なお、マトリックスには記載しておりますが、プロセスマイニングの対象とはならない、ビジネスモデル層については、ビジネスモデルキャンバス（BMG：Business Model Canvas）、プロセスモデルキャンバス（PMG：Process Model Canvas）といったツールが活用できます。
Reference Matrix for Process Mining Tool Selection
In recent years, process mining has been further recognized and understood as a useful solution for promoting and establishing DX. In addition, as shown by the recent acquisition of myInvenio by IBM and Signavio by SAP, there is no doubt that process mining will become increasingly important as an indispensable component of corporate IT system development and operation as it is incorporated into the solutions of major IT companies.
Needless to say, the adoption of process mining tools is essential for companies to improve their business processes and to renovate and develop their systems using process mining, and the selection of the best suited tool for your company is a major key to success.
In this article, I will explain a matrix that will help you determine what functions of process mining tools are particularly necessary for your company.
●Horizontal axis of the matrix: Time
From the perspective of time, there are three dimensions which are completed processes in the past, processes in progress at the moment, and future processes to be executed in the future.
In general, data analysis is done on completed historical data. The same is true for process mining analysis. By analyzing completed event log data with process mining tools, we can automatically model current processes and analyze them from various perspectives (basic analysis).
For example, the following basic analysis is available.
Performance analysis (analysis from the perspective of time required and cost)
Conformance checking (comparative analysis of current process and ideal process)
There are some process mining tools which can do continuous monitoring and if problems such as deviations are detected, alerts are sent to the relevant parties by importing ongoing event log data to the process mining tool at a frequency close to real time.
For future processes that will take place in the future, the following functions will be supported.
Simulation (What-IF Analysis)
Simulate how much improvement (throughput reduction and cost reduction, etc.) can be obtained if the current process is improved in some way.
Model the flow of the ideal process to be implemented in BPMN format.
predict how in-process projects will be processed in the future and how much time will be required by using AI.
Based on the results of the above predictions, the tool proposes the best measures to prevent problems from occurring and prolonging the processing time.
Automated Process Improvement (AutoPI)
A process mining tool automatically executes measures for process improvement under certain conditions to achieve a quick remedy.
●Vertical axis of the matrix: Business layer
The business layer is a factorization into more detailed components from a process perspective. Administratively, the higher the layer, the more “strategic” it is, and the lower the layer, the more “tactical” it is, and the more “operational” (day-to-day on-site management) it needs to be.
At the top is the business model. From there, the granularity becomes finer, including the value chain that grasps the processes of the entire company from end-to-end, and the individual processes that make up the value chain.
Any business process can be broken down into a number of sub-processes. One more sub-process is composed of finer-grained tasks, and those tasks are composed of multiple activities.
For example, if we consider a sub-process called “invoice processing” in the accounting department, this includes activities such as “receiving invoices,” “checking the contents of invoices,” “registering invoices in the accounting system,” and “processing payments for registered invoices.
Among these activities, in the case of “receive invoice,” each task step is executed one by one, such as “open the email with the PDF invoice attached” and “download the attached PDF invoice.
In addition, these task steps are executed in the smallest units of PC operations, such as clicking on the mail software icon, clicking on open mail, and clicking on the attachment. These are called “atomic activities” because they cannot be decomposed any further.
Process mining basically analyzes the activity layer (or task step layer, as the case may be) from the process layer. transactional data recorded in IT systems are often at the activity level, which is relatively coarse-grained. In many cases, transaction data recorded in IT systems is at a relatively coarse activity level.
Therefore, task mining is used to analyze task steps and atomic activities with finer granularity. Task mining is still in its infancy, and it is still at the stage of trial and error for deeper analysis besides BI-like aggregation. However, by using it together with process mining, it can contribute to process automation, especially with RPA.
Now, in light of your company’s business process issues, which should be the target of analysis: past, present, or future? Also, at what granularity should the process be analyzed as a business layer?
With the person in charge of the tool vendor, let’s look at this matrix together to understand the extent to which these functions can be implemented while recognizing where the company is aware of the issues.
For the business model layer, which is not subject to process mining, tools such as Business Model Canvas (BMG) and Process Model Canvas (PMG) can be used.
Will Process Mining tool and BI tool be amalgamated?
The answer is yes. The integration has already begun.
In terms of specific developments, a process mining tool called “PAFnow” is available as an add-on for Power BI. Similarly, “MEHRWERK ProcessMining” is offered as an add-on for Qlik.
On the other hand, process mining tools have also been enriching their “dashboard features” in addition to the standard features of process mining, such as “process discovery” which automatically creates a process model from the event log, but this dashboard feature is now close to the level of functionality provided by BI tools.
