Process Mining can find 5 problems being called, Muda, Muri, Mura, Mo-re, Miss in the target process.
Quality management as typified by Total Quality Control (TQC) is basically about solving various problems in the execution of business operations and aiming for reform and improvement.
In particular, TQC has been actively used in manufacturing plants, but it has also been applied to a variety of industries and corporate activities, including logistics, service, purchasing and sales. In recent years, the terms TQC and quality control have become less common, but the concepts and methods are universal and still valid today.
In the field of quality control, issues and problems to be improved are grouped into three main categories, which are called “darari” (muda, mura, and muri) or “3Ms”. In addition to these three items, More(mo-re) and Miss -Mistake are added to the 3Ms and called “5Ms”
The 5Ms is, of course, a framework that can be used for process mining analysis based on event logs. In fact, it is a familiar and simple term that provides an excellent starting point for smooth analysis implementation.
So, in this article, we will outline the 5Ms and tell you how they relate to process mining analysis methods.
What is 5M?
First, let’s discuss each of the 5M’s.
Muda can be translated in English as “Inefficient”.
It is a task that takes too long to complete because there are too many steps to accomplish the objective, or because it is too complex, or because it continues to be a formality that does not need to be done in the first place. It is an activity that does not generate much or no value. As these activities are literally “wasteful,” they need to be reduced or eliminated.
Muri is “over-burdened” in English.
Even if the number of cases to be processed is very high, or even if the number of cases is not so high, the number of cases waiting to be processed is rapidly overflowing due to the low number of staff assigned to the case. The result is stagnation and backlog of business. A “bottleneck. The number of projects and processing capacity are not in balance, and an excessive load is being placed on them.
Mura is “inconsistent” in English.
Inconsistency is, simply put, Too many variations in work procedures. If manuals don’t exist, or even if they do exist, they are not being used, leaving a large part of the process to the discretion of the individual, the procedure will vary from person to person. As a result, the throughput varies widely and the quality of the output varies.
In addition, although the basic procedure exists, if there are more cases where the flow of the procedure is complicated due to exceptions to the situation in the field, it is also an inconsistent business process.
Basically, the improvement measures for inconsistency are to reduce exception handling and standardize the process.
More is “omission” in English.
It means intentionally or inadvertently skipping a procedure that should be done. For example, in the inspection process of a production line, it is a customary practice to perform only three types of inspections and then skip them even though there are four types of inspections to be performed. Since some of the inspections that should be done are cut back, this may lead to accidents when the purchaser uses the product or to a recall.
In addition, from a compliance perspective, omission of a specific activity is a clear violation of compliance in a business where the work to be done is strictly regulated.
Since a deviated process that should not be allowed, you need to consider improvement plans such as providing training and education to ensure that the process is implemented, giving a systematic framework to prevent omission, and issuing alerts through continuous monitoring.
The word “miss” is “mistake” in English. To begin with, the Japanese word “mistake” is a diversion from this English word. It also includes the meaning of “error”.
A mistake is a human error, that is, a variety of mistakes made by the staff in charge of a task. Mistakes such as entering the wrong operating procedure or inputting the wrong value cannot be left as-is, but must be corrected by returning to the previous process or redoing the same operation.
The more mistakes are made, the more repetitive and wasteful work is required, and the more steps are required, the more “muri” and “mura” are generated. In other words, the cause of waste, wastefulness and unevenness is “mistakes,” so creating a system that prevents mistakes and RPA automation is an effective improvement measure.
Identification of 5Ms in Process Mining Analysis
Next, we will briefly discuss which of the various analytical functions of process mining analysis should be primarily used to identify the 5Ms, i.e., muda, muri, mura, more and miss.
Muda was an observable occurrence event, which was performing work that did not generate value. This is an issue of reduced efficiency and productivity.
In process mining analysis, after creating an as-is process model (flowchart) from the event log data, we first perform a “frequency analysis” to check how many cases are processed and where in the activities that make up the process and how many cases are flowing to the next process. This is because where there is a high volume of processing, there may be wasted steps lurking.
The next step is to look for process patterns that appear to be performing wasteful activities through “variant analysis,” which allows us to compare process variations. In addition, let’s look for wastage by “rework analysis” that discovers repetitions that are occurring.
Unreasonable workloads and improper procedures can create challenges that cause work to stagnate. Therefore, identifying “muri” means identifying the bottleneck in the process.
