By JOLT Experts on Mar 19, 2019 5:26:04 PM
Robotic Process Automation has proven to be one the main drivers of digital transformation across organizations, helping businesses maximize productivity and strive in competitive markets.
However, 40% of initial RPA projects fail and many organizations still struggle to meet expectations and scale their automation footprint. Among the main challenges are failure to select the right business process candidates for automation and automating broken processes without redesigning and optimizing them first.
To shorten the path to RPA, organizations need to have a clear process discovery strategy to identify automation opportunities, analyze productivity gaps, and optimize human driven business processes to maximize automation suitability. And in order to optimize a process to increase efficiency and decrease costs, we need to start by understanding how it currently works. That’s where process discovery and documentation are key to RPA's overall success.
In many organizations, the level of process knowledge and understanding is surprisingly low. They may have collections of standard operating procedures, but these are often poorly documented and outdated, leading to individual employees following their own understanding of best practices. Working with high-performing employees to challenge and improve the process and embed them into RPA, can result in significant improvements in the automated processes and reduce process problems across other parts of the business.
However, for many enterprises, traditional manual process discovery practices are still predominant, which can lead to:
- Selection of the wrong processes which can lead to more cost burden and missed ROI and expectations.
- Lack of data capture strategy which will lead to process fragmentation and increased inconsistencies.
- Automating highly complex and broken processes which can lead to an increased amount of exceptions that ultimately ends in automation failure.
- Relying only on the knowledge of human SMEs and manual documentation, which can be time-consuming, lack of data consistency, and lead to missed opportunities.
Best practices for RPA process selection
Remember just because it can be automated, doesn't mean it should be. Start by identifying rule-based, standardized processes that cross multiple systems, which need a nonintrusive approach to automation. Evaluate RPA opportunities where there is accumulated "swivel chair integration" (rekeying data between systems) and identify where work is being performed by humans that involves structured, digitized data processed by predefined rules.
Find processes with these characteristics:
- High manual and repetitive
- Mature and stable
- Not subject to methodology changes
- Has ROI potential
- Low exception handling required
- Contains readable inputs
- High volume transactions
Leverage Automated Process Discovery Tools
Automated process discovery tools can be key to boost process mining and optimizations efforts for RPA. Our partners at OpenConnect, provides the tools to improve any process — large or small, basic or complex.
It starts with accurately capturing the right activities and tasks being performed. You can get log data from larger packaged software like Oracle and Salesforce. However, if you aren’t including desktop tasks, you are not seeing the full automation opportunity. Using OpenConnect's WorkiQ we capture EVERY task that occurs on the desktop, natively. The tasks are captured where your people are doing actual work without interrupting the user. It doesn’t capture how the work is supposed to be performed, but it captures how it is actually being completed. Once this data set is collected, we can send it their DiscoveriQ tool for quick process documentation outputs of known process activities and variations. By using analytics to help design the outcome you are able to produce a result that improves your speed to ROI, overall cost savings and the final outcome.
The appropriate process discovery tool and strategy can provide accurate and complete process visualization and process documentation across your enterprise.
Don't Forget about Process Optimization
As Peter Drucker, business management expert famously said: “There is nothing so useless as doing efficiently that which should not be done at all.”
In the age of automation, businesses are pressured to doing more with less, making the lean methodology essential for automation success.
Lean Sig Sixma is a key complement to RPA, with LSS, you manage to reduce the manual load by eliminating waste, and by simplifying and standardizing processes, but then you reach a terminus where you realize you are not able to eliminate all the grunt work. This is where RPA comes into its own, expanding the LSS toolkit with an approach that empowers the business to continue to improve and move up the sigma scale without the need for bit disruptive IT initiatives.
LSS helps organizations:
- Identify the right candidates for automation
- Improve process stability
- Enhance process robustness
Best Optimization Practices With Lean Six Sigma for RPA:
- Filter the process candidates with SixSigma
- Standardize process redesign in your CoE with LSS practices
- Systemize the delivery process
- Never automate broken processes with temporary fixes and high exception
By leveraging the right process discovery tools, and filtering mined processes with the right optimization approach, organizations can ensure a streamlined planning and implementation of RPA across the enterprise.
Register to our webinar 'How To Streamline Rpa With Process Discovery & Optimization For Automation' where we will address the best practices for RPA process discovery, selection, optimization and bot translation for better automation results, along with a live demo of our partner OpenConnect's automation process discovery solutions.