By Robin Brodrick
The Bus Factor: Why Teamwork Is More Important than You Think
What the heck is the bus factor, and what does it have to do with teamwork?
If someone at your company were to get hit by a bus, would there be several other individuals with enough knowledge to carry on and complete their projects? This is the premise of the bus factor. The term was originally coined in reference to software development projects, but has been commonplace in business settings since 1998. A high bus factor means that there are several individuals who know enough to successfully complete a project if an adverse event were to occur, such as a colleague falling ill, resigning, or going on maternity leave. Teamwork increases the bus factor for any project, and therefore reduces risk.
Other beneficial aspects of teamwork: Output quality, accountability, and morale
Being the sole contributor to a project makes it more difficult to get early and frequent feedback, which can reduce output quality. The sooner feedback is received on a project, the less likely it is that you will spend valuable time going down the wrong path. It is significantly easier for for someone to review your work and provide worthwhile feedback if they are working on the same team as you because they will already know and understand the project context. Since working on a team means that there are other contributors with a shared context, it follows that there will be more people to challenge your ideas.
In his Forbes article Why And Where Is Teamwork Important?, Edmond Lau makes an excellent point when he notes that “peer pressure is a powerful force.” This is especially true if you are working with people who you hold in high regard. Working with a group of people increases your accountability and motivates you to help the team be successful. This is particularly useful on days when you may otherwise not have had the motivation to complete a portion of the project if you were working by yourself.
The highs are higher and the lows are not nearly as low when you work on a team. Tediously working through a monotonous portion of the project or trying to fix an unexpected problem becomes more bearable when there is someone to share the pain with. And if you are working alone, there is no one to celebrate with when you finally fix the problem or finish sorting through those 4,263 lines of Excel data.
Does size matter?
In 1861, Maximallian Ringelmann discovered that the greater the number of people who pulled on a rope, the less effort each individual contributed. As he added more people to the rope, he found that the total force produced by the group rose, but the average force of each individual declined. This is often referred to as the Ringleman effect. Why is it significant? Because it discredits the theory that a team effort always results in increased effort.
According to Evan Wittenberg, Director of the Wharton Graduate Leadership Program, the research on the best team size is inconclusive. Most findings indicate that five to 12 people is best, while others note that five to nine is optimal. The number six has also come out of multiple studies. In the end, the ideal team size will depend on the task. If you want to clean a mile long stretch on the side of a highway, then a group of 20 will do it faster than a group of five. However, if you are dealing with the coordination of ideas, tasks, and motivational issues, you begin to see diminishing motivation in groups larger than five people.
Wittenberg also notes that creating a good team is not all about its size. Many companies skip the set-up portion of creating teams. It is essential to set aside time for the group to do team building and trust building exercises. The team members need to get to know each other in order to structure how they will work together. They should share their individual values so that they can create team values. Most importantly, they should “work on their team goals, their team norms and their operating principles.” (Click here for the source.)
A real world example
In May of 2015, Amanda Truesdale, Senior Director of Biostatistics and Statistical Programming at Veristat, implemented a formal team structure for her 55 person department: three pods, each with a Manager of Biostatistics and a Manager of Statistical Programming, and each with specific clients and projects.
The org chart above may make it look like the managers are responsible for the projects. However, this is not the case. Every client project is assigned a Lead Programmer and a Lead Statistician and the final outcome of the project is very much a team effort.
Team size can vary widely depending on the size and timeline of a project. The Lead Biostatistician and Lead Programmer each have one or two people who provide support to them, resulting in each core team being made up of five to six people. Extra team members would be added for large scope projects or if the project has a tight timeline.
The results of implementing a formal team structure
As is always the case with change, not everyone was excited about it at first. The Biostatistics and Statistical Programming departments ran well prior to the team structure being formally implemented, so some people did not see the need for a change. Four months later, everyone is glad that the departments are now team oriented. The new structure has increased the bus factor of the departments. It also allows managers to focus on a concrete list of clients and projects, which has simplified the lines of communication, reduced stress, and increased efficiency. From a scientific perspective, the restructure has been advantageous because people are now working on a set number of projects with a consistent client list. This allows the teams to have a deeper understanding of the protocols they are working with and of the oddities that are inherent in some projects.
Veristat has a current opening for a Manager of Biostatistics to complete the third pod. The ideal candidate is located in Montreal, QC, but could also be in the greater Boston area. Feel free to send your CV to firstname.lastname@example.org if you would like to explore this opportunity and have your PhD or Master’s degree in statistics, biostatistics, or a related field and three to five years of biostatistical experience in the clinical trials or health research environment.