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Build a Culture of Continuous Improvement

Learning Objectives

After completing this unit, you’ll be able to:

  • Describe the difference between a growth mindset and a fixed mindset.
  • Explain how failures open the door to learning and improvement.
  • Explain how to bring scientific thinking into daily life.
  • Start the journey of building and sharing knowledge in your organization.

Building a Learning Culture

On a typical day, we make thousands of decisions. Some decisions, like what to eat for breakfast, have predictable consequences, because the situation is clear. A clear situation is one with a simple, predictable outcome and clear best practices.

But many decisions have less predictable results, because the situation is more complicated or complex. A complicated situation may require thought and analysis, but there are still predictable outcomes and good practices.

In a complex situation or system, you can’t reliably predict outcomes in advance, even though they make sense in hindsight. One reason is that in a complex situation, you change the system when you act on it. Human conversation is an example: The person we talk to actually changes to some degree based on what we say. We in turn become different based on how they respond.

Each person is a complex system. Software, our organizations, customers, and the business environment in which we work are also complex systems. Since they’re not perfectly knowable, we need to probe, watch, and learn from what happens when we work with them.

The Three Ways of DevOps are ways of interacting with complex systems. They emphasize agility—making changes and assessing the results on a regular basis.

In the Salesforce DevOps with Copado module and in the previous unit of this module, you learned about the First and Second Ways of DevOps. The Third Way, continual learning and improvement, is about how we learn and adjust in response to what happens.

This unit describes methods to increase our ability to learn from successes, from failures, and from each other. We also look at how to embed that learning into our daily work to achieve long-term results.

Fixed Mindset vs. Growth Mindset

Neuroplasticity

The human brain is the most complex structure we know. There are roughly 86 billion neurons in the brain, each of which has 10,000 synapses or connections to other neurons.

Young children learn quickly and are readily influenced by their surroundings because their brains are just forming. As our brains lay down pathways for understanding, we often rely on existing pathways and deemphasize learning. But if we challenge ourselves to continue learning, we can actually change the structure of our brains.

The brain’s ability to change is called neuroplasticity. Our brain naturally changes over time, but we can accelerate the process through activities like exploring a new culture, learning a new language, or practicing meditation.

Growth Mindset vs. Fixed Mindset

Dr. Carol Dweck, a psychologist and researcher, found that people’s beliefs about their qualities fall on a spectrum from “fixed mindset” to “growth mindset.” Those with a fixed mindset believe intelligence, creativity, and character are innate characteristics rather than the result of systematic effort. Those with a growth mindset believe skills can be learned and that learning takes work.

The difference in these two mindsets is most evident in how people respond to failure. People with a fixed mindset are more likely to see failure as a sign that they’re not capable. People with a growth mindset are more likely to see failure as a sign they need to work harder or change their approach.

The good news is that even if we have a fixed mindset, we’re not stuck with it. Just learning about neuroplasticity and the power of our brains to change can promote a growth mindset and increase our ability to learn.

Scientific Thinking

Situational Learning

We can learn some topics and processes, such as version control, in a general way and apply what we learn in any company or team.

But other topics are unique to a particular situation, and no one knows the answer in advance. For example, how will users respond if we combine two related pages into a single page? We can imagine pros and cons, but our ideas are just hypotheses. The only way we can know is to present the combined page to users.

It’s easy to think of building software like a monologue: We create something and simply hope users appreciate it. Or, if we work for someone else, we may think of building software as just doing what we’re told.

But it’s far more powerful to approach building software as a dialogue, in which both creator and user begin from distinct points of view and interact through building and using the application. The application is part of a shared understanding that emerges from that interaction.

Because you can install Copado in your main Salesforce org, your Salesforce users can share feedback and collaborate directly with developers.

Copado user story with user feedback in the record feed

Salesforce users can collaborate with developers on Copado user stories.

