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RPA Operating Model Guidelines, Part 3: From Pilot to Production & Beyond – The Keys to Successful RPA Deployment

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As well as conducting extensive research into RPA and AI, NelsonHall is also chairing international conferences on the subject. In July, we chaired SSON’s second RPA in Shared Services Summit in Chicago, and we will also be chairing SSON’s third RPA in Shared Services Summit in Braselton, Georgia on 1st to 2nd December. In the build-up to the December event we thought we would share some of our insights into rolling out RPA. These topics were the subject of much discussion in Chicago earlier this year and are likely to be the subject of further in-depth discussion in Atlanta (Braselton).

This is the third and final blog in a series presenting key guidelines for organizations embarking on an RPA project, covering project preparation, implementation, support, and management. Here I take a look at the stages of deployment, from pilot development, through design & build, to production, maintenance, and support.

Piloting & deployment – it’s all about the business

When developing pilots, it’s important to recognize that the organization is addressing a business problem and not just applying a technology. Accordingly, organizations should consider how they can make a process better and achieve service delivery innovation, and not just service delivery automation, before they proceed. One framework that can be used in analyzing business processes is the ‘eliminate/simplify/standardize/automate’ approach.

While organizations will probably want to start with some simple and relatively modest RPA pilots to gain quick wins and acceptance of RPA within the organization (and we would recommend that they do so), it is important as the use of RPA matures to consider redesigning and standardizing processes to achieve maximum benefit. So begin with simple manual processes for quick wins, followed by more extensive mapping and reengineering of processes. Indeed, one approach often taken by organizations is to insert robotics and then use the metrics available from robotics to better understand how to reengineer processes downstream.

For early pilots, pick processes where the business unit is willing to take a ‘test & learn’ approach, and live with any need to refine the initial application of RPA. Some level of experimentation and calculated risk taking is OK – it helps the developers to improve their understanding of what can and cannot be achieved from the application of RPA. Also, quality increases over time, so in the medium term, organizations should increasingly consider batch automation rather than in-line automation, and think about tool suites and not just RPA.

Communication remains important throughout, and the organization should be extremely transparent about any pilots taking place. RPA does require a strong emphasis on, and appetite for, management of change. In terms of effectiveness of communication and clarifying the nature of RPA pilots and deployments, proof-of-concept videos generally work a lot better than the written or spoken word.

Bot testing is also important, and organizations have found that bot testing is different from waterfall UAT. Ideally, bots should be tested using a copy of the production environment.

Access to applications is potentially a major hurdle, with organizations needing to establish virtual employees as a new category of employee and give the appropriate virtual user ID access to all applications that require a user ID. The IT function must be extensively involved at this stage to agree access to applications and data. In particular, they may be concerned about the manner of storage of passwords. What’s more, IT personnel are likely to know about the vagaries of the IT landscape that are unknown to operations personnel!

Reporting, contingency & change management key to RPA production

At the production stage, it is important to implement a RPA reporting tool to:

  • Monitor how the bots are performing
  • Provide an executive dashboard with one version of the truth
  • Ensure high license utilization.

There is also a need for contingency planning to cover situations where something goes wrong and work is not allocated to bots. Contingency plans may include co-locating a bot support person or team with operations personnel.

The organization also needs to decide which part of the organization will be responsible for bot scheduling. This can either be overseen by the IT department or, more likely, the operations team can take responsibility for scheduling both personnel and bots. Overall bot monitoring, on the other hand, will probably be carried out centrally.

It remains common practice, though not universal, for RPA software vendors to charge on the basis of the number of bot licenses. Accordingly, since an individual bot license can be used in support of any of the processes automated by the organization, organizations may wish to centralize an element of their bot scheduling to optimize bot license utilization.

At the production stage, liaison with application owners is very important to proactively identify changes in functionality that may impact bot operation, so that these can be addressed in advance. Maintenance is often centralized as part of the automation CoE.

Find out more at the SSON RPA in Shared Services Summit, 1st to 2nd December

NelsonHall will be chairing the third SSON RPA in Shared Services Summit in Braselton, Georgia on 1st to 2nd December, and will share further insights into RPA, including hand-outs of our RPA Operating Model Guidelines. You can register for the summit here.

Also, if you would like to find out more about NelsonHall’s expensive program of RPA & AI research, and get involved, please contact Guy Saunders.

Plus, buy-side organizations can get involved with NelsonHall’s Buyer Intelligence Group (BIG), a buy-side only community which runs regular webinars on RPA, with your buy-side peers sharing their RPA experiences. To find out more, contact Matthaus Davies.  

This is the final blog in a three-part series. See also:

Part 1: How to Lay the Foundations for a Successful RPA Project

Part 2: How to Identify High-Impact RPA Opportunities

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