Best Practices for Knowledge Workers describes Adaptive Case Management in the current era of digitization, Internet of Things (IoT), artificial intelligence (AI), intelligent BPMS and BPM Everywhere. You will learn how support of adaptive, data-driven processes empowers knowledge workers to know in real-time what is happening at the edge points, and to take actions through the combination of rule-driven guidance and their own know-how. It is not a traditionally-automated system but intelligent automation, where technology doesn’t merely replace human decision-making but extends the reach of the knowledge worker; making IoT data actionable.
As Sandy Kemsley points out in her foreword:
As adaptive case management (ACM) systems mature, we are moving beyond simple systems that allow knowledge workers to define ad hoc processes, to creating more intelligent systems that support and guide them. Knowledge workers still need to dynamically add information, define activities and collaborate with others in order to get their work done, but those are now just the table stakes in a world of big data and intelligent agents. To drive innovation and maintain operational efficiencies, we need to augment case work – typically seen as relying primarily on human intelligence – with machine intelligence. In other words, we need intelligent ACM.
Highly predictable work is easy to support using traditional programming techniques, while unpredictable work cannot be accurately scripted in advance, and thus requires the involvement of the knowledge workers themselves. The core element of Adaptive Case Management (ACM) is the support for real-time decision-making by knowledge workers.
In award-winning case studies covering industries as a diverse as law enforcement, transportation, insurance, banking, state services, and healthcare, you will find instructive examples for how to transform your own organization.
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