Introduction to Business Analytics and Operational Research Solution - Statswork

1. INTRODUCTION TO BUSINESS ANALYTICS AND OPERATIONAL RESEARCH SOLUTIONMETHODS WITH DECISION ANALYSIS, LINEAR PROGRAMMING, INVENTORY CONTROL, SIMULATION AND MARKOVCHAINS An Academic presentationby Dr. Nancy Agens, Head, Technical Operations, Statswork Group: www.statswork.com Email:info@statswork.com

2. TODAY'SDISCUSSION Outline ofTopics Introduction BusinessAnalytics Benefits of Business Analytics Goals of Business Analytics Markov chain Example Conclusion

3. Introduction There is a growing demand in the field of businessanalytics. 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 researchproblem. The meaning of business analytics and uses of the operation research methodsor decision making including linear programming, inventory management, simulation and Markov chains are explainedhere.

4. BusinessAnalytics Analytics are used to identify (i) what has happened? (ii) What should happen? And (iii) what will happen? In thebusiness. These three forms of question are categorized into Descriptive, Prescriptive and Predictive analyticsrespectively. 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 businessneeds. Thus, business analytics uses a huge amount of data or simply big datato make a profitable conclusion.

5. Benefits of BusinessAnalytics Business analytics is used to implement the data mining techniquessuch as classification, regression analysis, clustering analysis, etc., and to understand the complex data using neural networks, deep learning and machine learningtechniques. Business analytics is used to do quantitative statistical analysisor solving a mathematical model to deliver justifications for the occurrence of theproblem. 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 pastdecisions. It can be used for predictive modelling to improve businessstandards.

6. Goals of BusinessAnalytics 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, andefficiency. In recent years, business analytics in operational practice has become a great interest amongresearchers. 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 businessproblems.

7. Markov chainExample 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 therevenue. 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 othernodes. So, as a statistical consultant, the first step is to understand the trends in the loan cycle with the previousstudy. Contd..

8. Figure 1. Markov Chain for pattern ofloans

9. Next step is to calculate the transition probability matrix with the previousprobability. Estimate the number of loan which belongs to eachcategory. From the diagram, it is clear that 60% has good loans, and 40% has bad loans. Thus, the calculationbecomes, 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 badloan. The retail industry can develop their business insights to decrease the percentage of bad loans in thefuture. In addition, if you want to predict the same for 2 years, it is calculatedas Contd..

11. Similarly, the process is repeated until the convergence is achieved. Thatis, From the convergence result, it is identified that 54% of the present loan will be paid fully, and 46% will be a badloan. 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 isachieved. From the results, it is identified as only 23% becomes a bad loan whereas in the previous case it was recorded as46%.

13. Conclusion Operational Analyticsor 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 profitablebusiness.

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