How Process Mining Facilitates Operational Efficiency?

How Process Mining Facilitates Operational Efficiency?

How Process Mining Facilitates Operational Efficiency?

Process Mining is a family of data science technics and process management to support operational processes based on event logs.

This article reviews the main advantages of using process mining to facilitate an operational efficiency project. process mining will typically be used as the first step of an operational efficiency project.

Business-Driven Analysis

Every business project must serve business first.

Business Context

A process mining analysis is placed in a clear business context. The event log is enriched with business-relevant information to take into account this business context:

  • monetary value
  • cost of operation
  • type of product or service
  • location or department
  • any information relevant to operational performance

Time

One of the critical characteristics of process discovery is to take into account the chronology of events. It is a significant difference with traditional Business Intelligence analysis, which take a flat view of data.

A characteristic of process mining is that it considers the time between two steps to establish chronology, compute statistics, deviation to the norm, correlation with other business dimensions.

Data-Driven Analysis

A strong data-driven culture increases the chances of making correct business decision.

Event Logs

The starting point of process mining is an event log. These are business information entered, processed, and generated by users inside enterprise systems. These are the only input of the first round of process mining.

Pre-Processing

As with any data-driven project, there is a need for pre-processing. Event logs always contain errors, mistakes, adjustments, and in some cases missing information. It is crucial to document all the manipulations of raw data. It will provide audibility, validation and will make it possible to revert to the original data to support the analysis.

No Bias

This approach eliminates a lot of the biases of traditional process mapping and analysis. Throughout an operational efficiency project, it is always possible and highly recommended to always go back to the source data.

Reality-Based Analysis

Decision making must rely on accurate representation of the reality.

No Theoretical Construct

Because process mining starts from data recorded in enterprise systems, it is only based on what happened, not on what could happen in theory. This shield operational efficiency projects to invest in unrealistic hypothesis.

Relative Importance

Process Mining is also shielded from spending too much time on border cases. While in traditional process analysis, 90% of the time can be allocated to complex scenarios that only occur 10% of the time, process mining will consider scenarios at their actual frequency and give them the correct weight in the analysis.

Simulation Capabilities

With a complete set of event logs and executable process models, process mining gives the ability to replay an event log against different business rules, process variation, timing, or resource constraints. The power of simulation makes it easier to predict with accuracy the effect of a proposed business change.

Select the Right Candidate

Investing in technology must be driven by a good estimate of the potential return.

Deliverable

The best business outcome of a process mining project is a list of candidates for operational efficiency improvements. These candidates could be automation, process adjustment, UX improvement, and many more.

Selection Criteria

Depending on the original business question asked at the beginning of the project, the selection criteria used to analyze the candidates will be different. A few common criteria to use to select the optimal operational efficiency candidate include:

  • frequency of occurrence
  • potential time saved
  • number of variants

Candidate Selection

Process mining offers the rigor and accuracy of a full data-driven methodology from raw data to improvement candidate evaluation. It dramatically increases the chance of predicting the outcome of a process change to the overall operational efficiency by:

  • concentrating on most common real occurrences,
  • preventing many biaises of traditional process mapping,
  • uses the power of simulation of real event logs to predict outcome,

Process mining can also support operational efficiency in realtime when integrated into the enterprise system.

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At System in Motion, we are committed to building long-term solutions and solid foundations for your Information System. We can help you optimize your Information System, generating value for your business. Contact us for any inquiry.

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