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Report information:

Intelligent Automation Technology Platform Evaluation

Market Analysis

by Mike Smart

published on Aug 31, 2021

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Report Overview:

 

NelsonHall’s market analysis of the intelligent automation market consists of 57 pages.

Who is this Report for:

NelsonHall’s Intelligent Automation Platform Evaluation report is a comprehensive market assessment report designed for:

  • Sourcing managers investigating sourcing developments within the intelligent automation platform market 
  • Vendor marketing, sales and business managers developing strategies to target opportunities for Intelligent Automation platforms
  • Financial analysts and investors specializing in RPA and AI.

Scope of this Report:

The report analyzes the worldwide market for intelligent automation platforms and addresses the following questions:

  • What is the market size and projected growth for the global intelligent automation services market by geography?
  • What is the profile of activity in the global intelligent automation platform market by industry sector?
  • What are the top drivers for adoption of intelligent automation platforms?
  • What are the benefits currently achieved by users of intelligent automation platforms?
  • What factors are inhibiting user adoption of intelligent automation platforms?
  • What pricing mechanisms are typically used for intelligent automation platforms and how is this changing?
  • Who are the leading intelligent automation platform vendors globally and by geography?
  • What combination of features typically provided by the IA platforms and what new features are being added?
  • What are the challenges and success factors within intelligent automation platform market?

Key Findings & Highlights:

NelsonHall’s market analysis of the intelligent automation market consists of 57 pages.

Drivers currently influencing buyers use of IA can include:

  • Cost reduction – the time to achieve a positive ROI is decreasing as the maturity of automation increases. In some more extreme use cases, organizations are currently targeting a ROI of 2-3 months, down from ~6 months previously
  • Improved customer experience – with automations delivered in the front office, automation can be leveraged to support more positive outcomes for customer journeys. Automation projects are becoming increasingly focused on measuring outcomes via CX metrics such as NPS or CSAT scores. Enhanced customer experience can be achieved with automation through the reduction of cycle times, reduction of errors, and automation of repetitive tasks to allow organizations to focus on customer/agent interactions
  • Adherence to process standards – automations can adhere to a standardized process much closer than a human worker. The advantage of this adherence can be increased regulatory compliance, improved transparency, and reduced error rates. Automations can also be audited through one portal, whereas manual processes may require data to be extracted from numerous applications
  • Ability to scale – in particular with cloud-based bots, bots can be scaled up and down at a much faster rate in comparison to human employees
  • Enhanced change management – similar to the increased ability to scale, if an organization wishes to change a process (for example to run A/B testing), rather that having to send the changed process to a large number of employees, the organization is only required to update the process in the automation once
  • Improved employee experience – with automations in place, employees can be free to focus on more engaging tasks and move away from legacy interfaces.

While inhibitors for buyers in deploying IA include:

  • Difficulty in obtaining the buy in across the organization – while buy-in from the C-suite no longer tends to be an issue for organizations, there are often issues in assigning responsibilities for automations between business operations and IT. Intelligent automation platform vendors have worked to expand automation hub capabilities to support business and IT users to work more effectively together
  • Lack of skilled resources to build and manage bots
  • Understanding which processes to automate
  • Reducing the development costs and time to develop automations
  • The ability to build automations which can be easily manageable so that when a process requires change, the organization can implement those changes quickly with minimal rework
  • Difficulty in selecting the best of breed technologies, such as the technologies which are easier to scale beyond PoCs, or the best technologies to integrate ML and AI
  • The application of intelligent automation in customer interaction use cases is still in the embryonic stages of development
  • The ability to effectively build and manage automations across a number of intelligent automation platforms

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