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Introduction to Business Analytics and Operational Research Solution - Statswork

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In modern years, there is a growing demand in the field of business analytics. It actually means that what outcome we should get in business from the data to make better decisions. This is often sound like relating a business problem to an operation research problem. Contact Us: Website: www.statswork.com/ Email: info@statswork.com UnitedKingdom: +44-1143520021 India: +91-4448137070 WhatsApp: +91-8754446690 – PowerPoint PPT presentation

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Title: Introduction to Business Analytics and Operational Research Solution - Statswork


1
INTRODUCTION TO BUSINESS ANALYTICS AND
OPERATIONAL RESEARCH SOLUTION METHODS
WITH DECISION ANALYSIS, LINEAR PROGRAMMING,
INVENTORY CONTROL, SIMULATION AND MARKOV CHAINS
An Academic presentation by Dr. Nancy Agens,
Head, Technical Operations, Statswork
Group www.statswork.com Email info_at_statswork.com
2
TODAY'S DISCUSSION
Outline of Topics
Introduction Business Analytics Benefits of
Business Analytics Goals of Business Analytics
Markov chain Example Conclusion
3
Introduction
There is a growing demand in the field of
business analytics. It actually means that what
outcome we should get in business from the data
to make better decisions. This is often sound
like relating a business problem to an operation
research problem. The meaning of business
analytics and uses of the operation research
methods or decision making including linear
programming, inventory management, simulation and
Markov chains are explained here.
4
Business Analytics
Analytics are used to identify (i) what has
happened? (ii) What should happen? And (iii) what
will happen? In the business. These three forms
of question are categorized into Descriptive,
Prescriptive and Predictive analytics
respectively. Business analytics is the study of
data via statistical techniques, constructing
predictive models, implementing the optimizing
rule and draw a valid inference according to the
business needs. Thus, business analytics uses a
huge amount of data or simply big data to make a
profitable conclusion.
5
Benefits of Business Analytics
Business analytics is used to implement the data
mining techniques such as classification,
regression analysis, clustering analysis, etc.,
and to understand the complex data using neural
networks, deep learning and machine learning
techniques. Business analytics is used to do
quantitative statistical analysis or solving a
mathematical model to deliver justifications for
the occurrence of the problem. It can be used as
a supporting tool for conducting any multivariate
testing and A/B testing to find the relationship
or test the relationship with past decisions. It
can be used for predictive modelling to improve
business standards.
6
Goals of Business Analytics
The main goal of business analytics is to
identify which dataset will be useful and how it
can be taken forward to solve the business
problems and increase the profit, productivity,
and efficiency. In recent years, business
analytics in operational practice has become a
great interest among researchers. With the
growth of technologies, and with the large amount
of data at hand, it is important to make use of
analytics and the operation research approach to
solve many complex business problems.
7
Markov chain Example
  • Consider a bank which deals with both asset and
    liability products, and it is obvious that loans
    taken from the bank play a vital role in the
    revenue.
  • The bad loans and the paid-up loans are the
    absorbing nodes or the end state in a Markov
    chain. The absorbing node is that it has no
    transition probability to any other nodes.
  • So, as a statistical consultant, the first step
    is to understand the trends in the loan cycle
    with the previous study.
  • Contd..

8
Figure 1. Markov Chain for pattern of loans
9
Next step is to calculate the transition
probability matrix with the previous
probability. Estimate the number of loan which
belongs to each category. From the diagram, it is
clear that 60 has good loans, and 40 has bad
loans. Thus, the calculation becomes,
Contd..
10
From the final output, it is expected that 15 of
the loans are going to be paid-up loans for the
current year and 16 becomes a bad loan. The
retail industry can develop their business
insights to decrease the percentage of bad loans
in the future. In addition, if you want to
predict the same for 2 years, it is calculated as
Contd..
11
Similarly, the process is repeated until the
convergence is achieved. That is,
From the convergence result, it is identified
that 54 of the present loan will be paid fully,
and 46 will be a bad loan. Contd..
12
If you want to identify the proportion of good
loans becoming a paid loan, then you should start
with 100 of good loans and others as 0 in the
initial stage and repeat the process until
convergence is achieved.
From the results, it is identified as only 23
becomes a bad loan whereas in the previous case
it was recorded as 46.
13
Conclusion
Operational Analytics or business analytics
involves building a suitable model or developing
a predictive model to make meaningful business
decisions. It may be a transportation model, or
the Markov model, or the Linear programming
model or a simulation model the objective is to
satisfy the business needs and do a profitable
business.
14
CONTACT US
INDIA 91-4448137070
UNITED KINGDOM 44-1143520021 EMAIL info_at_statswork
.com
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