Eliminate Technical Ambiguity in RPA

As a technology user, you’ve likely encountered uncanny bugs in tax preparation software, phone applications, and various other products and services. Such gaps are inherent due to differences in how people communicate with the world and how computers communicate with each other. For example, people use a base ten counting system and computers use base two.

Managing the ambiguity between how a person completes a process and how a computer should be instructed to complete the same process isn't a feat to take lightly. It requires concentrated effort between various people spanning analysts, RPA developers, solution architects, project managers, testing engineers, system administrators, and many others.

In this article we’ll run through top drivers of technical ambiguity and how to minimize or remove it all together.

Siloed Robotic Process Automation (RPA) operations

Siloed RPA implementation and operation leads to a breakdown in coordination between departments. A resulting lack of integration planning and collaboration then leads to a poor understanding of the overall automation architecture, and a broken view of business processes.

RPA problems can lead to negative implications including inconsistent data, failing downstream processes, and even poor reputation or legal ramifications.

When multiple departments sign contracts with RPA providers, it leaves the organization in a fragmented state that has little to no centralized oversight.

Unintentionally decentralized RPA initiatives result in automation scaling gaps which limit benefits and reliability for the enterprise.

Overcoming siloed RPA operations requires the establishment of a center of excellence and a governance model.

Governance should clearly establish the RPA strategy, how resources will collaborate effectively, the objectives, and the best practices to be applied. For example, HR can be a partner in the program to assess the impact of RPA on the company, highlight skill gaps, and develop training programs to upskill employees with extra time on their hands. In return, HR can also become an automation beneficiary to receive technology solutions that makes manual mundane work obsolete.

The best way for an RPA program to be managed at an enterprise level is by establishing an RPA Center of Excellence (Furlong, 2017).

Technical ambiguity

Even though companies stand to gain a lot from RPA, many are having trouble realizing the full potential due to technical debt they've incurred or continue to incur. RPA ambiguity is a result of poorly managed assets, improperly scaled infrastructure, and inadequate license usage.

Minimal oversight and a lack of applying best practices also drive technical ambiguity. Ambiguity that goes unresolved for too long can have a devastating effect on an organization’s ROI and stakeholder experience.

Consider, as an example, a fleet of fifty automated bots implemented without centralized logging in place. As it becomes apparent that this isn't scalable from a monitoring perspective, the backlog of work to standardize the logging could hold the company back from implementing new automation to drive actual value to the business.

Removing technical ambiguity requires that companies address questions spanning:

1. Asset management,
2. Support of RPA bots
3. And various other delivery process questions (Parikh, 2018).

IT support is an important factor which not only maintains the infrastructure and automated processes, but the function also takes direction from InfoSec on how to guarantee systems meeting security requirements.

Questions regarding ownership of functions, such as IT support, should be addressed early on in RPA programs. If resources don't currently exist for effective RPA support, then they must be accounted for from the start.

Getting clear buy-in that establishes ownership and accountability for the RPA program helps to resolve technical ambiguity. Keeping track of individual automation key contacts (spanning those that are responsible, accountable, consulted, and informed) is also a must. Being nimble to begin with is fine, but as the program matures, it's important that expectations and resources also mature.

Poorly managed change

Avoiding ambiguity requires documentation, version control, and testing procedures, among many other change management practices. To learn more about libraries or frameworks that document these, you can look into COBIT or ITIL (which was covered on the topic of defining an automation strategy).

Lack of formal hand-offs

When original teams that build automation move on from the company, or to another department, automation operation becomes problematic if the hand-off was not completed thoughtfully.

In a poor-hand off scenario, business users don’t know where the logs are, if the logs contain textual data only (or if screenshots are available), what the escalation procedures are (or who to escalate to), what the business exceptions are, how unknown business exceptions are handled, and so forth.

When everything is running fine, not knowing the answers to these questions isn’t detrimental to the business. It’s when ‘stuff’ hits the fan that these unknowns set alight blazing fires that need to be put out.

In organizations that value removing technical debt and ambiguity, it only takes a few repeat incidents where teams don’t have the necessary documentation or fallback procedures to get serious about change management.

For organizations that accept the status quo, it’s not unlikely that these impromptu fires and unnecessary calls will become their way of doing business. It's also not unlikely that eventually it becomes the way that their business is undone.

For companies that want to make automation resilient and reliable, it's important to prioritize:

1. The creation of a logging and monitoring standard.
2. RPA BCP plans along with assigned process owners that incidents are escalated to.
3. A quality control procedure for each process.
4. Technical documentation outlining exceptions and more.

Next steps

If you’re looking for strategy best practices for scaling an RPA program, you may want to review Scaling Intelligent Automation: 27 Strategy Best Practices.

Footnote:

The term 'Robotic Process Automation' is used due to its popularity in the industry. Process automation is a clearer term that'll ideally replace 'RPA.'

References:

Furlong, S. (2017, February 14). Overcoming the Challenges of Robotic Process Automation. Default. https://isg-one.com/articles/overcoming-the-challenges-of-robotic-process-automation

Parikh, S. (2018, February 12). RPA implementation – meet the challenges with the right approach. Nividous Intelligent Automation Company. https://nividous.com/blogs/rpa-implementation-challenges-and-right-approach