The new productivity formula

The productivity of an organization is a major managers’ concern. And the same applies to Scrum Masters in the form of continuous improvement. What formula can we use for improving productivity?

Let’s say we have a stable team. We don’t move people in and out. Traditional thinking suggests that a team’s productivity depends on the experience of team members. And if they work extra hard, they can do miracles.

Something like below:

Team Productivity = number of years of experience * number of hours per week

What problem do we see with relying on such a formula? We can’t manage it.

The number of years of experience is growing slowly. Consider it as a constant. And the team can increase working hours only slightly. A substantial increase is not sustainable and leads to burn-out and errors.

Therefore, consider it as a constant too. So, from the traditional perspective, team productivity is fixed.

Maybe due to this thinking, managers often leave it up to individuals to improve their productivity. Simply said, managers just push people to work harder.

Is there an alternative? Let’s try to find out what we can manage.

Can we improve productivity continuously without limits? Surprisingly, the answer is Yes. There are at least 3 major things we can manage.

Team Productivity = knowledge * adaptability * automation.

Knowledge

Evolution is closely related to the tools people use. We know this from history. We explain the productivity of different generations based on the tools people used.

The tools’ efficiency defines productivity, and the quality of work people do routinely. Technological evolution and productivity evolution are correlated.

Also, we have seen evidence that governance structure defines the pace of progress. History shows that technological evolution has a direct correlation with the governance structure.

Technology evolves in countries with a lot of freedom and support. Therefore, managers must structure governance to support the people who build and innovate. We have a wealth of information about it. We just have to learn and apply this knowledge.

Another critical part is knowledge of the system. Especially the ability to identify and solve problems. Having specialists in every area is a good thing.

However, relying on specialists for every mundane task is wasteful. Specialists must work only on the most challenging cases. Most of the time, they should innovate and teach others.

Both innovation and teaching increase the overall knowledge in the team.

Adaptability

Even if we have the knowledge, we won’t leverage it without adapting it. We have to actively look to apply new knowledge.

Having time to explore problems and apply new knowledge is critical to improving productivity.

This doesn’t mean we have to try every new tool. We must be practical about what we’ve learned. We must find places where adapting new knowledge is worthwhile. Productivity depends on the success of adapting modern technology, techniques, and skills.

Adaptation to the market state is another critical process. Focusing on the customer’s benefits is effective.

Not only does it save a lot of time and money. If we don’t adapt to the customer’s problems, some other companies will. And they will take the business.

Conway’s law reminds us of an interesting phenomenon. The architecture of products repeats the org structure. This should tell us something about how we assign responsibilities and set goals.

How efficient is the pattern of component ownership? Elite performing companies practice adjusting organizational structure to the needs of the whole product. They look for ways to simplify the process and shorten the feedback loop.

This kind of adaptability requires adjusting the way people group, interact, and split responsibilities.

Automation

Finally, the advantage of the century is automation. When we talked about ancient people, we considered their tools as a factor of productivity.

Automation of routine and tedious tasks is a measure of the modern world. Machines and computers can do some work faster, better, and way cheaper than humans.

Call a company ancient if it keeps doing routine work manually. Quality control, delivery, deployment, resource provisioning, and configuration – all must be automated.

Yes, many companies still rely on manual processes. But it’s clear now that routine and repeated work can’t be based on error-prone manual processes. This approach destroys productivity.

Elite performers show a tremendous advantage in productivity thanks to automating most of the routine work. Automation creates time for gaining knowledge, innovating, and adapting. That’s why investing in it is so perspective.

The next step is Artificial Intelligence (AI). Today people create automation. This is the way we “teach” computers to do repetitive work. With AI, the way we “teach” the machines may change. And this time may come sooner than we expect.

Conclusion

We’ve passed the time when managers could constantly push people to work long hours. This doesn’t supply the necessary productivity advantage. And we can’t improve it continuously.

What we should leverage is knowledge, adaptability, and automation. We can improve them pretty much without limits and increase the productivity of the whole team.

The new productivity formula can bring companies to unseen levels of performance.

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