A world Without Email: Reimagining Work in an Age of Communication Overload

particular coordination protocol, we count the number of these
buckets in which at least some effort was expended toward the
coordination task. To stick with our consulting firm scenario, the
hyperactive hive mind protocol for evaluating new client requests
probably generates several dozen back-and-forth emails, with each
message corrupting a different five-minute bucket, creating a large
overall cognitive cycle cost. The meeting protocol, by contrast,
requires only one meeting per week. Assuming these meetings last
something like thirty minutes, then the protocol corrupts only six or

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so of these buckets per week, making it much less costly by this
measure.
Another relevant cost when considering workplace coordination
protocols is inconvenience. If a protocol induces a long delay for
someone to receive critical information, or requires extra effort on
the part of the sender or receiver, or leads to a missed opportunity,
then this generates inconvenience. For the sake of this thought
experiment, let’s imagine we have some sort of numerical scale for
measuring inconvenience (actual numbers don’t really matter here).
Returning to our consulting firm example, the hive mind protocol
probably scores better on this inconvenience scale compared with
the weekly meeting protocol, as the need to wait for the next meeting
before responding to a potential client might be perceived as an
inconsiderately long delay. In some cases, this might even lead to lost
business.
Shannon teaches us that we need to pay careful attention to
these costs and be willing to tinker with our protocols to find ways to
balance them optimally. In our scenario, the high cognitive cycle cost
of the hive mind protocol for dealing with client requests seems
prohibitive, even though it scores well on inconvenience. We might
instead turn to the weekly meeting protocol, which scores well on
cognitive cycle cost, and seek ways to reduce its inconvenience.
Perhaps, for example, we introduce the following standard operating
procedure: when a new client request arrives, whoever is in charge of
monitoring that inbox immediately sends a reply to the potential
client thanking them for their interest and promising a response
within a week—reducing the probability that the client ends up
annoyed by the delay. It’s still possible that a potential client could
be turned off by this response, but given the timely initial reply and
clear expectations, this worst-case scenario is made rare. This
approach slightly increases the cognitive cycle cost, as now someone
has to send a quick reply to each incoming message, but this cost
remains muted compared with what’s generated by the hive mind
protocol, which initiates an extensive thread for each new potential
client. On average, this hybrid protocol seems like it has a lower cost
than either of the alternatives and is probably therefore the right
choice for the consulting firm.
Our instinct in the knowledge work setting is to obsess about
factors like worst-case scenarios—how can we prevent bad things

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from ever happening?!—or to prefer the convenience of simple (but
costly) protocols to more finicky (but optimized) alternatives. The
information theory revolution tells us that these instincts shouldn’t
be trusted. Take the time to build the protocol that has the best
average cost, even if it’s not the most natural option in the moment,
as the long-term performance gains can be substantial.
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We’re now ready to pull together these various pieces to articulate
the central principle we’ll explore in this chapter. A key element of
any workflow is the means by which people coordinate their work.
This coordination requires communication, and whether or not you
use this terminology, this in turn requires the people involved to
agree in advance on a set of rules about how and when the
communication occurs—what we call a coordination protocol.
Most organizations default to using a hyperactive hive mind–
style protocol for most coordination activities, because it’s simple to
set up and persuade people to follow. Its flexibility also often allows
organizations to avoid worst-case scenarios. Shannon teaches us,
however, that if you’re willing to put in the hard work up front to
develop smarter protocols for these tasks, you can often drastically
reduce their long-term cost. The hard work you invest in advance to
deploy the optimized protocol will pay off many times over in the
lower cost you experience as you subsequently use it. Formally: