The preprint of this paper appears on my blog. The main story is that we examine how diverse roles in two teams in Brazil working on requirements and their related artifacts coordinated along task dependencies using a case study method, and report on how knowledge and work dependencies affect their work.
There are a number of other great papers that are appearing in the same session, including two co-authored by Prem Devanbu. It’s a good session to be at, in my opinion.
This article isn’t a new publication but I thought I’d provide some information about it here. I did this work by analyzing email communication between team members within a large, multinational organization: almost 5000 emails in all, sent all across the organization.
We found that many email discussions involved people who were included in the discussion thread only after the first email was sent! This was surprising because I thought, initially, that if you emailed people about a topic you’d put all of them in the To/CC of the first message. Instead, in this organization, in 57% of the threads someone added a new recipient to the To/CC list as the thread went on.
In addition, I examined the messages and identified four main situations why emergence occurred:
Crisis: There was a big crisis situation, and the message was being passed to as many people as possible so that someone, anyone, might have information that will help.
Explicit requests: In the discussion, there was a specific request that a person who was not initially included in the message be involved or undergo a task. This is quite common for expertise-seeking; some people would realise that they couldn’t solve a problem and CC a third-party for help.
Announcements: Announcements were large-scale announcements of some sort, and had to reach large numbers of people.
Following-up: After a particular event, a message would be sent following up on the event. If there were people involved in the event who were not initially invited, they were included on follow-up emails.
There were a number of takeaways that affect my email habits even now – I try to ensure that people are CCed right from the start, and if someone asks me to recommend someone they should talk to, rather than simply telling them that they should speak with Person X, I actually CC Person X as part of my reply.
Adrian at the ACM Conference on Computer-Supported Collaborative Work is presenting “To Talk or Not to Talk: Factors that Influence Communication around Changesets”. He went to Zurich to work with the IBM Rational Team Concert team located there, and interviewed them, applied surveys, and did personal observations. He found out that:
Release: Their discussions often were affected by their time within the release cycle. Early on in the cycle, developers were concerned about features, but as time went on, they were more concerned about the software being released, and were much more cautious about the change sets that were being applied.
Perception: The perception around the change set was also important. If the developer was giving off a good impression, then colleagues would monitor them less. Alternatively, if a developer is giving off a poor impression, then their changes may be more heavily scrutinized.
Risk Assessment: The developers were concerned about risk. High-risk change sets heavily encouraged developers to speak with each other. For example, if the change set was large, it was considered higher risk.
Business Goals: The developers were often conscientious about code quality, but were always under pressure to release features and fix bugs. This leads to the phenomenon known as technical debt, where the developers know that the fix is inelegant and ugly, but are often unable to fix it next cycle because management pressure continues to push the developers to release more features.
These considerations may have implications on collaborative recommender tools because they suggest the contexts under which the recommender system may have to adapt itself toward.
Adrian’s posted his slides here so you can take a look!