The difference between Process Mapping and Process Mining

The critical differentiator between traditional process mapping and process discovery based on new technology is the distinction between subjectivity and objectivity in visualizing processes.

In this article, we will make the case against process mapping in favor of automated process discovery through Process Mining, showing how it will allow organizations to quickly map their processes, complete and objective with all deviations.

Process Mapping

Process mapping is the traditional way of capturing an ‘as-is-process’, using workshops, interviews and document analysis. It’s primarily used to draw an idealized process model of how processes should be performed.
Pro’s:

  • Organizational involvement, broad organizational support;

Con’s:

  • Focus on major deviations, maximum of +/- 10 cases;
  • Subjective, dependent on participants;
  • Time and resource intensive;
  • Requires an ‘open’ culture.

Process Mining

Process Mining uses automation to extract process models from organizational databases. It is exclusively concerned with verifiable data logs, providing an accurate picture of how processes factually perform.
Pro’s:

  • Complete, all cases and deviations are known;
  • Objective, only facts matter;
  • Quick, once set up;
  • Process deviations are weighted without being unfairly amplified or ignored.

Con’s:

  • Reliance on data compatibility, specific format.

The Case for Process Mining — Why Automated Discovery is Best

The case for Process Mining is strong, particularly when midsize and enterprise level companies are looking to initiate Business Process Improvements (BPI). The most important arguments are:

1.Processes overarch departments and functional area’s

One of the most significant challenges in manual process mapping is effectively extracting information from people involved in a process and piecing together the “remembered activities” to create an overarching process map. This will require several iterations. There inevitably will be knowledge gaps and there will human interpretation. You simply don’t know what you don’t know.
Process mining captures all the nuances of a process, including statistical information, process exceptions, unusual transactions, deviations, bottlenecks, and variants. Process discovery bridges the gaps between the individual process steps across multiple IT systems. Automated process discovery delivers a detailed process map rich with data and flexible for interactive analysis, including ‘unknown’ facts.

2.Eliminate socio-cultural behavior

Without devious intentions, people will deliver a subjective view of reality. Humans gather information, process this information with our current mind-set and make a decision.
Process Mining uses data logs, eliminating the presence of subjectivity from process analysis.
Additionally, what manual process mapping may express as statistical noise, process discovery can appropriately highlight as inefficiencies in business processes.

3.Accuracy and speed

Have you ever seen a whiteboard overloaded with post-its — diamonds, arrows, colored mini-posted-its upon larger notes? This iterative approach and inefficient in terms of required human hours needed for interviews, facilitated brown paper workshops, analysis of existing documentation and direct work observation.
Process Mining software delivers a flexible, in-depth process analysis much faster.

4.Reusability of the analysis and measurements

Last but not least, a massive benefit of automated Process Mining over manual process mapping is reusability. Once systems are connected and process mining software established, the process can be endlessly reanalyzed. Process Mining software is able to capture effects of process improvements instantly.

Talk to one of our experts to understand how we can support your organization in achieving Business Process Improvement success through Process Mining.

Eric Hellemons
Call: +31 6 18 84 61 98
E-mail: eric.hellemons@squadra.nl

Enno Kroesen
Call: +31 6 38 78 79 57
E-mail: enno.kroesen@squadra.nl

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