Need for Analytics in a MBA
The Master’s in Business Administration or MBA is one of the more widely sought degrees in professional life by aspiring students. One of the reasons for choosing an MBA over a Master’s in Economics or a Master’s in Science, is the focus on applied sciences in industry, at the intersection of both science and commerce. Managers are supposed to take decisions in the constraint of time, information and resources for optimized value creation and a quality education in management hopes to expose and imbibe the students to these characteristics.
Increasingly businesses have started using business analytics in every aspect of decision making, it makes a case for some exposure to business analytics while during the course of study as a MBA. While Market Research and quantitative techniques in Finance are optional subjects in the MBA curriculum, there is a case for integrating business analytics in the syllabus for a MBA rather than simply open separate Master’s in Business Analytics.
Exposure to analytical techniques like clustering, segmentation , regression modeling and forecasting have always been a critical part of MBA study, but it is necessary for academia to recognize that there is big data revolution going on, and thus move beyond spreadsheet analytics to more formal and industry aligned analytical platforms
This is because business analytics is now used through out the enterprise in marketing, finance, supply chain, and human resource planning. Skills required in business analytics involve a mix of statistics, business knowledge, and programming. In addition there is considerable avenue for creative thought leadership as well as softer aspects of project management including communication to stakeholders and helping implement analytics solutions.
Business analytics skills are also in great demand , and given the global macro economic uncertainties with employment , having some business analytics skills also acts as job insurance for young MBA students. Based on my experience with MBAs and Business Analytics, I would recommend that some exposure to both SAS and SPSS languages should greatly help MBAs be more competitive in the business marketplace as well as add greater value to the organizations that they choose to join. Given the learning curve of R, and the lack of a global sales and technical support and inadequate standardization of Graphical User Intefaces, I would recommend that R be placed more as an optional subject in second year, while SAS and SPSS languages be taught compulsorily with realistically large and complex datasets (than rely on decades old classical datasets like Iris and Old Faithful).
In industry , one of the primary challenges is data management,data reconcilation and data cleaning . Indeed ensuring process quality of any corporate function is a task for new MBAs. Thus traditional quality management techniques taught in the MBA course should also focus on these important and inevitable aspects of corporate life.A brief exposure to concepts in data quality including master data management can thus produce a much more technologically literate and well enabled next generation of managers.
To produce these business analytics enabled MBA requires close synchronization with industry , and here industry needs to think long term in terms of skilled resource creation rather than simply enhancing short term brand value for attracting fresh talent, or beta testing their own Research and Develeopment at a lower cost. Sharing case studies with suitably disguised data can lead to much better teaching and learning process of business analytics within a MBA.