Designing a Business Analytics program, Part 3: Structure

This post continues two earlier posts (Part 1: Intro and Part 2: Content) on Designing a Business Analytics (BA) program. This part focuses on the structure of a BA program, and especially course structure.

In the program that I designed, each of the 16 courses combines on-ground sessions with online components. Importantly, the opening and closing of a course should be on-ground.

The hybrid online/on-ground design is intended to accommodate participants who cannot take long periods of time-off to attend campus. Yet, even in a residential program, a hybrid structure can be more effective, if it is properly implemented. The reason is that a hybrid model is more similar to the real-world functioning of an analyst. At the start and end of a project, close communication is needed with the domain experts and stakeholders to assure that everyone is clear about the goals and the implications. In between these touch points, the analytics group works "offline" (building models, evaluating, testing, going back and forth) while communicating among the group and from time to time with the domain people.

A hybrid "sandwich" BA program can be set up to mimic this process:

• The on-ground sessions at the start and end of each course help set the stage and expectations, build communication channels between the instructor and participants as well as among participants; at the close of a course, participants present their work and receive peer and instructor feedback.
• The online components guide participants (and teams of participants) through the skill development and knowledge acquisition that the course aims at. Working through a live project, participants can acquire the needed knowledge (1) via lecture videos, textbook readings, case studies and articles, software tutorials and more, (2) via self-assessment and small deliverables that build up needed proficiency, and (3) a live online discussion board where participants are required to ask, answer, discuss and share experiences, challenges and discoveries. If designing and implementing the online component is beyond the realm of the institution, it is possible to integrate existing successful online courses, such as those offered on Statistics.com or on Coursera, EdX and other established online course providers.

For example, in a Predictive Analytics course, a major component is a team project with real data, solving a potentially real problem. The on-ground sessions would focus on translating a business problem into an analytics problem and setting the expectations and stage for the process the teams will be going through. Teams would submit proposals and discuss with the instructor to assure feasibility and determine the way forward. The online components would include short lecture videos, textbook reading, short individual assignments to master software and technique, and a vibrant online discussion board with topics at different technical and business levels (this is similar to my semi-MOOC course Business Analytics Using Data Mining). In the closing on-ground sessions, teams present their work to the entire group and discuss challenges and insights; each team might meet with the instructor to receive feedback and do a second round of improvement. Finally, an integrative session would provide closure and linkage to other courses.