Gartner Research

Hype Cycle for Back-Office Analytic Applications, 2017

Published: 17 July 2017

ID: G00314730

Analyst(s): Alys Woodward

Summary

Back-office analytic applications are the first touchpoints for analytics and artificial intelligence for many business users. This Hype Cycle helps data and analytics leaders in analytics teams and business domains understand where they can leverage these powerful technologies for business benefit.

Table Of Contents

Analysis

  • What You Need to Know
  • The Hype Cycle
  • The Priority Matrix
  • Off the Hype Cycle
  • On the Rise
    • Artificial Intelligence in Postmodern ERP
    • Licensing and Entitlement Management
    • Al-Based Underwriting
    • AI for Procurement
    • Artificial Intelligence for IT Operations (AIOps) Platforms
    • Voice of the Employee
    • Digital Payment Advisor
    • Algorithmic Retailing
    • Workforce Engagement Management
    • Analytics Governance
    • Machine Learning in HCM
    • Mid/Back-Office WFO
    • Workspace Analytics
  • At the Peak
    • Social Media Analytics
    • Warehouse Resource Planning and Scheduling
    • Retail Activity Optimization
    • Social Media Risk Management
    • Supply Chain Execution Predictive Analytics
    • Mobile App Analytics
    • Mobile Marketing Analytics
    • User and Entity Behavior Analytics
    • IMC-Enabled Packaged ERP and F/SCPM Applications
    • Workforce Planning and Modeling
  • Sliding Into the Trough
    • Application Portfolio Management
    • Fraud Analytics
    • Consumption Analytics
    • Supply Planning
    • Workforce Analytics
    • Corporate Social Responsibility
    • Dynamic Discounting
    • Device Monitoring Analytics
  • Climbing the Slope
    • Cost-to-Serve Analysis
    • Application Performance Monitoring Suites
    • Real-Time SPC Applications
    • Talent Management Suites
    • Algorithmic Merchandise Optimization
    • Contract Life Cycle Management
    • Diagnostic Analytics
  • Appendixes
    • Hype Cycle Phases, Benefit Ratings and Maturity Levels

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