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Uncover the 7 Production Wastes with Process Mining

  • Process Improvement
  • 05. 12. 2019

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In the Fall of 1988, industry experts John F. Krafcik and Jim Womack published an article in the MIT Sloan Management Review titled “Triumph of the Lean Production System”. 

Though a little over 30 years old, its arguably considered the birth of the term “lean production,” and the start of a cultivation of teachings that continues to resonate well throughout 2019.

At the time, Krafcik and Womack explored car-manufacturing processes at Toyota’s Japanese production system, where they defined key characteristics of high-performance facilities, apart from their average-performing counterparts. 

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With the additional help of Taichii Ohno, seven mudas (無駄: Japanese for futility, uselessness or wastefulness) were identified within the facilities

seven-wastes-lean-production-minit

Use the useful mnemonic TIM WOOD to effectively remember the seven categories of waste.
Image provided by Gary Kapanowski.


With the production of physical goods, these non-value adding mudas continue to affect the success of production plants. While some that are necessary for end-customers can be hard to eliminate, others only directly contribute to waste and incur hidden costs. It’s through the holistic approach with Process Mining that wastes can be identified and quickly eliminated.

Here’s a breakdown of each muda below as well as the Process Mining involved to mend them:

1. Transportation

The first muda is transportation. Specifically, the unnecessary movement of product that risks damage, misplacement, avoidable cost or delay. Since transportation adds no value to the end product, it’s considered a process that a customer is not willing to pay for.

Process Mining helps identify this muda, by pinpointing the happy path (the most optimal path from start to finish — or in the most complicated situations — the path featuring the least amount of exceptional error conditions). Any deviations from the original happy path are called variants that should be quickly identified and isolated to prevent further waste.

2. Inventory

Whether it’s raw materials, work-in-process (WIPs), or finished goods, significant cost incurs when product is found just laying around. The reason? They haven’t had a chance to produce an income yet, so the longer they sit as inventory, the more they contribute to muda.

A continuous flow of work ensures excess amounts of inventory are minimized.

That’s the aim with Process Mining, where process discovery that involves shifting deadlines, changing priorities and other complexities are usually filled with opportunities to improve. It’s just that no one has acted on that opportunity.

3. Motion

While the transportation muda referred to damage and cost associated with unnecessary product movement, the motion muda pertains to operations involved in creating the product. 

Examples that causes irrelevant downtime include equipment wear and tear, repetitive strain or injuries for workers and neglecting maintenance for software like Robotic Process Automation (RPA).

RPA_Guide

RPA Guide: How to Prepare Data to Avoid Pitfalls

Read our guide created for decision makers and leaders responsible for making RPA a success.

In this muda, consider the effectiveness of the plant layout, process documentation, and workplace organization. Reducing people or equipment from moving more than is required to carry through the original task.

Process Mining maps out processes in a way that can be better communicated, analyzed and reported. Interactive dashboards are customized to provide necessary information to key stakeholders to capture opportunities and mitigate undesired motion mudas.

4. Waiting

Another muda is just simply waiting.

Waiting can be found when codependent events aren’t fully synchronized. Idle machines during a lunch break or shift change, bottlenecks in the production line, or unplanned equipment downtime all contribute to product downtime, waiting for the next process to occur, eventually..

These sort of bottlenecks can be easily identified with Process Mining, as they typically break through the norm in terms of time taken to process. 

Some tasks might even be ripe for an introduction to automation. However, without an active analysis of the situation, problems may just be pushed further along the production line, causing a so-called bottleneck shift (typically found in hybrid business processes).

5. Overproduction

Simply explained as production ahead of demand, overproduction is the result of producing more than needed, faster than needed, or before it’s needed. 

Caught in the economies of scale, organizations allow cheaper production rates to dictate batch quantities instead of customer needs. Once there’s a change in customer needs before a larger batch is produced, cash flow is then tied to materials that are no longer required.

With a healthy realization of the issues at hand, Process Mining can be employed to map processes. By highlighting the causes of the overproduction muda we can identify the many other problems acting as symptoms hidden by access inventory.

6. Overprocessing

The devil’s in the details, but some details are overkill.

The overprocessing muda is a result from redundant production or communication activities that add little to no value to the end product or service. Think endless process refinement, excessive approvals, and unclear customer specifications that result in a longer and more costly production.

Albeit trickier to find, the source of overprocessing can be found when decision making is done at inappropriate levels, inefficient policy communication, lack of customer input, etc. 

As such, the best method of improvement is to obtain deep visual and analytical insights into how teams, units or divisions execute the same processes to ensure business compliance.

7. Defects

Arguably, nothing cripples an organization and its stakeholders more than poor crisis management. Since spending time inspecting, fixing, discarding or reworking a product due to earlier defects in work or components results in a cascade of additional costs and delays.

With Process Mining, it doesn’t have to be the case.

Armed with a clear perspective of your processes, an unexpected event such as a recall can be thoroughly tracked as far back as needed in your end-to-end process, uncovering the root cause of the issue along the way.

This level of identification assists in assessing, understanding and coping with the situation, improving turnaround time from the moment a problem occurs to analyzing the aftermath.

Master Lean with Minit Process Mining


Having data readily available for your lean strategy is key when identifying the seven mudas. With Process Mining you have opportunity to identify, resolve and monitor the success of organizational process improvement

Once you fully understand lean processes, you'll have the knowledge to enhance, reduce or eliminate unnecessary costs and streamline business processes that help propel future growth.

Minit is a Process Mining software solution that helps enterprises unveil the true picture of their operations, enabling them to make data-driven decisions that cut costs, increase revenues and become the ultimate process heroes.

See real-world examples in our free guide: Process Mining 4 Success Stories.

Photo by Ryan Searle

Picture of Robert Heger

Written by Robert Heger

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