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NICE Systems- Process Discovery & Mining Technology Evaluation

Vendor Analysis

by Bailey Kong

published on May 28, 2020

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Report Overview:

This NelsonHall assessment analyzes NICE Systems' offerings and capabilities in Process Discovery & Mining Technology Evaluation

Who is this Report for:

NelsonHall’s Process Discovery & Mining Technology Evaluation, provides an assessment of NICE Systems’ process discovery & mining platform designed for:

  • Sourcing managers monitoring the capabilities of existing suppliers of Process Discovery & Mining platforms and identifying vendor suitability for RFPs
  • Process reengineering and RPA and intelligent automation center of excellence personnel evaluating process discovery & mining platform capability
  • Vendor marketing, sales, and business managers looking to benchmark their platforms against their peers
  • Financial analysts and investors covering intelligent automation and process discovery & mining platforms.

Scope of this Report:

The report provides a comprehensive and objective analysis of NICE Systems’ process discovery and mining capabilities, covering its Automation Finder and Desktop Analytics products’ functionality for:

  • Data collection
  • Process analysis
  • Process improvement
  • Administration.

This report also assesses NICE Systems’ product development strategy and strengths and challenges.

Key Findings & Highlights:

NICE Systems platform offers Automation Finder and Desktop Analytics products for process discovery and business intelligence. The two products combined offer:

  • Data collection
  • Process analysis
  • Process improvement.

NICE Systems offers a capable product for process discovery. Automation Finder’s ML technology to discover tasks/routines and its capability to analyze the interaction of tasks/routines to build process maps without any input from business analysts.

NICE uses unsupervised ML to split a day’s worth of work into individual routines (tasks, e.g., Updating an Order in SAP) and processes (set connected routines, e.g., Ship to Receive).

NICE plans to enhance its ML for process/routine discovery to incorporate user input.

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