Rooting out process or system wastes along with their causes is a key step for effective fat-to-lean transformation endeavor. A handful of Root Cause Analysis (RCA) tools can be used to eliminate wastes. However, institutionalizing a waste elimination culture requires adopting a structured RCA methodology rather than tools. And here where the seven M’s of management can be leveraged to serve as an RCA analytical approach to strip out wastes in any industry or business.

The seven M’s (Man, Method, Machine, Material, Measurement, Mother Nature, and Mindset)-with all their  variations- have been used in business management for so long. Though, in the book Driving Operational Excellence by Ron Crabtree– the seven M’s are leveraged creatively by linking them to the Eight Types of Waste.

Before digging deeper in how the seven M’s can be used in waste elimination, let’s have a quick overview on the definition of each component:

1. Man refers to the manual and mental skills used by a person to execute an assignment.
2. Method is the sequence and steps necessary to convert material or information into a product or service.
3. Machine is a mechanical, electrical or electronically-operated device used to perform a task.
4. Material is the physical matter or information converted or acted on to create another form with added value.
5. Measurement refers to an action using a physical device to record a characteristic and compare it to a standard or expected outcome. Notice that Measurement is a possible cause of waste only if the cause is the instrument itself. If the person taking the measurement causes the error, waste is categorized as either Man or Methods.
6. Mother Nature is the environment and immediate surroundings of the task or process. Examples of Mother Nature are weather, humidity, moisture, temperature, wind, noise, dust, odors, lighting, ground, and vibration.
7. Mindset refers to the fixed mental attitude about a situation, event or belief. It may be derived from culture, value system, experience, or management directives. Mindset as a cause of waste is characterized by inflexibility, and it does not allow for change or new ideas.

The seven M’s-eight Wastes root cause analysis approach is premised on investigating each type of waste from the perspective of every “M”. Each type of waste is examined as a prospect effect of an M, then analysis is continued until the root cause is caught. The cycle continues for each recognized waste against the 7 M’s. Fishbone Diagram and Mind Mapping are excellent tools to visualize the analysis.

In investigating prospect causes that effect Defect as the first type of waste, the effect is mapped to each one of the 7 M’s as shown in the below mind-map. Then, each M is further probed to dig out a probable root cause. For Man, lack of training or poor skills could lead to producing defected output of a process. Looking through the Machine lens, lack of preventive maintenance or wearing out tools would result in a lower throughput yield. From the perspective of Mindset, a “we’ve always done that” culture is a prime fallacy that accepts defects and elects to maintain the status quo. At the end, all M’s are scrutinized against the selected waste type until root causes are identified.

Once root causes are identified efforts are directed towards eliminating them. If high percentage of defects, for instance, is deemed a  consequence of insufficient job training, proper training programs should be compiled to develop the skills of the workforce. And if using raw material with inconsistent quality causes defected products, improvement efforts could be extended to the supplier’s premises rather than manipulating machine parameters to absorb material inconsistencies.

Root cause analysis of Wastes through the lenses of the seven M’s is a creative lean thinking. In one way, it allows lean practitioners to look into causes from different angles. At the same time, it provides a structured methodology that enables standardization across the organization in hunting for root causes without overlooking many of the hidden wastes.