Therefore, first of all, we check the areas with a large number of processes with “frequency analysis”. This is because the areas with a large number of processes are not only inefficient, but also tend to be stagnant due to a high load. In addition, the “performance (time) analysis” mainly looks at areas with long waiting times (the time between the previous process and the next process). The part with long waiting time is really a bottleneck. At the same time, “social network analysis” is used to understand the business transfer relationships among the participants in the process in question, and a deep dive is made into which participant in the process is most likely to cause a bottleneck.
The mura is that work procedures vary from person to person, and the lack of standardization makes variation in process quality an issue.
This is the first step in a “variant analysis” to see how many processing patterns there are. The more patterns you have, the more you have, the more various procedures are being performed. We also identify which activities are deviating from the standard by means of “conformance checking”, which is a comparative analysis against the standard process (to be process).
As improvement measures, since standardization is the goal, it is effective to prepare manuals and systematic measures that do not allow multiple procedures.
Because More omits or skips some of the required procedures, it is considered to be a deviation from the standard and a business process with issues of non-compliance.
Therefore, we need to conduct a comparative analysis of the standard process (to be process) and the current process (as is process) reproduced from the event log, or in other words, a “conformance checking”, to identify the deviation.
As for improvement measures, as mentioned earlier, the system should be structured so that the procedure cannot be omitted, and compliance training should be provided to raise the awareness of the person in charge.
Miss(Mistakes) are specifically wrong procedures, careless mistakes, and various other errors that result in rework.
Since it is difficult to determine whether a mistake has been made or not through process mining analysis, we can check whether a large number of repetitions have occurred in activities with a large number of processes or in activities with long processing times by conducting “frequency analysis,” “performance (time) analysis,”“rework analysis,” etc., and finally, we can conclude that The process is verified to see if any mistakes have occurred through interviews with the people in charge on site and by understanding the detailed process at the task level through task mining.
It is difficult to reduce the number of mistakes to zero, but with RPA automation, theoretically, the number of mistakes can be reduced to zero. In addition, if the user interface is difficult to use, or in other words, if the usability is low, mistakes are more likely to occur, so the system will need to be modified to improve usability.
Introduction to Process Mining (17)Outlook for the Future of Process Mining
プロセスマイニングの分析は、2000年代当初からはまずSAPなどのERPシステムが主な対象となりました。したがって具体的には、「購買プロセス（P2P：Procure to Pay)」や、「受注プロセス（O2C: Order to Cash)「」、および経理業務に含まれる「買掛金管理プロセス（Account Payable）」、「売掛金管理プロセス（Account Receivable）」が多く分析されてきました。
近年は分析対象が拡大しつつあります。例えば、販売・マーケティングのプロセス、すなわち集客からの見込客獲得・育成を行うマーケティング活動、および有望見込客に対して行う、受注に至るまでの営業活動を分析する企業が増えつつあります。この背景には、マーケティング活動は、マーケティングオートメーション（MA)と呼ばれる支援ツールが普及し、また営業活動についてはSFA(Sales Force Automation）と呼ばれる支援ツールが普及したことがあります。すなわち、マーケティング、セールスのデジタル化が進んだことによって、プロセスマイニング分析対象となりうるイベントログデータが生成されるようになったわけです。
市場リーダーのCelonisは既に社員数900人を抱え、大型の資金調達にも成功して「ユニコーン」としても認められる存在。そして、リーダーグループの一角を占めるSoftware AGは、「ARIS」のブランドで知られ、「ARIS Process Mining」の販売にも力を入れてきています。Uipath社は、買収したProcessGoldを「UiPath Process Mining」に名称を変え、UiPathが強みを持つRPAを含むトータルソリューションとして提案力を強化しています。
プロセスマイニング市場はまだまだ新しいため、市場全体を把握できるデータや資料がほとんど存在しません。そんな中、イタリアのITコンサルティング会社、「HSPI Management Consulting」が2018年から毎年発行している「Process Mining: A DATABASE OF APPLICATION」は、プロジェクト件数ベースでのプロセスマイニング活用状況を伝えてくれる貴重な調査資料です。
同社では、プロセスマイニングを単なる問題発見ツールとしてだけでなく、実際の業務プロセスが可視化できることで、関係するメンバーが「すごい（Sense of Excitement)」と思ってもらうこと、また、非効率性やボトルネックが一目瞭然となることから「すぐに改善しなければ（Sense of Urgency）」という気持ちを喚起できる仕掛け、すなわちプロセス改善を着手させ（Initiator)、促進する(Katalysator)ことのできる有益なアプローチとして活用しています。
AIG (USA) – Process Wind Tunnel（プロセス風洞）で確実な改善効果を
グローバルに展開する保険会社、AIGでは様々な業務プロセス改善に取り組んでいます。特に、米国AIGの”Data-Driven Process Optimization”と呼ばれる部署では、プロセスマイニング、シミュレーション、BIを組み合わせることで改善成果を積み重ねています。
Data-Driven Process Optimization部署では、プロセス改善の一連の手順を「プロセス風洞（Process Wind Tunnel）」と呼んでいます。自動車や航空機、建築物などの設計においては、風洞に模型を置いて風の流れ等を測定する「風洞実験」を行います。同様に、プロセスの改善にあたって、シミュレーションによる改善成果の予測を行った上で改善施策に展開するという手順を踏んでいるのです。