By the way, both process mining tools and BI tools are the same in that they take in various data related to corporate and organizational management, calculate numbers from various angles, and present the results visually in tables and graphs.
The decisive difference between a process mining tool and a BI tool is in how the calculation results are interpreted and utilized.
Concretely, we can explain as follows.
Calculation results presented by process mining tools
Process mining tools mainly look to performance of activities (processes) that create value = causals. In other words, process mining tools mainly cover Key Performance Indicators (KPIs).
For example, in the case of an insurance company’s claims processing process (from insurance claim to payment), process mining tools can analyze the number of cases for each activity in the process, the total time required for processing (throughput), processing cost, and the number of people in charge, and so on. In addition, the process discovery function can automatically draw a flowchart of business procedures to identify problems such as bottlenecks and inefficient repetitive tasks.
In this way, by analyzing activities that create value, i.e., causal data analysis, it is possible to link them to business process improvement measures to further increase value or reduce costs.
Calculation results presented by BI tools
BI tools mainly look at The size of value (sales, profit, etc.) generated = outcomes. In other words, BI tools cover KGI (Key Goal Indicator).
BI tool basically calculates sales, profit, market share, etc. as a result of corporate activities, and enables multifaceted analysis in various dimensions such as by division, area, and product.
BI tools can make judgments about which business units or areas are producing superior (or inferior) results, but they cannot infer the causes of why results are superior (or inferior). This is because it does not analyze causal data in the first place.
As explained above, to summarize the differences between them, BI tools are like a report book at the end of the term, and they are used to make final evaluations and to set new goals for theKGI in the next term. On the other hand, process mining tools are used to analyze performance in detail during the period and consider how to improve it in order to achieve the goals of KGI.
There is one more difference in the way data is analyzed that has recently emerged.
While BI tools only calculate a snapshot figure of historical data for the entire analysis period, process mining tools are now adding the ability to perform real-time monitoring that sequentially analyzes the data of the cases in the processing.
In order to continuously look back on the status of corporate and organizational operations, and to improve what needs to be improved, ensuring the achievement of goals, it is essential to combine KGI evaluation using BI tools and KPI evaluation using process mining tools.
Currently, more and more companies are using a combination of both tools, but as mentioned at the beginning of this article, the boundary between process mining tools and BI tools is blurring, and in the future, they will be provided as a combined tool.
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。
Organizing the functionality of a process mining tool based on the purpose of analysis
Process mining tools that perform analysis based on event logs are basically very versatile and are evolving with new features being added every day. It’s not easy to get an overview of the features of a process mining tool when you’ve just been given a one-size-fits-all explanation or demo.
So, in this article, let’s start with what kind of analysis you want to do, that is, the “purpose of the analysis”, and organize what kind of function it has.
Please note that we have deliberately left out task mining because it is a technologically immature feature and we are focusing on the main features.
Now, there are many ways to analyze using process mining tools, but I would like to divide them into the following four main categories.
1 Process Focus
This is the basic analytical perspective of process mining. The analysis focuses on the flow of the target process.
2 Organizational Focus
The three required data items for process mining analysis are process ID, activity, and time stamp. In addition to these three items, “resource (user in charge)” and “role (department and position)” are typically analyzed as semi-requisite items.
In addition to the process itself, the Organizational Focus analyzes the process from the perspective of the people in charge of executing the process and their departments and positions.
This approach is sometimes referred to as “organizational mining”.
3 Simulation Focus
Literally, it’s an approach to simulating by setting up some parameters.
4 Operational Focus
Process mining analysis is essentially an approach that targets previously completed data, but analyzes currently running and uncompleted processes in real time.
Let’s take a look at the analysis objectives and corresponding functions for each cut.
