My earlier post on this subject, noting the need for educating business professionals beyond IT, stimulated good reflections and comments.
Since then, I became aware of a study (Sircar, Sumit (2009) “Business Intelligence in the Business Curriculum”, Communications of the Association for Information Systems: Vol. 24, Article 17). Sircar, a professor at the University of Miami (Ohio) School of Business, described the components of a business analytics minor comprising courses in statistics, quantitative analysis of business problems, and data mining.
His research at that time showed few business schools with such an analytics curriculum. That finding is disappointing as measured against the large number of IT and business professionals who need to be trained. But there are encouraging signs of change, as I observed in a recent visit to a new centre for customer analytics at Yale School of Management.
Analytics is at or near the top of IT spending priorities across a range of industries. Associated with this is the need for skilled business professionals who are comfortable with analytics. I was chatting with an executive from a major insurance company at a recent CIO conference who has led an impressive effort to build programs to implement a 360 degree view of the customers across all channels and product lines for his firm.
I asked him how he attracts the necessary talent to make these programs effective. He indicated that he has success looking to graduate students in psychology who are trained and regularly use analytical methods throughout their courses of study. Given the nature of psychology, the analytics would be people or behaviour-oriented - the right fit for the jobs he needs to fill.
On the other hand, he has not been able to find these capabilities in business school graduates, as he felt that they are weak on the quantitative methods necessary for his teams on customer analytics.
Clearly, there is a misalignment between the demand for analytics skills and the supply of trained graduates coming out of business schools. There is a critical need to train future IT professionals who will build the data architectures covering wider forms of data (structured and unstructured), the database and system administrators who need to ensure the availability of the information resource, and the quantitative analysts who will employ data mining to explore the data and build analytical models.
We also need to train business professionals who will use analytics in decision making. Companies are recognising that the ability for decision makers to apply analytics in the decision-making process is essential to improve overall business performance. Given the trend to flatter organisational hierarchies, decision making is more widely distributed - so analytics must become more pervasive.
IDC research showed that training has the highest impact on making analytics pervasive. This implies that the training of future business professionals requires the integration of analytics within domain-specific courses, such as marketing, finance, or supply chain.
“Analytics” is an umbrella term for a variety of techniques and the skills in scarcest supply are the ability to marry the appropriate technique to a specific business problem. With regard to applied analytics, one size does not fit all. Here are some examples of the different analytic techniques required for different groups of business processes:
- Customer processes benefit from the application of people-centric predictive analytics where the business user can learn which attributes are the best predictors of future customer behaviour. This knowledge can be applied for developing and measuring the impact of personalised offers to customers. Similar techniques are now being used in employee or HR analytics.
- Financial processes benefit from the application of multi-dimensional analysis (OLAP) against pre-defined financial categories enabling the setting of goals and measurement of actual business performance related to the stated goals.
- Supply chain processes benefit from constraint-based optimisation that has been perfected through the application of operations research techniques. For example, sales and operations planning attempts to balance consumer demand vs. production capacity vs. inventory
Faculty and students showed a keen awareness of the changes to the way marketing is done and the need to leverage all available information on customer behaviour. The centre offers a for-credit course that is more of a directed independent study, rather than traditional classroom learning
The heart of the course is a semester-long project working with a corporation (most recently, a financial software company) related to measuring and analysing the attitudes of their customers in order to assess the effectiveness of advertising and marketing campaigns.
They are interested in using non-traditional sources of customer data, such as unstructured social media content. Students are provided IBM software such as SPSS and Cognos and are trained on the use of the tools and coaching on applying the software to address the problem at hand. Such hands-on learning is the best way to learn how to use analytics effectively in a business process context.
The Yale centre and others like it are positioned to change the situation to begin to meet the demand for analytics-knowledgeable IT and business professionals. In a tough job overall market for business school graduates, this approach comes at the right time for students and employers alike.
Posted by Henry Morris
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