DEBUG: PAGE=domain, TITLE=View all Vendors,ID=1466,TEMPLATE=vendors
toggle expanded view
VENDORID = -1
VENDOR =
VENDORparam =
Title = View all Vendors
Description =

Search across all vendors:

from:
until:

NICE Systems- Process Discovery & Mining Technology Evaluation

Vendor Analysis

by Bailey Kong

published on May 28, 2020

Access to this report is restricted to logged in clients with access. Login to get full access

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.

Login to get full access:

close