プロセスマイニング分析結果から、部品補修プロセスの総所要時間（ターンアラウンドタイム、またはスループットと呼ぶ）を長くしている大きなボトルネックは3カ所ありました。すなわち、「検査（Inspection)」、「提案と承認（Proposal and approval）」、「修繕と認証（Repair and certification)」です。
各工程では、大きなユニットの60－80％が処理待ちとなっており、このため6日～12日ほど想定よりも時間が掛かっていました。どれも解決すべきボトルネックではありましたが、どの工程から着手するか、優先順位をつけるために同社では「制約理論（Theory of Constraints）」を適用しました。制約理論は、プロセス改善を目的としてボトルネックの解消に取り組むためのアプローチです。そして、制約理論に基づき、「提案と承認（Proposal and approval）」からボトルネック解消のための施策を開始したのです。
Position and Role of COE – Center of Excellence for Continuous Process Improvement
This article explains the role and position of the Center of Excellence (COE), which can be regarded as a specially designated organization that promotes DX for the purpose of continuous process improvement and leads the realization of digital twin.
In Europe and the United States, an increasing number of companies have established a COE. Some Japanese companies have also established a COE, and although the role of the department is the same, it is often called “DX Promotion Department” or “BPR (Business Process Re-engineering) Department”.
What is DX and Digital Twin?
“Digital Transformation” (DX) is primarily focused on using technology to significantly transform your business model.
It doesn’t mean simply replacing analog operations with digital tools. It is about leveraging technology to transform the business and organizational structures and adapt to the socio-economic environment that is changing dramatically due to digital technology.
The digital twin, or more precisely, the Digital Twin of an Organization (DTO), reproduces actual business operations as a virtual model (i.e., digital twin) on a PC display, making it easier to discover various problems in business processes and also to identify problems in the daily The purpose of the COE is to monitor the occurrence of problems in the company’s operations in real time and attempt to take immediate corrective action.
The role of the COE
In recent years, as every aspect of the socio-economy and every aspect of business activity has become more digital, the old ways of working can no longer survive. We need to push forward with enterprise-wide DX and continuous process improvement through DTO.
The COE, a specially designated unit within the company, leads the way in promoting DX and DTO implementation.
The COE is positioned between the IT department and the business units such as procurement, manufacturing, logistics, sales, marketing, service, and accounting and finance, and coordinates a variety of activities to ensure that the two departments work well together.
The COE helps the incumbent get the most out of the latest technologies and tools so that they can deliver results. On the other hand, the COE supports the IT department by absorbing the needs of the business units and translating them into the required specifications for the development and improvement of the system.
Key Members of the COE
The COE for the promotion of DX, which is based on the use of technology, is data-driven, i.e., it discovers and corrects problems through the collection and analysis of various data related to the business. Therefore, a DX project is launched together with the business units, and the following experts belonging to the COE are appointed as project members. The following experts belonging to the COE are appointed as project members, and they will also participate in various DX projects of the operational divisions as necessary.
Knowledge of both business and IT, and plans and directs the deployment of business process improvement measures using IT. Proficient in BA, BPM, Lean, Six Sigma, PMC (Process Model Canvas), etc. as tools for implementing improvement measures.
Using process and task mining tools, we discover problems based on data analysis, perform root cause analysis, and present insights that lead to improvement measures.
The successful candidate will be responsible for data pre-processing tasks such as data extraction and data cleaning from the IT system in collaboration with the IT department engineers.
Various knowledge systems and tools must be used to understand the current situation, identify problems, analyze the root cause, and come up with improvement measures or design new business processes.
Typical examples are as follows;
BPM (Business Process Management)
PMC (Process Model Canvas)
As mentioned above, these tools are something business analysts should be equipped with.
In addition, IT tools and technologies for improvement include the following.
Artificial Intelligence (AI)
BPMS (Business Process Management System)
The members of the COE are expected to deepen their knowledge of these technologies and tools, and also to keep up with the latest developments in the fast-moving technologies.