Editor’s note: A follow-up article features three specific examples of gemba walks.
With so many tools available to a continuous improvement professional, it is easy to get overwhelmed and consequently focus on a narrow grouping of tools. Experience expands the practitioner’s toolbox, but sometimes it is just as important to return to the foundations to further the path to mastery.
What Is a Gemba Walk?
A gemba (and sometimes genba) walk is the term used to describe personal observation of work – where the work is happening. The original Japanese term comes from gembutsu, which means “real thing.”1 It also sometimes refers to the “real place.” This concept stresses:
- Observation: In-person observation, the core principle of the tool
- Value-add location: Observing where the work is being done (as opposed to discussing a warehouse problem in a conference room)
- Teaming: Interacting with the people and process in a spirit of Kaizen (“change for the better”)
This last point is sometimes a bit misunderstood. In the United States, Kaizen and Kaizen events are usually thought of as a one-week push for a change, usually a step change in performance. Gemba walks can help achieve a step change but can also be used for frequent, incremental improvements – which was the original concept of Kaizen.
What Is a Gemba Walk Not?
A gemba walk is not an opportunity to find fault in others while they are being observed. It is also not a time to enforce policy adherence (except possibly for safety problems or gross violations). If a gemba walk is used punitively, employees will shut down and resistance to change will rise rapidly. A gemba walk needs to be approached from a place of mutual respect and interest in making things faster, safer, easier and just plain better.
A gemba walk is also not the time to solve problems and make changes. This is a time of observation, input and reflection. That does not mean it is the time to ignore operator ideas for improvements or stifle brainstorming, but rather to be open and observe the “real thing” – see what is really happening. If ideas or complaints arise, note them and make sure they are followed up on after the walk. Be mindful not to focus on the details too quickly without seeing the whole.
Solving Problems on the Shop Floor
A sensei routinely encourages their students to get out of the habit of conference room analysis and design, and go to the shop floor to work directly with the operators. With this approach, the need to work through problems or to understand issues at a distance diminishes. The focus shifts from problem solving after the fact, to solving problems live, and eventually to coaching operators directly on how they can solve problems themselves – without the use of a week-long Kaizen event.
The more observation and problem solving that happen with operators on a gemba walk, the more successful and enduring the changes will be. There is no rule that says a practitioner cannot take a gemba walk at any point in a process change. In fact, reviewing ideas, piloting changes and tweaking implementation issues are all great uses of the gemba walk. This is similar to the management by walking around (MBWA) strategy coined by Hewlett Packard. As a practitioner’s confidence builds in solving problems with many tools, the more problems you will solve directly on the shop floor and then be able to coach others to recognize their abilities within themselves to solve the challenges they face.
Gemba Walk Compared to Other Data Collection
A frequent objection to a gemba walk is that it cannot be as accurate as an established data acquisition system using statistical process control (SPC) to monitor and improve processes. This argument against a gemba walk is likely to come when trying to solve problems in a strict methodology, more often with individuals who are newer to continuous improvement. But there does not need to be conflict in using all available data.
The key difference between gemba walks and, say, run chart data, is that there are no restrictions or filters on the input data. The only restrictions or filters are a practitioner’s mental models (e.g., preconceived notions) that can cause observational biases based on assumptions gathered from past experience. Mental models can both help and hinder process observation.
Let’s explore this a bit further. In the case of run chart data, the interaction of two parameters is seen with snapshots over time. A run chart displays a lot of information: how any time period compares to any other time period, historical averages, and prescribed or derived control limits. Hidden in there, however, is a big assumption – that what is being measured is the key variable influencing the output of interest. Said in the more traditional fashion, the assumption is that the run chart measures the vital X driving the big Y.
The social momentum created from a run chart is a blessing and a curse. The blessing, shown in the figure below, is that it helps maintain the status quo as far as this X and Y relationship goes. A run chart also leads to the psychological effects of authority and consistency; these two social norms are powerful in regard to directing human behavior to rally around a common, central tendency.2 Because the patterns shown in a run chart are compelling, it can leave practitioners open to false security and, at times, incorrect decisions. What if the whole problem is wrong? What if the process dependency of the big Y on vital X changed such that X is no longer vital or is, at the least, diminished? What if Y is no longer relevant?
In contrast to the streamlined information from a run chart, which provides process feedback at a glance, observing a process opens an individual up to a flood of visual data. The amount of data the human eye takes in is estimated at approximately that of an Ethernet connection, or from 10 million to 100 million bits of data per second.3 That flood of data from observation can be especially overwhelming when encountering a process unfamiliar to you. This is where mental models make life easier, in a sense, because they filter the incoming data, synthesize it into accessible bits of information and deliver conclusions. Although this constantly happens without any effort – and dramatically speeds an individual’s ability to react to situations – it is not helpful on a gemba walk.
Consider supervisors providing work direction to the floor personnel; an individual’s eye tends to look at how well supervisory instruction is executed. The mental model is narrowed to how well people follow orders. The supervisory instructions, however, may be inadequate. By relaxing the mental model that restricted perceptions to only one area to illuminate problems, it is possible to be more open to finding solutions. Although this can require only a subtle shift in awareness and perception, the observed waste and subsequent conclusions may be completely different.
Being aware of mental models is the first step in allowing more data to stream into conscious observations of processes. This is one reason an outsider is a valuable team member – they tend to have fewer preconceived ideas about how the current process or system works and can facilitate team learning. With experience and presence of mind, anyone’s observation skills can improve. Those improved skills help an individual to ask better questions and to focus on mentoring operators in solving their own problems.
References
1. Wikipedia. “Genchi Genbutsu.” http://en.wikipedia.org/wiki/Gembutsu. Accessed June 11, 2012.
2. Cialdini, Dr. Robert. Influence: Science and Practice. Allyn & Bacon, Boston, 2000.
3. Unutmaz, Derya. “Researchers Calculate Human Eye Transmits Information to the Brain at the Rate of an Ethernet.” Biosingularity blog. http://biosingularity.com/2006/07/26/researchers-calculate-human-eye-can-transmit-at-the-same-rate-as-an-ethernet-connection-to-the-brain. Accessed June 11, 2012.
Editor’s note: A follow-up article features three specific examples of gemba walks.