1 Process Focus
1.1 I want to know what the variations of the process are.
⇒ Variant Analysis
1.2 I’d like to see the number of cases flowing through the process.
⇒ Frequency analysis function
1.3 I want to see the time required for a process (throughput, lead time between activities, etc.)
⇒ Performance analysis function
1.4 I want to Discover deviant processes compared to standard processes (to be processes)
⇒ Conformity inspection function
1.5 I want to compare multiple process variations.
⇒ Comparative analysis function
1.6 I would like to delve deeper into the causes of the problem regarding inefficiencies and bottlenecks in the process.
⇒ Root cause analysis function
1.7 I want to understand the deviation from the KPI target values (throughput, processing time, etc.).
⇒ KPI setting function
1.8 I want to understand the business rules in the process branch (gateway).
⇒ Business Rule Mining Function
1.9 I want to create a BPMN-compliant model.
⇒ BPMN model conversion function
⇒ BPMN model creation and editing functions
2 Organizational Focus
2.1 I want to know which person is in charge of which activity.
⇒ Activity Map Function
2.2 I want to calculate the number of processes and processing time for each person in charge.
⇒ Create customized dashboards
2.3 I would like to understand how those in charge of the process relate to each other in the target process.
⇒ Social network function
3. Simulation Focus
3.1 We want to verify the effects of changing a part of the process or implementing RPA.
⇒ Simulation function
4 Operational Focus
4.1 I want to estimate how much more time it will take to complete an incomplete process.
⇒ Predictive analysis function
4.2 I’d like to estimate the steps to be taken to shorten the throughput of an incomplete process.
⇒ Recommended process functions
4.3 I want to send an alert to a person in charge when a deviation process occurs.
⇒ Alert function
Above, we have organized the features of the process mining tool according to the purpose of the analysis. Please note that the function names of each tool are different.
When selecting a tool, understand how you want to analyze the process to be analyzed from the perspective of your company, and then confirm whether the candidate tool has any functions.
市場リーダーのCelonisは既に社員数800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。また、先ごろ買収したProcessGoldを「UiPath Process Mining」と名称を変え、UiPathが強みを持つRPAを含んだ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。
Major Contender、すなわちリーダーグループに闘いを挑んでいる主要な競争ベンダーはまさに群雄割拠という状況。なお、私が把握している限りですが、日本においてなんらか連絡先があるのは、ABBYY Timeline、LANA Lab、myInvenioの３つだけです。
“Process mining” was born in the late 1990s and last year turned 20 years old. In 2019, a new concept called “task mining” appeared.
In this article, I would like to organize and sort out the differences in purpose and positioning, including “SIEM: Security Information and Event Management”, which is a similar solution to process mining and task mining.
First, the difference between process
mining and task mining. In simple terms, the data to be analyzed is different.
Process mining analyzes the event logs
(transaction data) recorded and accumulated in business systems such as ERP,
CRM, and SFA. The recorded data is based on activities such as “purchase
request” and “purchase approval” when the “send” or
“update” button of the system is pressed, and the granularity of only
the “milestone” of the business Is a rough thing.
On the other hand, task mining analyzes the
detailed operations on PCs that employees operate individually, specifically,
the “PC operation log” that records application launches, file opens, mouse
clicks, copy and paste, etc. Eligible. Compared to the event log extracted from
the business system, it is “atomic” detailed data that cannot be
further decomposed and can be analyzed at the task level. Since these PC
operation logs are not recorded anywhere, install software called sensors or
agents on the PC to be analyzed and actively capture and collect PC operations
as data. A mechanism to accumulate on the server is required.
“SIEM” is a similar solution
adjacent to process mining and task mining. It analyzes security logs, network
devices, and various logs remaining on servers to find security-related issues
such as cyber attacks and data leaks, and manages IT devices as assets. And so
Now, since these solutions basically
analyze data generated in the “workplace”, they can be broadly put into the
framework of “Workplace Analytics”.
Now let’s position process mining, task
mining, SIEM, and their key solutions within the framework of workplace
analytics. (See the figure below)
Look around the double arrow at the bottom
of the figure. Process mining is “process improvement oriented”,
while “SIEM” is “risk aversion and management oriented”.
Task mining is located in the middle. This is because task mining can be used
for attendance management because it allows you to understand the entire daily
work of employees. (In process mining, since only the data of operations performed
on the business system is the analysis target, it is not possible to grasp the
entire business of the day.)
In addition, process mining and task mining
can be surrounded by the framework of “process intelligence”, but SIEM is not
included because “process” is not analyzed.
And process mining is “DX-driven” because it is effective for process reform of the entire company and approach from the viewpoint of digital transformation (DX), while task mining is ultimately an automation at the task level Because it is often aimed at a certain RPA, it can be said that it is “RPA-driven”.
Let’s look at the key solutions in each
category. At this time (February 2020), two key players in the Japanese process
mining market are Celonois and myInvenio. Both tools are enterprise solutions
with rich functions and excellent operability, and the number of enterprises,
especially large enterprises, is increasing. And recently, both tools have
added a “task mining function”. By being able to create not only
event log data from business systems, but also flow charts (process models)
from PC operation logs, it can be said that it meets the analysis needs
necessary for RPA to aim for task-level automation Will be.
In the task mining category, heartcore,
myInvenio’s sole agent in Japan, provides Heartcore Task Mining. In addition,
MeeCap, which has a track record of introduction in the banking industry, has
begun to expand to a process mining function that analyzes event logs from ERP
and other sources.
In the SIEM category, Splunk and Skysea View are known, but Splunk has added a process flowchart function. However, it seems that analysis cannot be performed until the event log is imported.