Stop Wasting of time

How is time wasted?

There are several ways to waste time:

• Knowledge workers are spending time on tasks that do not add value. For instance, many people complain that meetings usually waste time. The claim is that if there are fewer meetings or at least shorter ones, their "lost time" will be saved and used for more productive work.
• Knowledge workers are waiting for inputs or information for decisions, approvals, or work from a peer. For example software developers could wait for pull requests and code review.
• Knowledge workers are waiting for inputs or information for decisions, approvals, or work from the people who requested the work.

  Asking a question implies that there is somebody to answer it. On top of that, questions need to be answered in a timely manner. If there is nobody to answer the questions then the knowledge discovery cannot take place. If there is somebody to answer the questions, but they are constantly unavailable then the knowledge discovery is delayed. Delays make the individual knowledge discovery inefficient. Small inefficiencies have compounding effects. The feeling of inefficiency spreads throughout the organization. For the organization the inefficient way of working becomes an accepted routine defining how work is done.

  Managers have to establish a structure where there are people able to answer in a timely manner questions regarding “what” need to be developed and technical architects able to answer questions regarding “how” the “what” to be developed.

  Making people available to answer questions and do it in a timely manner are responsibilities of management.

• Knowledge workers are multitasking. Multitasking or working on several tasks at a time actually means working on different tasks by alternation instead of working on them strictly at the same time. That usually happens because people want to be productive. Hence while waiting for inputs knowledge workers start on a new task. It seems to be an axiom of modern knowledge work, that for every person, every minute of every day should be filled with assigned tasks. In reality multitasking leads to lower productivity and lower morale.

  Queuing theory shows that working concurrently on several tasks increases lead time, because it makes the work queues grow in size[2].

  Aslo, engaging in multitasking behavior usually incurs cognitive cost, because switching between tasks requires people to make changes to physical and mental states. The operations required to make these changes take time and resources and thereby affect performance. For example, we know that when interruptions are particularly long or taxing, people find it harder to resume their original task[3].

  In addition to the cognitive costs associated with multitasking, there are also emotional costs. For example, interruptions can increase feelings of stress and frustration[3].

• Knowledge workers are not able to dispose of time in fairly large chunks. To have small dribs and drabs of time at his disposal will not be sufficient even if the total is an impressive number of hours. Small chunks are wasted in irrelevant activities e.g. social media. As Peter Drucker pointed out:

  “To be effective, every knowledge worker needs to be able to dispose of time in fairly large chunks. To have small dribs and drabs of time at his disposal will not be sufficient even if the total is an impressive number of hours.” ~ Peter Drucker [1]

  Drucker then offers how to get a large uninterrupted chunks of time:

  1. Measure your time, keep an activity log. If we want to manage the time better, we have to know where it goes first.
  2. Identify the non-productive work. Go through all the recurring activities in the log one by one. What would happen if we would stop doing them?
  3. Identify the critical tasks from the trivial tasks and cut the trivial, time-wasting, tasks.
  4. Consolidate time into the largest possible continuing units.

Quantifying the time wasted

To comprehend the impact of time-saving measures on productivity, we need to quantify it using the Efficiency Multiplier.

Let's consider the case of Reddit's new 2021 M1 MacBook acquisition.

We recently found that the new 2021 M1 MacBooks cut our Android build times in half.

So for a team of 9, $32k of laptops will actually save $100k in productivity over 2022. The break-even point happens at 3 months.

TL;DR Engineering hours are much more expensive than laptops!

— Jameson (@softwarejameson) November 3, 2021

However, this raises a crucial question: How does a faster computer equate to increased productivity in knowledge work? Wouldn't the bottleneck for productivity be cognitive processes rather than build times? A faster computer might not reduce thinking time, but it could allow for more uninterrupted thinking periods.

The key advantage of faster builds is the allocation of larger, uninterrupted chunks of time. Considering that a significant Android app with numerous files and submodules at Zomato takes over 2 minutes for a build, this waiting time can lead developers to switch their focus, possibly to social media, often extending beyond the build time. Reducing the build time to 30 seconds or less decreases the frequency of such distractions.

So, how can we validate and quantify these time-saving benefits? This is where the Knowledge Discovery Efficiency (KEDE) comes in.

From the details in the tweet, we can calculate the claimed time saved per developer per workday, as illustrated in the table below.

We estimate that the speeding up of the builds saved 0.68 hours or roughly 40 minutes per developer per work day.

This calculation suggests that speeding up the builds saves roughly 40 minutes per developer per workday. When we apply these 0.68 hours per developer per workday to the Efficiency Multiplier formula, it indicates an expected 9% improvement in the team's average KEDE.

One assumption here is that the saved 40 minutes per day are in one single uninterrupted time chunk, while in reality, they may be divided into smaller periods. However, short periods of around five minutes may not be sufficient for knowledge workers to ponder and process information effectively.

By comparing KEDE scores before and after investing in faster computers, management can objectively verify if the projected time savings have indeed been converted into productive time for the company.