When we build applications, we’re also in dialogue with the platform, the data, other parts of the system, and so on. This is why being able to change the system quickly and get as much feedback as possible helps us grow.

Situational learning demands a growth mindset, since no one can know the answers in advance. In fact, finding answers takes work. In the page example, we have to design a new version of the page (or at least a mockup), present it to users, get their feedback, and analyze that feedback.

This iterative and experimental approach is a lot like the approach taken in science.

Scientific Thinking

We may think of scientists as especially intelligent, but science requires intellectual humility. As we deliver innovation in our organizations, we need to be humble, too.

Learning means improving our mental models of how things work. When we take a scientific approach, we develop hypotheses based on these mental models, then design experiments to test the hypotheses. If the experiment disproves the hypothesis, we can learn and update our mental model.

For example, if we show users a mockup of the new page design, they might tell us that they prefer the two pages to remain separate. In that case, we learn from users that our idea wasn’t correct.

On the other hand, if users like the idea, we might decide to combine the two pages. We won’t know if all users like the combined page until we actually deliver it, but we have more confidence that they will.

Improvement Kata

When Joan’s team first started to adopt DevOps practices, she and her team learned a lot, fast. They set up version control and continuous delivery, and they saw big improvements in a short time.

But Joan knows the team still has room to improve. She decides to implement a practice based on Toyota’s approach to continuous improvement.

Toyota Kata

Since the 1980s, Toyota has dazzled the manufacturing world by producing more types and higher quality cars than their competitors. They have also been unusually open in letting others come and learn from their processes.

In the book Toyota Kata, Mike Rother describes a key practice that distinguishes Toyota from other organizations: a deeply rooted culture of ongoing experimentation and improvement. Toyota’s design and manufacturing practices change significantly from year to year, but what remains the same is a daily ritual that Rother called the improvement kata.

A kata is a series of actions that you repeat until you internalize it. The term comes from martial arts, but the concept is common to many activities including sports, dance, and music.

In this case, the kata is a ritual of continuous process improvement. It consists of four steps.

  1. Understand the direction or challenge.
  2. Grasp the current condition.
  3. Establish the next target condition.
  4. Iterate toward the target condition.

Setting the Direction and Incremental Goals

Step 1 is to set a direction or challenge that’s in line with the organization's goals and is relevant for the team. Joan wants her team to focus on reducing the time to resolve priority 1 bugs. Handling those quickly would be a huge help to the support team.

Steps 2 and 3 are to determine where you are right now and to set a goal for the next target condition. Since Joan’s team already does 2-week sprints, she decides to integrate steps 2 and 3 of the improvement kata into her team’s agile planning process. They determine that it takes 8 hours on average to resolve a priority 1 bug. She decides to aim to reduce that to 6 hours within the next 2 weeks.

In the improvement kata, the manager sets the target condition but does not determine how to achieve it. Individual workers determine how best to achieve that goal. This naturally engages the team’s creativity to find the best method. They perform a series of experiments, rather than following a plan.

Daily Iterations

The main activity in the improvement kata is the fourth step, iterating toward the target condition. Importantly, this is something that you do every day. Joan’s team already has a daily standup meeting to track work progress. Incorporating step 4 of the improvement kata into that meeting only adds a few minutes. In each daily meeting, they ask these five questions.

  1. What is the target condition?
  2. What is the actual condition now?
  3. What obstacles do you think are preventing you from reaching the target condition? Which one are you addressing now?
  4. What is your next step? What do you expect?
  5. When can we go and see what we learned from taking that step?

The team approaches these improvements as a collective challenge, and takes an experimental approach to improvements. Making this a daily ritual integrates improvement opportunities into everyday work, and brings every member of the team into the process.

Joan’s team repeats steps 2 and 3 every 2 weeks during their sprint planning. They assess their progress and assess the next target condition. If they achieve their goal, they take on a different challenge. If they don't achieve their target condition, they continue working toward that goal with the next round of daily experiments.

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