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March 20, 2016


Robotic Process Automation + Analytics

by Ravi Kalakota

“Looking to the future, the next big step will be for the very concept of the “device” to fade away. Over time, the computer itself—whatever its form factor—will be an intelligent assistant helping you through your day. We will move from mobile first to an AI first world.” 

— Sundar Pichai, CEO Google


  • A global oil and gas company has trained software robots to help provide a prompt and more efficient way of answering invoicing queries from its suppliers.
  • A large US-based media services organization taught software robots how to support first line agents in order to raise the bar for customer service.

Software agents or Robotic process automation (RPA) is becoming a mainstream topic at leading corporations. I have seen a massive uptick in corporate strategy work in this area as C-Suite execs look at new ways to do more with less.

Software robots ∼ Apple Siri, Microsoft Cortana, IBM Watson, Google DeepMind, drones and driverless cars ∼ are now mainstream. What most people are not aware of is the rapidly advancing area of enterprise robots to create a “virtual FTE  workforce” and transform business processes by enabling automation of manual, rules based, back office administrative processes.

This emerging process re-engineering area is called Robotic process automation (RPA).

Machine Learning (ML) and graph processing are becoming foundations for the next wave of advanced analytics use cases. Speech recognition, image processing, language translation have gone from a demo tech to everyday use in part because of machine learning. Machine learning models, e.g., in driverless cars,  teaches itself how to discover relevant things like a stop sign with snow partially obscuring the sign.

The market opportunity of artificial intelligence has been expanding rapidly, with analyst firm IDC predicting that the worldwide content analytics, discovery and cognitive systems software market will grow from US$4.5 billion in 2014 to US$9.2 billion in 2019, with others citing these systems as catalyst to have a US$5 trillion – US$7 trillion potential economic impact by 2025.

RPA – What?

According to Blue Prism, “Robotic automation refers to a style of automation where a machine, or computer, mimics a human’s action in completing rules based tasks.”

RPA is essentially the novel application of analytics, machine learning and rules based software to capture and interpret existing data input streams for processing a transaction, manipulating data, triggering responses and communicating with other enterprise applications (ERP, HRMS, SCM, SFA, CRM etc.).

RPA is not a question of “if” anymore but a question of “when.”  This is truly the next frontier of business process automation, enterprise cognitive computing, predictive analytics and machine learning. To make a prediction, you need an equation and parameters that might be involved.

Industrial robots are remaking factory and warehouse automation by creating higher production rates and improved quality.  RPA, simple robots and complex learning robots, are revolutionizing the way we think about and administer business processes (e.g. customer service), workflow processes (e.g., order to cash), IT support processes (e.g., auditing and monitoring), and back-office work (e.g., data entry).

I strongly believe that as cognitive computing slowly but surely takes off, RPA is going to impact process outsourcers (e.g., call center agents) and labor intensive white collar jobs (e.g., compliance monitoring) in a big way over the next decade. Any company that uses labor on a large scale for general knowledge process work, where workers are performing high-volume, highly transactional process functions, will save money and time with robotic process automation software.

RPA picture

Business Impact of RPA – Where?

RPA is already being applied to a wide range of industries to improve speed, quality and consistency of service delivery. Virtual FTE robots can:

  • Learn from natural language interactions in order to solve customer problems and respond easily to a wide range of queries
  • Automate data and rules intensive activities like HR, procurement, invoicing, billing. Now it is possible to create complex cross-enterprise apps (xapps or composite apps) like order-to-cash automation.
  • Orchestrate other application software apps through the existing APIs or user interface

Workflow and Process automation

Clerical labor is replaced by software.

Best projects for robot automation are bulk repetitive rules based procedures. Process automation can expedite back-office tasks in finance, procurement, supply chain management, accounting, customer service and human resources, including data entry, purchase order issuing, creation of online access credentials, or business processes that require access to multiple existing systems.

Technologies like BPM software – a technology that mimics the steps of a rules-based, non-subjective process without compromising the existing IT architecture – are able to consistently carry out prescribed functions and easily scale up or down to meet demand.

Automated agents and assistant

Large call centers are going to get restructured.

As in voice recognition software, IVR or automated online assistants, developments in how machines process natural language, retrieve information and search mean that RPA can provide answers to self-service customers without human intervention. I can see demand reducing systematically for armies of low-cost labor offshore that do simple tasks like status checking…. query multiple systems and respond;  data entry…input into multiple systems and error check.

Monitoring support and management

‘Human only’ processes will shift as machine learning and data-driven decision making evolve further.

Activity, fraud and risk monitoring is going thru some changes. Automated processes in the remote management of IT logs, audit trails, security, and other risk related areas can consistently monitored, flagged and exception handled faster.   In IT function specifically, RPA can improve service desk operations and the monitoring of network devices.

KPMG, for instance, is leveraging IBM Watson in improving Audit, Tax processes. One current initiative is focused on employing supervised cognitive capabilities to analyze much larger volumes of structured and unstructured data related to a company’s financial information, as auditors “teach” the technology how to fine-tune assessments over time. This enables audit teams to have faster access to increasingly precise measurements that help them analyze anomalies and assess whether additional steps are necessary.

This example highlights how cognitive technology is further advancing improvements to sampling processes, in which auditors review subsets of data to analyze thousands or millions of actions to draw conclusions. Cognitive technology helps allow for the possibility of a larger percentage of the data to be analyzed, providing KPMG professionals the potential to obtain enhanced insights into a client’s financial and business operations. At the same time, cognitive-enabled processes allow auditors to focus on higher value activities, including offering additional insights around risks and other related findings.

Many of professional services rely heavily on judgment-driven processes. Adding RPA and cognitive technology’s massive data analysis and innovative learning capabilities to these activities has the potential to advance traditional views on how talent, time, capital and other resources are deployed by professional services organizations.


The robots are coming! Enhanced scalability, greater accuracy, digital integration with APIs, improved compliance and reduced cycle times to deploy – as these improve… RPA adoption will take off.

Analytics enabled Robotic process automation (RPA) will drive improvements in accuracy and cycle time and increased productivity in transaction processing (e.g., healthcare claims processing) while it elevates the nature of work by removing people from dull, repetitive tasks.

RPA is in early days.  So, sometimes the hype can get ahead of the reality.  But this is an area where I am going to be digging deeper in subsequent blog posts.

Additional Sources

  1. Predictive Analytics 101 (quick overview)
  2. Business Analytics 101 (quick overview)
  3. Executing Analytics 101 (quick overview)
  4. Machine Learning 101 (quick overview from Google)
  5. RPA vendors include:  Blue Prism; AutomationAnywhere, Deskover, Jacada, UIPath, IBM
  6. Institute for Robotic Process Automation –
  7. O2 implements RPA
  8. Amazon Robotics ~ Robots in the warehouse…. interesting  vision statement… “At Amazon Robotics, we are continually reimagining what now looks like. We see the big picture, imagine a better one, and make the connections that turn complex problems into elegantly simple solutions. Our drive toward a smarter, faster, more consistent customer experience fuels Amazon – and the industry – forward, now. With a fearless resolve to achieve the improbable with real solutions, we meet tomorrow’s challenges today. We Reimagine Now.”
  9. RPA is an Analytics use case.  See more on Use Cases in Analytics here.
  10. IBM Watson



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