Robotic automation, machine learning, artificial intelligence, the Internet of Things — so many buzzwords surround business process automation. On closer examination, they all point to the same theme: knowledge-rich processes. Whether they involve insurance claims, mortgage approvals or clinical studies, they are all becoming digital, instrumented, analyzed and increasingly operated by smart machines and code.
The benefits of such automation, often called robotic process automation (RPA), include lower error rates, lower costs, and faster throughput. But while technically accurate, the term RPA often misses the bigger point of what can be gained through process automation. Rather than just automating rote tasks, organizations can harness the rich data and metadata that accumulates around process value chains, extending the capabilities and talents of human workers, and making their smart processes even smarter.
For instance, organizations can use process intelligence to get immediate feedback on what’s happening within the process itself, and act on those insights in real time. An example is in automated claims management: when insurers use the data from their daily audit logs to detect hidden fraud patterns that could never be discovered in a manual process, they can move beyond incremental efficiency improvements to competitive advantage. To get started with this more transformative approach to business process automation, organizations should take the following steps to work better and differently:
- Pick your pressure points: Conduct an audit of existing processes and choose ones that are ripe for re-instrumentation. Prime candidates include processes with digitized inputs, those that are prone to error and re-work, or are characterized by repeatable tasks and a structured, rules-based approach. Businesses should also consider processes in which workers toggle between multiple systems and screens to perform data checking, inputting, searching, or collating. Consider how you can apply analytics to moments of engagement to improve metrics such as cost-per-claim, clinical trial yield, healthcare unit cost, fraud prevention rates, etc.
- Calibrate where, how, and when process automation complements the workforce: Give employees access to digital process tools. It’s not the number of people “doing the process,” it’s about outcomes.
- Fuel “meaning-making” with process data. Focus on industry-specific processes, like underwriting, clinical drug trials, or wealth management, or horizontal ones, like supply chain or CRM, especially those that shape 10 percent of costs or revenues. Focus on data that is, or could be, exchanged and used for value.
- Go beyond “simple” automation: Evaluate a fully digital transformation of core processes to discover insights into the movements of people, goods, information, and services that are “born digital.”
The real benefits of business process automation will happen only if organizations master the rich data insights about their processes, unlocked by the powerful tools of digital automation. The end game of process automation isn’t automation itself but the intelligence it can unlock to drive meaningful insights, value, and business outcomes.
Robert Hoyle Brown is an Associate Vice President in Cognizant’s Center for the Future of Work, and drives strategy and market outreach for the Business Process Services Practice. He is also a regular contributor to futureofwork.com. Prior to joining Cognizant, he was Managing Vice President of the Business and Applications Services team at Gartner, and as a research analyst, he was a recognized subject matter expert in BPO, cloud services/BPaaS, and HR services. He also held roles at Hewlett-Packard and G2 Research, a boutique outsourcing research firm in Silicon Valley. He holds a Bachelor of Arts degree from the University of California at Berkeley and, prior to his graduation, attended the London School of Economics as a Hansard Scholar.
