Process re-engineering, process improvement, productivity enhancement were techniques that have been in existence for over 2 decades. The principles behind these techniques were sound, but cumbersome implementation resulted in low levels of adoption.
Whether it is automation, process improvement or performance improvement, one needs to know the AS-IS ground reality. How are people currently performing the process? Where do they face challenges? These and many other questions require granular observation of human activity. Digital data of human actions can then be used to analyze patterns and suggest improvement. The only known technology so far was the manual time and motion study. In this process a human would shadow a worker and note down all the unit level actions in a diary. Imagine the magnitude of difficulty, if one were to shadow tens and thousands of users. One would need an army to undertake such an endeavor.
Technologies of task mining come to our rescue. Task mining technologies observe human actions without straying into their zone of privacy. Task mining technology is also mindful of secure data and ensures that they are screened out at the source.
Task mining can provide raw data for further visualisation of hypothesis. An hypothesis can unravel insights from the data stream and one can uncover bottlenecks that were hidden for decades.
Task mining is no longer a nice to have in the arsenal of the CTOs and CIOs. It has become a mandatory technology for those who want to cut down costs, boost productivity without compromising on the output or revenue.