Between endless planning or actionistic “just go for it,” there’s a simple middle ground for moving into uncharted territory. In iterations you achieve progress without having to “fail your way forward”.
Imagine you would like to become more active in sports. How do you go about it?
You’ve probably already thought about a few basic conditions, e.g. whether you’d prefer to do it indoors or outdoors, alone or in a group, or which sports you rule out in advance. How do you get into action now?
You could now conduct a market analysis, noting down all the options – from fitness apps for working out alone, to the various club and association offerings. You carefully evaluate everything for costs and benefits, risks and expandability. The drive to do something has already diminished significantly. Nevertheless, the facts are on the table, you decide and finally start with the chosen activity. After a few weeks, you realize that the course dates or the chosen sport don’t fit after all. You have decided so carefully, this must be the right thing to do! You force yourself through a few more weeks and gradually let the activities fall asleep. Failure.
The “common sense”
Fortunately, when it comes to personal decisions, most people act differently: of course, you briefly gather information, ask friends for their recommendations and what it takes to get started. From a manageable selection of options, you choose one that is easy to implement for the beginning – and off you go! After the first few weeks, you find that the sport you’ve chosen is fun, you buy better equipment, and you look for groups to get active in. Little by little, your sporting activities develop, you are satisfied. Success!
Without thinking too much, you have applied the PDCA approach to implementing change in the second variant. Intuitively, we choose this for the most part when faced with a confusing task where we prefer to proceed piece by piece or in unfamiliar territory when we have to choose between options without knowing exactly what the consequences will be.
This approach can be applied systematically for implementing changes or learning processes in companies.
Plan – Do – Check – Act
PDCA sounds new, but it is not. The method was already described by Francis Bacon in the 17th century as a procedure for gaining scientific knowledge: Form hypothesis, conduct experiment, observe & draw conclusions.
In the 20th century, the procedure became known as the Deming Circle with the phases plan – do – check – act (sometimes also “adapt”). Designed for quality assurance processes, it quickly found its way into lean manufacturing as a basis for continuous improvement and finally into agile methods.
Unlike classic plan & execute, PDCA is about making and checking a reasoned hypothesis about the consequences of doing something, rather than complete analysis and predetermination of all possibilities.
But PDCA is also not “just get on with it”, because there is a relevant planning phase. And unlike “failing your way forward” or “learning from mistakes,” PDCA works without having made mistakes before. Iteration makes it possible to learn systematically from the results, even if no mistakes have been made.
Thus PDCA is especially suitable for
- extensive topics, which can only be planned through at the beginning with great effort (classic projects, where the conception would take longer than the requirements would last);
- new topics where not everything can be planned at the beginning because not all factors are known (gaining knowledge through experimentation);
- improvement of existing, complex processes (i.e. processes where cause-effect relationships are not known, cf. Cynefin framework) in small steps, in which the effects are observed or measured and used for readjustment.
Just do it – with preparation
How can this be applied in everyday work? It’s best to start with a small topic, a new idea, for which complete market research is not worthwhile. Let’s say you want to improve the sense of togetherness in your hybrid team.
Gather everyone you think will be affected by the idea, who can benefit from the idea, or who is involved in its implementation. Consider the current situation surrounding the idea. What is the purpose of the idea, what benefits can it bring? What are starting points for putting the idea into practice?
Make a hypothesis: If we do the following, we expect these effects. Think about how you will measure the desired results.
Determine steps and subtasks for how to initially implement the idea and agree on an early date to put it all to the test.
In the example, the team gets together. After a brief discussion, everyone agrees on what they particularly miss (the Klönschnack – Northern German for “informal conversation” – on the way to lunch together) and what wouldn’t work at all (hybrid Klönschnack meetings in the appointment calendar).
They hypothesize “if we continue to go to lunch together on site and regularly swap between home office and office in such a way that everyone is in the lunch group once, everyone will feel up to speed again.”
For the next 4 weeks, the team wants to set up an attendance plan so that the mixing succeeds.
Implement the steps discussed. To ensure that the test phase is also reached if possible, the plan should contain enough leeway for the manner of implementation to be able to react to circumstances. The hypothesis must still be testable even if there are changes in the procedure.
For example, in the example, if attendance at the office or home office is required due to childcare, the plan can be quickly adjusted.
Important: In the event of major obstacles, it is better to abort and carry out the check phase ahead of time than to continue wasting effort.
In this phase, you check which effects have occurred. Even if the cause is not always clearly identifiable, you simply first record all observations found.
So you sit down with the team again after the 4 weeks and collect the experiences. As with the retrospective, you check what was good, what can be expanded, what would need to be changed.
Then you evaluate: Is the result okay for you? Where do you want to readjust to achieve even better results? Can the whole thing now be rolled out one step larger?
And of course, both the readjustment and the roll-out can be started again as a PDCA cycle.
In the example, the team now decides together whether the goal has already been achieved or with which of the points found in the retrospective they would like to go into the next iteration.
Variations of PDCA
The PDCA cycle underlies many incremental change procedures, here are a few examples:
Quality management- DMAIC
Here, the focus is on a detailed hypothesis that can then be precisely tested. For this purpose, the planning is divided into the steps Define, Measure, Analyze.
First, the status quo including measured values is determined and analyzed where changes need to be made in order to achieve desired effects. The achievement of objectives can then be precisely measured in the check phase.
This procedure makes sense for easily measurable key figures in processes that have already reached a certain maturity, so that the levers can be estimated quite well, e.g. in production.
Continuous improvement – Kaizen
Established, complex processes can be improved well in small steps. Planning will be kept short, because the process is known and rather small changes will be implemented.
The focus here is on the iteration of small advances, i.e. the Act phase.
Dynamic environment – Agile methods
Agile approaches limit planning to the bare essentials, to the near future. The focus is on customer orientation, which is checked in the Check phase. In addition, the Act phase is also important here for preparing the next iteration.
Short planning and frequent checks are useful, for example, when adapting quickly to frequent, unspecific changes.
Conclusion and criteria for success
PDCA is a simple, dynamic, basic method for change and learning when the first step is difficult because the mountain seems too big, or the direction to the top is lost in the fog.
Follow these success criteria and quickly achieve actionable results:
- When planning, think of it as formulating a hypothesis. Planning is not only preparing the “Do”, but also preparing the “Check”.
- Don’t make the implementation phase too short, they often need some time to collect enough observations as well.
- Make the implementation phase as short as possible, not all desired effects need to be implemented in one iteration.
- Dare to continue, even if a hypothesis is not realized, keep at it!