Cognitive Automation and the Disruption of Business Services

Using a Center of Excellence approach to Create Scale and Drive Adoption

To help manage change, increase adoption, build scale and establish core standards, some organizations have established an Automation Center of Excellence (COE). Establishing this type of COE, guided by the right charter has helped develop and implement bots with higher success rates and better efficiency by combining the strengths of business analysts, development resources, process engineers, and operations expertise under one umbrella.

Several of our clients have found that the successful implementation of an RPA program in one small part of the business has created a catalyst for further automation in other functions in the enterprise. In these cases, the COE has played a vital role in facilitating the expansion of automated processes, as well managing change and galvanizing support from the stakeholders.

During the initial RPA deployment, the COE is formed and focuses on gathering the knowledge and codifying the processes and mechanisms to capture and digitize process knowledge and document lessons learned. Then COE can create process libraries and toolsets that can be redeployed across other areas of the enterprise and enable subsequent programs with minimal effort.

Realizing the benefits of bots

While cognitive automation and RPA can provide a number of benefits to a business in terms of cost savings and greater efficiencies, they also present their own unique issues that CIOs must be able to address.

To be sure, the fundamental role and responsibilities of IT don’t change in an RPA environment. Development, testing, operations support, and performance tuning are all necessary components to a successful bot solution. For example, bots are considered users. For system changes, when user acceptance is identified in testing plans, testing scenarios must be devised and conducted just as they would for a human user.

Nevertheless, dealing with bots may require some adjustments. For instance, the role of QA may indeed grow. Consider this situation: A business user may request a small change to the user interface of a system to make it easier to use.

Traditionally, these changes are low risk. But where RPA is deployed, even simple user interface changes can negatively affect bot performance. Bots expect fields, text boxes, etc., on screens to be presented in the same place every time. Human users can be trained for UI changes, but bots must be reconfigured to “learn” the new screens. Additionally as bots become more efficient through machine learning, QA must ensure that the bots are learning the right resolution to issues, as those learnings have the ability to proliferate much faster.

As RPA is implemented, humans and bots will likely exist in the same workflow. But, of course, bots aren’t subject to the same time constraints as human users: They don’t need to adhere to work hours and can process work much faster. As parts of a process are sped up, and other parts remain the same, being able to predict where and to what degree bottlenecks will occur allows for better resource planning—not to mention having a tremendous positive downstream impact on the overall success and return on investments.

Next Steps

How can CIOs achieve success in developing and executing an RPA strategy? A key and fundamental factor is demonstrating how bots can help solve business problems and how they fit into the organization’s existing architecture/toolset.

Here are some steps CIOs should consider to ensure that the message of adding value is communicated to the business.

• Work with business partners to define use cases and proof-of-concept opportunities. Or pilot RPA in a small setting first and highlight its benefits to your business partners.

• Work with business partners to define the best scripting and support model. It comes down to a balance of “do it for them, do it with them, let them do it themselves.” Remember, as soon as a bot stops working and affects a business process, the helpdesk will hear about it.

• Have a demand-management capability before marketing RPA. Business units can get very creative with RPA and demand will pick up quickly. Have an idea of how prioritization, license allocation, hardware asset allocation, etc., will be governed.

• Form a business case for each opportunity and hold people accountable for the savings they identify related to RPA. Many of the grassroots opportunities will come from teams who have multiple people doing a task for part of their day. In order to achieve savings, work has to be re-allocated to remaining staff.