How Can My Company Benefit From Robotic Process Automation?
Peter Drucker was quoted as saying ‘there is nothing so useless as doing efficiently that which should not be done at all." His wisdom continues to ring true today as readers reflect on the fact that robotic process automation (a technology) can only be successful when founded upon a business's process improvement initiative.
This article will examine the challenges of RPA — those that your company must mitigate, avoid, or augment to benefit from automation. The second half will cover specific use cases for top industries benefiting from RPA.
What minimizes RPA benefits?
EY, a top consulting firm, has reported that they’ve seen anywhere from 30–50% of RPA projects fail (10 Common Pitfalls to Avoid When Delivering Robotic Process Automation Projects, 2017). Their experience shows that failure is a result of a lack of business partnerships with IT, Cyber, Risk, HR, and other lines of business. Not treating RPA as part of a change program also causes issues.
On the other hand, EY has seen that automating most of a process (say 70%) is enough to realize cost-effective benefits. If a company attempts to go all in on automating a process, including all scenarios no matter how variable they can be, that increases the chance of failure. The 80/20 rule is paramount to RPA as it is to other facets of business - in this industry you want to focus on automating 20% of the work that will drive 80% of the results.
Another mistake that companies early in their RPA journey can make is not fully scoping the investment needed for infrastructure and for RPA development resources. Simply because a business user can build a proof of concept doesn't mean that their automation can scale to a resilient ecosystem that is profitable. Resilient solutions are those with excellent up-time, are proactively checked for upgrades (to avoid incidents), and are supported effectively (to guarantee success throughout years of operation).
Companies benefit most from RPA when they treat automation as a program through governance, proper management, and nimble execution. In an ideal setting, RPA would be seen as another tool in the toolbox of automation which includes:
- Integration solutions (IPAAS)
- Vendor’s workflow products already in use by the company (such as those from Microsoft or Salesforce)
- Other automation avenues including Python, APIs, and workflow orchestration (such as Airflow).
What types of Robotic Process Automation are out there?
RPA bots come in a variety of attended, unattended, or hybrid options.
Attended bots run on a user’s machine and help them perform work more efficiently. The user can watch the bot as well as pause it.
The downside is that the user's computer can't be used for anything else (unless a virtual machine is run which allows for the minimization of the environment the bot runs in).
Some applications, such as web browsers, can also be automated in the background without the need for virtual machines. Automating applications in the background of a user's machine is referred to 'picture in picture' by some RPA vendors.
Unattended bots run on servers and are triggered by events such as database updates, emails, or business users.
Hybrid bots are a mix of attended and unattended bots. For example, an attended bot started manually could trigger the start of an unattended bot.
Use cases for the insurance industry
The insurance industry is notorious for high volume work due to the hundreds of thousands of cases processed yearly. RPA is a perfect fit for helping employees spend less time on manual data entry, updating claims, and detecting fraud.
As an example, the decision making tables used for fraud patterns in the insurance industry require checking disparate systems to establish fraud scores (Verma & Ramakrishna Mani, 2013).
Even though a system may use regression analysis (through AI) to compute a final fraud score, it still needs the data to do so. Verma and Mani establish that such data is often fed through manual work that surfaces public records (spanning judgments, foreclosures, criminal records, and address change frequency).
RPA evolves the process of collecting and entering case information into a seamless and efficient experience. With all of this manual work out of the way, employees can focus on completing the tasks that require human creativity and judgment.
RPA use cases for manufacturing companies
Manufacturing companies rely on modern and legacy software to execute their processes. Legacy software is needed due to constraints ranging from interoperability with factory machinery (which can last decades) as well as the desire to keep production uptime as high as possible.
Thankfully, RPA implementations can help manufacturers with quoting, invoicing, and other manual operations. Manufacturers already use Agile, data analytics, and physical robots, which gives them an advantage over other industries that aren't as comfortable with robotics (Tilley, 2017).
Use cases for healthcare companies
RPA is a great solution for digitizing information found on accounts payable and paper documents used in a plethora of processs. The benefits of healthcare billing automation includes the improvement of revenue cycle times as well as a reduction in the manual labor required.
Hospital staff must complete mundane tasks such as keying in order data or moving information between systems. Automated healthcare processes enable staff to better serve patients, increase positive outcomes, and reduce cost (Ostdick, 2017b).
RPA use cases for the telecom industry
Telephone and communications companies deal in a high amount of support tickets. Here, RPA is used to automate manual tasks that support representatives must complete while on the phone with customers. Automation in this industry reduces average handling time (AHT) and helps increase customer satisfaction as well as employee moral.
The telecom industry is dependent on technology, but it's also dependent on paperwork. The industry's paperwork gets stored in a scanned format and requires various amounts of processing that leads to customer delays. Scanned data is also a challenge in maturing analytics programs since they require accurate and recent data (Ostdick, 2017a).
The integration of Robotic Process Automation with intelligent document processing makes it possible to transform paper records into digital information.
Use cases for retail companies
Retailers have exciting opportunities to automate manual data processing between point of sale systems, CRM systems, social media, and much more.
Better integrated retail data can be used to:
- Determine whether there is enough inventory in store
- Determine whether pricing is appropriate
- Identify where there are opportunities for promotion
Other use cases for retail include automating invoices, customer support requests, and order processing. For example, automation can enhance the productivity of agents (allowing them to handle more calls or returns during peak periods).
RPA use cases for the public sector
RPA has experienced great success in the public sector. Consider for example that North Tyneside, in partnership with ENGIE, reduced the cycle time of processing new benefit claims from 36 days to 25 days — which represents a 31% reduction (Hazlegreaves, 2017).
Ending note on RPA and AI
One unfounded fear within the public sector and other industries is that automation is in of itself Artificial Intelligence (which comes with its own concerns).
The reality is that RPA actions and results are easy to trace through the workflows they're developed in. Artificial intelligence on the other hand uses algorithms which aren't often as transparent. While RPA has the potential to integrate with AI, it doesn't have to be combined in the industries where AI presents unsolved challenges.
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
10 common pitfalls to avoid when delivering Robotic Process Automation projects. (2017, June 14). EY. https://www.ey.com/en_ee/financial-services-emeia/get-ready-for-robotic-process-automation
Hazlegreaves, S. (2017, December 15). Rise of the robots in the public sector. Open Access Government. https://www.openaccessgovernment.org/rise-robots-public-sector/40598/
Tilley, J. (2017, September 7). Automation, robotics, and the factory of the future. McKinsey & Company. https://www.mckinsey.com/capabilities/operations/our-insights/automation-robotics-and-the-factory-of-the-future
Verma, R., & Ramakrishna Mani, S. (2013, December). Using analytics for insurance fraud detection. The Digital Insurerr. https://www.the-digital-insurer.com/wp-content/uploads/2013/12/53-insurance-fraud-detection.pdf
