July, 2020

How to Use New Tools to Optimize Your Intelligent Automation Program

By Enkel Doci & Xavier Hanson, Reveal Group

Intelligent Automation (IA) is an industry that is growing exponentially, with a vast number of organizations having already established Intelligent Automation programs. These are delivering enormous value back to the business by automating processes across a range of functions. According to Gartner; banks, insurance firms, telecoms, and utility organizations are currently the leading adopters with massive IT legacy investments and aggressive digital transformation initiatives. Despite the growth and drive behind IA, scaling across an enterprise is still one of the major hurdles’ organizations face. These challenges are commonly caused by a lack of oversight, risks associated with multiple sources of truth and inability to standardize quality and cost.

Lack of oversight on the lifecycle of automation initiatives, from idea generation all the way to benefits realization, is one of the factors that is preventing IA programs to scale. A typical automation journey starts with identifying the opportunities through crowdsourcing or an Operational Diagnostic performed on a specific business area. The next phases in the journey involve performing an assessment, delivering the automation, and then managing it in production in order to realize benefits.

The myriad applications organizations often put in play throughout the automation lifecycle is resulting in a lack of oversight and keeping them from growing their IA programs.

We have seen numerous organizations that have had to face great risks because of the multiple “sources of truth” for their key IA information. This is creating challenges when trying to capture and report on the benefits realized from automations that are in production because key data is either missing, or it sits on multiple applications.

For example, imagine the challenges involved with creating a weekly report that shows the collective benefits that are being realized from ‘in-production’ automations. This task would require collating data from several sources, including the IA platform, the process details captured during the intake process and the project management tool used to deliver the automation. These organizations are expending a lot of time and effort to develop in-house tools or customize existing applications to have one source of ‘truth’.

The ability to standardize the quality and cost of automation deliveries is another common inhibitor to scaling an IA program. As organizations mature in their IA journey into a federated operating model, they are faced with challenges in continuing to deliver automations at the same quality and best practices across the organization. Regardless of where the developer is located or which business unit they serve, it is important that automations continue to be delivered following best practices and comply with controls without reliance on humans to review such code. Having a solution in place that enables teams to standardize the quality and cost of automation deliveries will allow IA programs to scale and have a bigger impact across their organization, without impacting quality.

The good news is that two emerging categories of IA tools have emerged, designed to overcome these obstacles and increase impact across organizations by enabling them to operate at a higher level. Those categories are:

IA Lifecycle Automation Tools

These manage automations end-to-end from ideation all the way to production management, in one place. Such tools solve risks associated with lack of oversight and multiple sources of truth of key IA information. Criteria to consider when choosing a tool:

  • Ability to identify pipeline opportunities
  • Accurately estimate automation costs
  • Prioritize based on value by quantifying strategic indicators
  • Provide transparency and enable collaboration across the delivery team
  • Report on each phase of the lifecycle
  • Ease of integration and customization


Automated Review Tools

These check the code developed by all delivery teams across your organization against best practices while providing actionable feedback. Such tools solve challenges around standardizing quality and cost of automation deliveries. Criteria to consider when choosing a tool:

  • Percentage of code review automated
  • Adherence to best practices
  • Ability to reduce ongoing support
  • Improve quality
  • Features that drive scalability, e.g. self-service and easy to install

Combining the use of these two new categories of IA tools will have a tangible impact in optimizing current IA programs allowing their expansion by leveraging the benefits and insights accrued from these emerging technologies.

Using our own industry experience and lessons learnt at over 1000 process automations, we have developed Reveal RoboManager™  to be the pinnacle of IA lifecycle automation tools and Reveal RoboReview™ as the ultimate Automated Review Tool.

You can register for a free 14-day trial of both tools right now.

Also available on the Blue Prism Digital Exchange.


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