Third Step

Prepare your mindset
for automation

Overview of RPA

A natural place to begin digital transformation using intelligent automation is with robotic process automation (RPA). RPA tools automate steps of a process by mimicking the manual steps a human worker would take when using existing application software.

It’s been highly successful in back office clerk activities in financial services and insurance, call center and typical swivel chair activities. Examples include document and data download, transaction processing; high-volume data entry, repeatable, computer-centric processes; as well as double and concurrent data entry into old and new systems during migrations.

RPA is quickly maturing and best used for repetitive and rule-based tasks. It’s a significantly more sophisticated evolution from macros and scripts, and is often deployed tactically as a standalone, ‘duct tape’ repair. Or, else it’s deployed more strategically, with BPM or case management tools that manage entire processes.

By now it should be clear where RPAs are a traditionally good and bad fit, and where they are helped by AI and IC. They tend to work well with processes that are rule-based, simple to moderately complex, stable, mature and documented. If AI makes them smarter, they can do better with less structure and more complexity.

They also historically required digital processes with structured data, and many processes otherwise suitable for automation do not have neatly structured data inputs, making them unfit for RPA solutions. But if you attach IC to the front end, you can address processes that include paper and dumb images.

Defining Next-Gen Process Automation

Next Gen workflow emerged from past and current generation process management. It’s useful to take a quick tour to understand what’s old and what’s new with it. Workflow has evolved from a few categories:

Simple Work Routing
Basic request-submission-review-and-approval routing and tracking. Often addressed through lightweight ECM solutions and document collaboration tools.
Content-Centric Workflow
Designed for more structured and repeatable processes that involve human interaction and document routing. Often addressed by the workflow capabilities of an ECM solution. Broader BPM-centric solutions also play in this space.
Business Process Management
Designed for structured processes that may involve both human-to-system and system-to-system process orchestration. BPM differs from workflow in providing more advanced data aggregation, transformation, integration from multiple sources and business activity management (BAM) including process monitoring, analytics and simulation.

Case Management
These solutions are designed for processes that are highly variable, dynamic and ambiguous. They rely on knowledge workers to determine how to structure the work throughout a complex “case” based on decisions needed, other teams to involve, information needed, etc. Most of the leading BPM vendors offer case management solutions or at least capabilities, as do most of the leading ECM vendors who provide content-centric workflow.

Digital Automation Platforms

A Digital Automation Platform (DAP) is a supplier and analyst-driven term for the newest process automation platforms. They include the capabilities of the preceding types, are low code and light weight and can be configured by citizen developers. DAPs improve and include characteristics of traditional workflow, BPM and case management. Benefits include:

Maximize capability for building apps.
Maximize flexibility for updating apps.

Integrate to many information / content sources.
Built-in compliance and analytics.

The Current Automation Platform Landscape

New platforms have several advantages. Where they come into play with the Unicorn is in orchestrating, coordinating and managing various IC and RPA pieces, providing a much more efficient, stable, and automated process:

Aggressive Best-in-Class peers focus on using “light” platforms to improve decision-making, self, service and automation, and to replace other legacy platforms.
Leading solutions are comparable on core capabilities, but differ more significantly in emerging capabilities.
Core capabilities include user experience, business rules modeling, case management, document support, process and flow design, analytics, integrations, enterprise scalability, etc.
Emerging capabilities include AI and RPA integration, low-code, mobile engagement, customer journey metrics, etc.

The three major types of low-hanging fruit for these combined solutions are:

1) Automating everything better: from 80% to 99%.

2) Automating things you couldn’t before: handprint and handwriting, package level validation.

3) Attaching to the front-end of RPAs. RPAs need semi-structured text or data to work –paper and dumb images are indigestible to them. Stick IC to the front of an RPA and you can automate more. Note that you can insert IC and RPAs at any stage of a process, not just the front end.

What's The Next Step For You?

Do a Proof of Concept

Start with a Proof of Concept (PoC). The POC process has 4 big steps, each of which consists of several smaller steps:

1) General Preparation, where you plan what you want from the POC and make some of the big decisions like who you’re going to test and why.

2) Detailed Preparation, where you get everything ready for all testing.

3) Actual Testing of the software tools against your own docs and environment.

4) Evaluation, where you evaluate your results and decide what Next Steps you should take.

How to Govern Your Process Automation Initiatives

Another question is what kind of governance structure you should have as you expand your RPA and capture capabilities. We recommend that you start with an extension of capture or workflow, or with the RPA group that’s trying to extend and grow to the next level. Mature organizations have a strong centralized matrix organization with oversight committees, cross-functional involvement in platform direction/roadmap, and alignment with enterprise initiatives and business unit priorities.