Faced with the challenges of becoming digital organizations that truly meet customer and citizen demands, many organizations want to support their holistic transformation by combining new and emerging technologies. According to the CGI Client Global Insights (2017), one of the top trends among business and IT leaders is increasing use of digital technologies (e.g. robotics, advanced analytics, cloud etc.). The potential of intelligent robotic process automation (RPA) for increasing the efficiency of operations and creating new products and services is being explored in many industries worldwide. Over the last few years, CGI has spent a lot of time proposing and delivering Proofs of Concept (POCs) and enterprise RPA projects to IT and business leaders.
Based on this experience, CGI wants to share some of the lessons it has learned with leadership teams wishing to embark on an intelligent automation journey. Here are seven tips to consider:
1. Aim small, miss small
In its current form, RPA is just the beginning of an automation journey toward much more cognitive-based solutions. That said, since organizations need to get used to a new and very different way of thinking when it comes to automation, they should start small, aim for low-hanging fruit, and build from there. This applies to everything, from proposing RPA POCs all the way to selecting business processes for first-time implementation.
2. Select, select, select
Building successful RPA projects is all about choosing the right business processes. Whether it is a POC or an RPA factory solution running at full speed, automation is only as strong as the business processes selected to back it up. Unless you get this right, everything further downstream will also go wrong, leaving you trying to play catchup. Based on some very good work by CGI teams, we have built a customizable process selection and analysis tool that lets us to filter out poor candidate processes relatively quickly.
3. Keep it simple
This age-old principle is still valid for RPA projects. From process selection to infrastructure setup, don’t try to “boil the ocean.” Instead, an agile approach with a continuous delivery model works best for building organizational confidence and ironing out any kinks in the delivery model.
4. Never underestimate anything
The buzz around RPA has been about how easy it is to develop and implement. While this is true, too many times both organizations and implementation partners make the mistake of underestimating the amount of work and experience required to provide a quality product. Yes, it is easier and faster to deliver, but successful implementation still depends on experienced people.
5. Put the right infrastructure in place
Having struggled to create an ad hoc, quick-and-dirty hosting solution, CGI has learned the hard way that it’s extremely important to have the proper infrastructure solution in place from day one. Virtual workers are useless if they can’t connect to the automation engine.
6. Measure and track
To deliver and continue improving the efficiency of virtual workers, it is important to have baseline metrics and then provide ongoing tracking of efficiencies on a daily, weekly and monthly basis. The reporting functionalities of enterprise tools are limited, but that is mostly by design. Any reporting required should, and can, be created from within the automation approach itself to ensure customized designs that fit to an organization’s needs and KPIs.
7. This is just the beginning
As mentioned at the outset, RPA in its current form is not the culmination of intelligent automation. It is a stepping stone to greater opportunities in the journey toward full-blown artificial intelligence. Every automation solution should be modular enough to fit into more cognitive and AI-based solutions such as conversational agents and chat-bots, intelligent document processing, natural language platforms, voice recognition and synthesis, computer vision/image processing and machine learning (including deep neural nets), to cite just a few examples.
If you’re interested in learning more about CGI’s capabilities in intelligent automation including robotics process automation, chat-bots etc. please contac