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How BPM and RPA Are Changing the Development Landscape Forever
Workflow efficiency translates to better business outcomes.
22:01 05 June 2018
There are a lot of directions a company can go to boost effectiveness and productivity, and more and more automated options are arising. The demand for tools that are accurate and streamlined is growing as enterprises look for the most efficient ways to collect, maintain, and deploy data.
Blending business process management (BPM) with robotic process automation (RPA) gives enterprises an advantage when it comes to better management of data and business operations. The two together offer a reliable way to interact with the workflow systems already in place for trustworthy results.
Not sure how to make either - or both - work for your operation?
Let’s start with the basic definitions of BPM and RPA:
- Business process management (BPM) is a meticulous way to improve workflow, while adapting to changes. Business process management isn’t an umbrella item; each business process activity follows a certain path for a particular goal.
- Robotic process automation, or RPA, allows developers to automate tasks like data entry through a retrieval process that taps the actual interface of a database or application. This allows the company to go past any missing APIs for a faster end result.
Pegasystems, a customer engagement software developer, connects robotic process automation with BPM like this:
“RPA is a perfect fit for BPM: If an automation fails or is unavailable, BPM can easily route the request to a pool of humans to complete.”
So in this way, RPA is not just an automated system left to its own devices (and therefore, volatile). RPA automates everything it possibly can and then sends the rest to a human who can better analyze and respond. Rather than bypassing the missing pieces, RPA identifies them and flags them for correction or identification.
These solutions working together aren’t without their downsides. Analyzing the amount of data required to execute RPA and BPM requires significant bandwidth and infrastructure. Constant network analysis and testing is required to keep the automation running smoothly.
The End of Screen-Scraping
The earliest RPA systems used a process called “screen-scraping” to collect the data needed for automation between incompatible legacy systems. For basic applications, this approach is pretty accurate – but most enterprises have complicated, multi-step processes that need a step up from this increasingly-archaic method of data collection. This is the same technology that today is used to extract data from the web, although there’s still limitations to scraping the web due to compatibility with systems and an underlying reliance on the HTML code of websites. A system that works just part of the time isn’t very effective.
Instead, enterprises should look for RPA options that actually work with the controls of application. This improves the speed of delivery and results in much more reliable outcomes. Automation of business processes frees up customer service staff for more creative, vital tasks. Many large corporations that are highly regulated are using BPM and RPA to follow mandated procedures or communicate regulatory information to increase customer service productivity and reduce costs. To implement robotic process automation, an organization needs to first document the business processes that RPA systems will automate. During this process, businesses will be able to analyze employee workflows to identify inefficiencies such as navigation across disparate applications and keystroke errors causing customer experience disruptions. Once all inefficiencies and workflow processes are documented, robotic process automation can be implemented to automate many of the repetitive tasks slowing down customer service representatives.
Combining BPM with RPA is forever changing how enterprises operate. Retrieving data through systems already in place means a more accurate, targeted result that leads to workflow efficiency. Leading RPA solutions can work with existing systems, both online and on desktop, without the need of API’s to move data accurately and efficiently. That optimal performance results in improved productivity – and overall business performance.