ITM203
Marketing Information Systems
Assignment No.I
Assignment Code: 2013ITM203B1 Last Date of Submission: 15th October 2013
Maximum Marks:100
Attempt all the questions. All the questions are compulsory and carry equal marks.
Section-A
Ques. 1 What are the reasons for the existence of an ‘internal documentary system’ (internal
accounting system) within the organization? Explain the significance of such a system
to the marketing information system.
Ques. 2 List the various components of a Marketing Information System and explain the
purpose of each in detail.
Ques. 3 To survive in highly competitive markets, companies need to be able to develop the
marketing function and scale it up on “Internet time” with best-of-class decision
support solutions for customer relationship management, sales force automation,
market research, marketing communications, logistics, and product development.
Comment on this statement. Justify your views with examples.
Ques. 4 List various phases of marketing research process and explain how Information
systems can be used to improve this process
Section-B
5. Case Study:
Design a plain for developing a Marketing Information System for an Automobile dealer. Specify various sources of data input, process and various queries and reports you will include in this system. Explain how this system will provide data to various users at different levels of an organization. Give example of each.
ITM203
Marketing Information Systems
Assignment No.II
Assignment Code: 2013ITM203B1 Last Date of Submission: 15th November 2013
Maximum Marks:100
Attempt all the questions. All the questions are compulsory and carry equal marks.
Section-A
Ques. 1 Describe the following terms :
a).Distributed decision support systems and marketing information system
b).Functions of decision support system.
Ques. 2 Describe the international/multinational/global marketing information system model.
Explain various problems inherent in the operation and coordination of a multinational
/global marketing information system.
Ques. 3 What is market Analytical system? List and explain various data mining tools and
techniques used by this system for supporting marketing decisions.
Ques. 4 “Marketing Intelligent System is not purely a computer-based system. It is a total
system that incorporates human processes for interpreting and processing
information into intelligence.” Comment on this statement.
Section-B
Case Study: BI Helps Allergan Monitor Sales Data
The 12-year-old Allergan India is a pharmaceutical that specializes in ophthalmic products. A joint venture between Allergan and Nicholas Piramal, the Rs 100-crore company offers medication for conjunctivitis, dry eyes and glaucoma and has about 17 percent of the Rs 430-crore Indian ophthalmic pharmaceutical market. Like other pharmaceutical business, Allergan knows the importance of an extensive downstream strategy. It prides itself on having the largest reach in the Indian ophthalmic industry with its network of 10,000 ophthalmologists. The company's primary points of sale are 18 clearing and forwarding agents (CFAs). From there products go to the distributor, and the chain goes down a couple of tiers, to the wholesaler, retailer and chemist outlets. Between 900 and 1,200 distributors and about 1.2 lakh small distributors and stockiest constitute secondary sales.
This vast network creates plenty of scope for data inaccuracies. As the company grew, it became increasingly crucial to monitor parameters like DSO (Day Sales Outstanding), which is used to gauge the performance of every division and DOH (the Day's On Hand), which is a measure of inventory. It was then that they realized there was a fair amount of inefficiency in the system. That's when we decided to introduce BI tracing the need for RUBIC (Re-usable Business Intelligent Components). The association with Rubik's cube is no accident. The cube represented the two things Allergan wanted from its IT team: a single version or block of truth and multiple sides to look at it.
Which is why like most companies, Allergan, chose to implement BI: to give the business more actionable information. But, Allergan also needed BI to create a platform that its executives could collectively work off. The year 2006 saw a decision to implement a BI solution that could throw up solutions to this problem. In 14 months, with Mindtree (who had helped build Empower) as their technology partner,
Rajan set up RUBIC. The tool had an SQL 2005 server at the backend and an extraction transformation loading (ETL) tool in the middle. The ETL extracts and cleans data then coverts it into a standard format. It then puts the data into a local ERP that feeds the data warehouse. The warehouse is fed from various transactional level systems. A number of analytics, static and dynamic query capabilities were built on this. Reports are available through a presentation layer (on Windows Share Point), and allowed a comprehensive representation of various key business performance indicators.
His solution paid off in a big way. While the rest of the pharmaceutical industry grew between 5 and 6 percent in the last fiscal, Allergan India registered 20 percent growth. Rajan modestly acknowledged that some of that lead is thanks to RUBIC. It also improved the company's day sales outstanding (DSO) and its inventory levels. Post-RUBIC, DSO levels dropped by 10 percent and Allergan achieved what few of its pharma peers have managed: it maintains an inventory of less than 20 days. The industry average, says Rajan, is about 45 days.
Figures aside, the biggest advantage RUBIC offers Allergan is the power of informed decision-making. "Earlier, a little bit of guesstimate and a little bit of gut feeling would have seen a decision through. Today, all decisions are data driven," Rajan says.
5. Case Questions:
a) What are the various sources of data Allergan has? Why we can not use Marketing Information System for analyzing that data?
b) Explain how business warehouse can look at data from various dimensions, and generate as many reports as we want. Give an example to support your answer.
c) What type of different mining techniques can be used by Allergan to analyze sales data and what kind of strategic decisions they can make.
