Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/123456789/10860
Title: Go-to-market strategy for MDM solutions
Authors: Singh, Ashit 
Kakaraparti, Srinivasarao 
Keywords: Marketing management
Issue Date: 2009
Publisher: Indian Institute of Management Bangalore
Series/Report no.: PGSEM-PR-P9-36
Abstract: Master data is business crucial data about customers, products, suppliers etc. Master data is stored in multiple, disconnected systems/databases. Master data management describes a set of disciplines, technologies and solutions used to create and maintain consistent, complete, contextual and accurate business data for all stakeholders (users, applications, data warehouses, processes, trading partners). Improper master data leads to multiple business challenges like reduced sales effectiveness, sub-optimal procurement decisions, and even delayed Go-to-market process. Poor master data quality can lead to companies failing to capitalize on market opportunities when introducing new products. The following examples show the gravity of business losses from poor master data. The Cost of Inaccurate Product Data in Consumer Products/CPG: The use of inaccurate and outdated data in invoicing and purchasing orders results in delivery errors and lost sales. A 2003 report by A.T. Kearney found that delivery errors cost the retail and consumer products industries about $40 billion annually. In Industrial Catalogs: Another study, released by AMR Research, revealed that 30% of items in product catalogs contain errors, requiring 25 minutes per SKU to correct. This study also found that incorrect product data results in returned shipments, delays in payment or deductions on invoices, and costs between $60 and $80 per item. 5 High Tech: Maintaining a single part master code costs an average of $1000 per year. For a company with 10,000 part masters, 10% duplicate data, and 10 connected systems each of which costs $50k per year to connect the total savings potential is at least $1.5 million per year. Banking and Insurance industry: In 2007 alone, poor quality data cost the insurance industry US$14 billion and the banking industry US$27 billion in operating costs. As we can see above, hardly any industry is spared of bad data malaise. Market needs for MDM solutions are strong, and many vendors are trying to address these problems with myriad solution offerings. Established IT majors like IBM, Oracle, and SAP have invested fortunes building and selling MDM products, but adoption rate is very slow. Using both primary and secondary data, we have tried to come up with an effective Go-to-market strategy that can help in taking a MDM solution to the Indian customers.
URI: http://repository.iimb.ac.in/handle/123456789/10860
Appears in Collections:2009

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