Remote Work Theorem

Prior to the COVID-19 pandemic in 2020, working remotely was considered a privilege for few people. During the pandemic, many employees were working from home, adopting new routines and technologies. In a post-pandemic time, many people have a desire to continue working from home full time and will effectively be fully remote employees.

I have experience of working with geographically distributed teams at companies like Nokia, Realm, MongoDB, and CrateDB. While not always working from home, working remotely from an office is a way to describe the situation where all team members work from other locations but work at different offices. The same technologies and routines apply as working fully remote.

The Remote Work Theorem applies to teams or organizations of any size, and it is capturing the possible modus operandi for different work situations. The theorem can be formulated as follows.

Remote Work Theorem

For any work situation, you can only pick two of following three conditions:

• Speed of Decision-Making (synchronous collaboration, fast iteration)
• Deep Work & Flexibility (asynchronous communication, fewer meetings)
• Knowledge Retention & Scalability (strong written culture, documentation-driven)

Based on my personal experiences, the theorem is purely empirical, and no strict proof can be offered.

The theorem implies that three different combinations of work conditions exist. Each combination sets the scene for trade-offs in how the work in a team optimally can be organized.

• If you optimize for Speed and Deep Work, you might sacrifice Knowledge Retention, as decisions happen quickly but aren’t well-documented.
• If you prioritize Deep Work and Knowledge Retention, decision-making can be slow as asynchronous communication takes time - in particular if the team is spread across many time zones.
• If you focus on Speed and Knowledge Retention, you risk over-synchronization, with too many meetings and interruptions.

With the Remote Work Theorem, and the trade-offs outlined above, it is possible to design a work environment for any given team or organization. By applying an inverted work environment maneuver, the two work conditions can be found to support the desired work environment.

To mitigate the trade-offs when optimizing for Speed and Deep Work, processes can be designed. The processes will help the team to be able to communicate asynchronously as team members will know what to do next without slowing down by waiting (synchronization point) for other team members. While processes should not come before people, the processes can set the individual team members free and give them flexibility.

If Deep Work and Knowledge Retention are important, a clear team agreement on the asynchronous communication can lower the latency. An example of an agreement is that each team member spends time in the morning doing code reviews to unblock other team members. It requires a strong discipline to work in this regime as a single day missed for a reviewer, might waste a day for the other team members.

To combine Speed and Knowledge Retention will often require synchronization points (meetings). As interruptions and context switches are costly, it is important to schedule meetings either early or late in the day to give team members as long a flow time as possible. Moreover, a team agreement about meeting free days can be helpful.