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Making a Systematic Business Case for Marketing Analytics

Business analytics is a hugely popular area these days. I started working in this field in 2005 back in India at MeritTrac. Even that time in Bangalore every other person I used to meet was working in the analytics business. India has many business analytics outsourcing firms and is expected to lead the global analytics services business by 2015 with 70% market share [PDF].

Due to the "big data," (huge amounts of data that are piling up at unprecedented speeds) and issues related to law, privacy, and trade secrets, large corporations prefer to set up in-house analytics divisions. They can be at the enterprise level or at the SBU levels. In either case, the cost of implementation can run in millions. The two main direct costs relate to the IT systems (hardware as well as software) and the human resources. Vendors such as IBM, SAS, and Oracle are major players in the analytics IT systems market and their systems are costly due to the scale of the client companies' operations. Human resources are currently quite expensive because there is a major shortage of skilled analytics professional people. Read McKinsey report here for better grip on this topic.

Whereas analytics benefit large corporations, there is no reason why it shouldn't provide the same advantage to small and medium size enterprises. But, considering the prohibitive costs, how can their executives even start to make a business case for analytics? The benefits of analytics can be large but can be overshadowed by the costs. In order to address this issue, I spoke at the SES Conference in Singapore the last month. The presentation is embedded below. I tackle the problem from a marketing manager's point of view. Therefore the case has to be first made to the marketing department. Of course, HR will jump and say that the cost of hiring will take up all their hiring budget. To tackle this objection, I go in some detail discussing various alternatives. Next I discuss the strategies for talking to the finance and IT departments.

One of the two key ideas in the presentation is categorizing your organization based on the data-driven culture and the existing analytics usage. I create a 2X2 matrix and suggest the type of anlytics you can propose based on in which square your organization falls.

Type of Organization and the Proposed Analytics 

For example, if your organization never used analytics and the culture (mainly the top management) is not data-driven then you can simply stick to "descriptive analytics." This includes dashboards and scorecards. On the other hand, if you already use analytics and the culture is also highly data driven, you could go ahead and use "prescriptive analytics." This comprises game theoretic and other mathematical modeling.

If you have any comments, feel free to write them in the section below. I am currently writing this as an article.


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