing attributes in order to construct data. It can evaluate effectiveness of this model
and find out areas where it needs to focus for better data management. In regard to Carnival
corporation & Plc, it can be said that it can allocate inventories as per the demand of customers
and by managing customers’ related information. As like DELTA plus model, this model also
has some limitations such as: there is a lack of clarity due to numbers of steps and sub-steps.
Blind hand-offs to IT is other main limitation of this model (Huang, Naghdy and Du, 2017).
Mindless rework is other main problem that employees may face while making use of this
analytical tool (Kristoffersen and et.al., 2019).
Business analytical development model: It is one of the most used analytical model that
has numbers of models within it. Companies may use different sub models for data collection,
management, improving financial information and managing revenue. Descriptive, predictive
and prescriptive are three main analytics. With descriptive analytics, company can look at data
statistically in order to see what happened in the past (Cao, Wachowicz and Cha, 2017). It can be
in the form of data visualizations such as charts, graphs, dashboards and others. Descriptive

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analytical can helps in measuring overall performance of company such as: measuring sales,
profit, revenue and others. With this analytics, Carnival corporation & Plc can know numbers of
customers in the past and by comparing numbers of customers with current year, it can know
areas where it is lacking behind. Predictive analytics take historical data and such data are being
feed into machine learning model that helps in identifying patterns and trends. Such data are
being applied to current in order to predict that what can happen in the future or in few days or
weeks (Lepenioti, Bousdekis, Apostolou and Mentzas, 2020). The last and third one, prescriptive
analytics makes use of predictive data to the next level. As with predictive data, company can
know or predict that what can happen in the future so, as per this, it can improve its performance
by making use of courses of actions. This model provides some courses of actions or solutions
by analysing predictive data to company. So, overall, it can be said that this model is effective
and it can help Carnival company in knowing current state of business, improving performance
for the future and becoming the market leader. It can be understood with some advantages such
as: BADM can help companies in monitoring the progress of mission (Nero and et.al. 2018). It
can help Carnival corporation & Plc to increase overall efficiency, managing revenue and
increasing customers' experience. Along with numbers of advantages, it has few limitations such
as: business analytical model has lack of reliability, availability and alignment. Sometimes it can
lead low quality of underlying data. Understanding different concepts of analytical can be time-
consuming.
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REFERENCES
Books and Journals
Chen, C., Wang, W. and Li, B., 2018, April. Performance-aware fair scheduling: Exploiting
demand elasticity of data analytics jobs. In IEEE INFOCOM 2018-IEEE Conference
on Computer Communications (pp. 504-512). IEEE.
Huang, C., Naghdy, F. and Du, H., 2017. Delta operator-based fault estimation and fault-
tolerant model predictive control for steer-by-wire systems. IEEE Transactions on
Control Systems Technology, 26(5), pp.1810-1817.
KUMAR, D.R., 2019. A study on E–commerce trends and its advantages in digital era. IJRAR-
International Journal of Research and Analytical Reviews (IJRAR). 6(2). pp.276-281.
Nero, M. and et.al. 2018. Concept recognition in production yield data analytics. In 2018 IEEE
International Test Conference (ITC) (pp. 1-10). IEEE.
Richards, G. and et.al. 2019. Business intelligence effectiveness and corporate performance
management: an empirical analysis. Journal of Computer Information Systems. 59(2).
pp.188-196.
Studer, S. and et.al. 2021. Towards CRISP-ML (Q): a machine learning process model with
quality assurance methodology. Machine Learning and Knowledge Extraction. 3(2),
pp.392-413.
Wang, Y. and Byrd, T.A., 2017. Business analytics-enabled decision-making effectiveness
through knowledge absorptive capacity in health care. Journal of Knowledge
Management.
Verbeek, D., 2018. Carnival Corporation: The Challenges of Cutting Costs While Maintaining
Quality and Customer Satisfaction. Council of Supply Chain Management
Professionals Cases.
Ren, S. and et.al., 2019. A comprehensive review of big data analytics throughout product
lifecycle to support sustainable smart manufacturing: A framework, challenges and
future research directions. Journal of cleaner production. 210. pp.1343-1365.
Perakis, K. and et.al., 2020. CYBELE–Fostering precision agriculture & livestock farming
through secure access to large-scale HPC enabled virtual industrial experimentation
environments fostering scalable big data analytics. Computer Networks. 168.
p.107035.
Hammer, M., Somers, K., Karre, H. and Ramsauer, C., 2017. Profit per hour as a target process
control parameter for manufacturing systems enabled by Big Data analytics and
Industry 4.0 infrastructure. Procedia Cirp. 63. pp.715-720.
Gouet Bañares, R., Lafuente, M., López, F.J. and Sanz, G., 2020. Exact and asymptotic
properties of delta-records in the linear drift model.
Le Huy, V. and Dzung, N.D., 2020, December. Tracking Control of Rostock Delta Parallel
Robot Based on the Dynamic Model. In International Conference on Engineering
Research and Applications (pp. 846-853). Springer, Cham.
Huber, S., Wiemer, H., Schneider, D. and Ihlenfeldt, S., 2019. DMME: Data mining
methodology for engineering applications–a holistic extension to the CRISP-DM
model. Procedia Cirp. 79. pp.403-408.
Kristoffersen, E. and et.al., 2019, September. Exploring the relationship between data science
and circular economy: An enhanced CRISP-DM Process Model. In Conference on e-
Business, e-Services and e-Society (pp. 177-189). Springer, Cham.
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Cao, H., Wachowicz, M. and Cha, S., 2017, December. Developing an edge computing platform
for real-time descriptive analytics. In 2017 IEEE International Conference on Big
Data (Big Data) (pp. 4546-4554). IEEE.
Lepenioti, K., Bousdekis, A., Apostolou, D. and Mentzas, G., 2020. Prescriptive analytics:
Literature review and research challenges. International Journal of Information
Management. 50. pp.57-70.
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