Learn how Zeitwork’s capabilities compare to RPA Task Mining and Process Mining products and platforms.
With so much confusing jargon in the world of business process operations, analysis, automation, and development today, it can be challenging to understand how different products and platforms compare. Terms like process intelligence, process mining, process discovery, task mining, process analysis, and process modeling can all sound similar. What does it all mean and how does Zeitworks fit in?
Below you'll learn how Zeitworks compares to other similar products like RPA Task Mining and Process Mining, filling in big gaps in coverage across both process understanding and team behavior.
Leveraging desktop task-mining and AI, Zeitworks is a business process intelligence platform that empowers teams to transform their operations by revealing continuous data and insights into how work really gets done. Like a fitness tracker for team productivity, Zeitworks surfaces insights and analyses about people and processes in real-time, giving you the information you need to make better data-driven decisions.
Beyond showing you the steps of a given task, Zeitworks provides a wide breadth and depth of continuous information, including detailed metrics on all unique executions of a business process (Note that this capability is similar to traditional process mining, but for desktop processes).
Combining the team productivity metrics and behavior with detailed application usage statistics gives leaders the information they need to improve efficiency, lower costs, and maximize the human potential of their teams.
While RPA task-mining capabilities provide a helpful snapshot in time, they are not designed to dynamically and continuously provide operational improvements, insight into team behaviors, team time and costs of process executions, or details of customer-specific processes.
Some RPA platforms offer “task mining” features that facilitate the creation of RPA bots from limited user executions of repetitive business processes. Process executions are recorded by users on their desktop computers and uploaded to a cloud portal. There, analysis tools help identify automation opportunities from the paths and steps that have been repeated frequently. These tools and analyses help managers understand the characteristics and variances of the processes, assisting in determining the automation structure. RPA instructions of the chosen candidate process are generated, accelerating the development and deployment of the RPA bot.
Because the input data source for process mining technologies is the transactional logs of centralized enterprise systems, the process map output does not include details or insights into employee-specific productivity or behaviors.
Process mining platforms and tools measure processes executed within siloed enterprise systems (e.g., ERP systems like SAP). Importantly, the process executions are confined to these systems and do not span desktop application usage. Process mining algorithms consume trace log files from enterprise systems that result from the execution of business processes such as accounts payable/receivable. These log files are typically well structured and contain a time-stamp and a case ID representing the specific unit of work. Historical log files can be retrieved and analyzed by process mining algorithms which will produce process maps of individual or typical processes. This information can then be used by a business process analyst to assess the current process structure and execution paths, providing a baseline for understanding and improvement.