Marketing Information Systems
Assignment No.I
Assignment Code: 2013ITM203B1 Last Date of Submission: 15th October 2013
Maximum Marks:100
Attempt all the questions. All the questions are compulsory and carry equal marks.
Section-A
Ques. 1 What are the reasons for the existence of an ‘internal documentary system’ (internal
accounting system) within the organization? Explain the significance of such a system
to the marketing information system.
Ques. 2 List the various components of a Marketing Information System and explain the
purpose of each in detail.
Ques. 3 To survive in highly competitive markets, companies need to be able to develop the
marketing function and scale it up on “Internet time” with best-of-class decision
support solutions for customer relationship management, sales force automation,
market research, marketing communications, logistics, and product development.
Comment on this statement. Justify your views with examples.
Ques. 4 List various phases of marketing research process and explain how Information
systems can be used to improve this process
Section-B
5. Case Study:
Design a plain for developing a Marketing Information System for an Automobile dealer. Specify various sources of data input, process and various queries and reports you will include in this system. Explain how this system will provide data to various users at different levels of an organization. Give example of each.
ITM203
Marketing Information Systems
Assignment No.II
Assignment Code: 2013ITM203B1 Last Date of Submission: 15th November 2013
Maximum Marks:100
Attempt all the questions. All the questions are compulsory and carry equal marks.
Section-A
Ques. 1 Describe the following terms :
a).Distributed decision support systems and marketing information system
b).Functions of decision support system.
Ques. 2 Describe the international/multinational/global marketing information system model.
Explain various problems inherent in the operation and coordination of a multinational
/global marketing information system.
Ques. 3 What is market Analytical system? List and explain various data mining tools and
techniques used by this system for supporting marketing decisions.
Ques. 4 “Marketing Intelligent System is not purely a computer-based system. It is a total
system that incorporates human processes for interpreting and processing
information into intelligence.” Comment on this statement.
Section-B
Case Study: BI Helps Allergan Monitor Sales Data
The 12-year-old Allergan India is a pharmaceutical that specializes in ophthalmic products. A joint venture between Allergan and Nicholas Piramal, the Rs 100-crore company offers medication for conjunctivitis, dry eyes and glaucoma and has about 17 percent of the Rs 430-crore Indian ophthalmic pharmaceutical market. Like other pharmaceutical business, Allergan knows the importance of an extensive downstream strategy. It prides itself on having the largest reach in the Indian ophthalmic industry with its network of 10,000 ophthalmologists. The company's primary points of sale are 18 clearing and forwarding agents (CFAs). From there products go to the distributor, and the chain goes down a couple of tiers, to the wholesaler, retailer and chemist outlets. Between 900 and 1,200 distributors and about 1.2 lakh small distributors and stockiest constitute secondary sales.
This vast network creates plenty of scope for data inaccuracies. As the company grew, it became increasingly crucial to monitor parameters like DSO (Day Sales Outstanding), which is used to gauge the performance of every division and DOH (the Day's On Hand), which is a measure of inventory. It was then that they realized there was a fair amount of inefficiency in the system. That's when we decided to introduce BI tracing the need for RUBIC (Re-usable Business Intelligent Components). The association with Rubik's cube is no accident. The cube represented the two things Allergan wanted from its IT team: a single version or block of truth and multiple sides to look at it.
Which is why like most companies, Allergan, chose to implement BI: to give the business more actionable information. But, Allergan also needed BI to create a platform that its executives could collectively work off. The year 2006 saw a decision to implement a BI solution that could throw up solutions to this problem. In 14 months, with Mindtree (who had helped build Empower) as their technology partner,
Rajan set up RUBIC. The tool had an SQL 2005 server at the backend and an extraction transformation loading (ETL) tool in the middle. The ETL extracts and cleans data then coverts it into a standard format. It then puts the data into a local ERP that feeds the data warehouse. The warehouse is fed from various transactional level systems. A number of analytics, static and dynamic query capabilities were built on this. Reports are available through a presentation layer (on Windows Share Point), and allowed a comprehensive representation of various key business performance indicators.
His solution paid off in a big way. While the rest of the pharmaceutical industry grew between 5 and 6 percent in the last fiscal, Allergan India registered 20 percent growth. Rajan modestly acknowledged that some of that lead is thanks to RUBIC. It also improved the company's day sales outstanding (DSO) and its inventory levels. Post-RUBIC, DSO levels dropped by 10 percent and Allergan achieved what few of its pharma peers have managed: it maintains an inventory of less than 20 days. The industry average, says Rajan, is about 45 days.
Figures aside, the biggest advantage RUBIC offers Allergan is the power of informed decision-making. "Earlier, a little bit of guesstimate and a little bit of gut feeling would have seen a decision through. Today, all decisions are data driven," Rajan says.
5. Case Questions:
a) What are the various sources of data Allergan has? Why we can not use Marketing Information System for analyzing that data?
b) Explain how business warehouse can look at data from various dimensions, and generate as many reports as we want. Give an example to support your answer.
c) What type of different mining techniques can be used by Allergan to analyze sales data and what kind of strategic decisions they can make.
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