Table of Contents
- Market Categories and Deployment Types
- Key Criteria Comparison
- GigaOm Radar
- Vendor Insights
- Analyst’s Take
- About Saurabh Sharma
Process mining is a key enabler providing visibility and understanding for end-to-end processes before an automation initiative is launched (Figure 1). Using process mining, business and automation center of excellence (CoE) leaders can leverage quantitative data about a process as well as customers, specific products or services, sales channels, and other entities. This wealth of contextual information helps drive improved outcomes from automation initiatives. Key user personas for process mining software include end users (those who work and interact with existing analysis), process analysts, process managers, data scientists, administrators, auditors, and automation COE leaders. Common use cases for process mining solutions include process discovery, conformance checking, resource optimization, and cycle time optimization.
Figure 1. Process Mining Procedure
Organizations can derive good value by applying process mining to already digitized processes and for which unstructured work (such as reviews and manual approvals) is undertaken outside the IT systems. Using process mining, organizations can analyze their processes from the bottom up. Process mining uses the historical data in IT systems, so there’s no need to have a preexisting process model for analysis.
In simple terms, process mining algorithms determine how a process model is inferred based on raw event data. An algorithm is used to correlate event log data to identify trends and patterns, and aggregate metrics obtained from event logs recorded by IT systems. The models obtained from process mining can then be compared with existing models to check for conformity and discover relatively more efficient process models.
Task mining enables organizations to understand how tasks are performed by monitoring user interactions with workstations. Task mining technologies include optical character recognition (OCR), data mining, pattern recognition, and natural language processing (NLP). Task mining allows organizations to track KPIs of individual tasks that are often manual. Organizations can track task productivity and make data-driven process improvement decisions by analyzing user interaction data. Task mining focuses on analyzing employee interactions with one or multiple applications or information systems (like Microsoft Excel and Microsoft Word) while maintaining data security and privacy for sensitive information. Task mining helps the automation CoE and business leaders by enabling efficient discovery of high-potential opportunities for automation.
Process mining has a broader purview and aims to discover, analyze, and monitor end-to-end processes and sub-processes using event logs from information systems. Process mining is a sequence of events constituting individual steps. Process mining algorithms exploit data from event logs, which can be different types of databases and files from enterprise information systems and enterprise applications—for example, an enterprise resource planning (ERP) application. The data is visualized as a process flow that presents a given process as it’s actually executed.
Process mining solutions can be used as part of digital transformation initiatives to discover or create a transformation pipeline, and monitor progress to achieve key business objectives, such as faster time to market, improved return on investment (ROI), and a better customer experience (CX). With process mining, enterprises can extract hidden process insights to uncover new business opportunities (that is, cross-sell or upsell) and better ways of doing business. Table 1 provides a comparison of task mining and process mining.
Table 1: Task Mining versus Process Mining
|Solution Type||TASK MINING||PROCESS MINING|
|SCOPE||Steps, actions associated with a task||End-to-end processes|
|ENABLING TECHNOLOGIES||OCR, data mining, pattern recognition, and NLP||Data mining algorithms, process modeling|
|SOURCE||Keystrokes, mouse swipes and clicks, copy and pasting, and screen jumps||Event logs from information systems|
|LEVEL of DETAIL||Steps and actions||Tasks|
|Source: GigaOm 2022|
This GigaOm Radar report focuses on process mining and task mining solutions. Process and task mining solutions that are tied to a specific automation ecosystem or part of a broader automation suite ultimately aimed at driving robotic process automation (RPA) adoption are not included in this evaluation. In the corresponding GigaOm report “Key Criteria for Evaluating Process Mining and Task Mining Solutions,” we describe in more detail the key features and metrics that are used to evaluate vendors in this market.
How to Read this Report
This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding, consider reviewing the following reports:
Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.
GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.
Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.