Collaboration

By IDI Special Invitation, Dr. Evan S. Levine

In modern analytics, many projects are carried out by groups with the tasks split up amongst collaborators. It’s a cliché, but communications technologies are a key ingredient in these collaborations. Can you imagine coordinating amongst a team of analysts without email and file sharing? With the speed at which these technologies have developed since the 1990s, it’s no wonder that we’re still working the kinks out of analytical collaborations.

There are numerous benefits of effective collaboration. Analysts can choose which tasks they perform according to their interests and skills, leading to increased capacity and efficiency. Analysts generate ideas from talking to each other, so having multiple people look at the same data often leads to new and creative approaches.

Well, that’s the idea, anyway. In reality, there are added complications that eat into these productivity gains: work has to be coordinated, no single individual is an “expert” on the project, and tasks can fall into the gaps between people’s responsibilities and not get done. Most importantly, the unpleasant, boring, and repetitive tasks also need to get divided up in a fair way. Self-sacrificing leaders will sometimes take all of these unpleasant tasks upon themselves and build up resentment towards the rest of the group, or uncaring managers can feel that these unpleasant tasks are not their responsibility and delegate them all downwards, leading to resentment amongst the group members. Finding a happy medium is key.

Good management is often the difference as to whether the benefits of collaboration outweigh the drag of the complications. I’ve supported many projects throughout my career, and often can tell within 5 minutes how the project is going to fare from the organizational and management skills of the project lead. I would expect that you’ve had similar experiences working on group projects with fellow students or coworkers. When you participate in these projects, take notes as to what works well and what doesn’t. Emulate the behaviors that are successful when you run your own projects.

When offered the chance to participate in collaborative projects, I recommend volunteering for at least one task that is outside of your established skill set. This will give you an opportunity to learn a new technique and receive prompt and constructive criticism on it from your collaborators. After all, it’s in their interest for you to do a thorough job and make them look good! Even better are the opportunities to learn a skill when there is someone else in the group who is an expert in that skill; you can pick up tips and tricks from that person much faster than you would learn them on your own. Continuing to add to your skills is also very important; it’s not good for your career to be pigeonholed as a narrowly skilled analyst.

 

This post is an excerpt from the recently published textbook Applying Analytics: a Practical Introduction. Find out more at www.applyinganalytics.com and at the book’s amazon page (here). Dr. Levine can be contacted at applyinganalytics@gmail.com.