While a majority of organizations cite digital transformation a priority for next two years, the business process automation will be a crucial part of their digital transformation strategy.
Process automation, also called robotic process automation (RPA), allows enterprises to automate their tasks and decisions, which helps them in improving business processes and making the IT operations more efficient.
Various organizations turn to the service providers that embed automation into business process outsourcing (BPO) and business process as a service (BPaaS) offerings.
In a new report, IDC has identified three stages in the intelligent automation value chain for organizations and service providers implementing process automation solutions.
The intelligent automation is a combination of artificial intelligence and automation that helps organizations to rise above the traditional performance tradeoffs and achieve higher levels of efficiency and quality.
“Cost reduction and workforce and process efficiency are a few of the benefits that are driving major interest in automation across many organizations,” said Ali Zaidi, research director, IT Consulting and Systems Integration Strategies at IDC.
“While most organizations are still in the early phase of RPA and AI-enabled automation adoption, developing an overarching automation strategy and developing the right use cases that map to specific business and IT outcomes will be crucial to the successful adoption of intelligent automation in the near term.”
Stages: the value chain of intelligent automation services
When the repetitive tasks that leverage structured data are automated using basic technologies like macros and scripts, they are categorized under basic automation.
The use cases of basic automation can include executing data manipulations, creating new documents, completing manual data entry, extracting data from multiple sources, etc.
Machine Augmented Decision Making
There are several tasks that are performed by human by following a predetermined set of rules. The process automation of such tasks using software tools is called machine augmented decision making.
If there are tasks that can’t be performed using process automation, then both humans and machines work on them together.
Various business processes can be automated with MADM, such as analyzing and processing invoices, best recommendations, route and track work across ecosystem, as well as connect data resources to tasks at runtime based on context.
Autonomous Decision Making
Autonomous decision making, also called decision-centric process automation, is the automation of nondeterministic tasks using systems or machines. What these systems and machines do is receive and analyze data, and discover patterns from data to predict a decision, and then provide a recommendation to improve it.
The autonomous decision making is applied for preventing unplanned outages, recommendation engines, customer onboarding medical diagnostics, and Intelligent virtual agents.
The organizations turn to service providers to build RPA and intelligent automation capabilities for them. IDC said that every organization should consider the entire intelligent automation value chain when selecting an intelligent automation vendor.
“RPA is embedded throughout most BPO engagements today, and buyers are expecting a cost savings of almost 30% and to recoup the funds from their initial investment in one to two years. However, providers can still be more proactive in recommending automation capabilities according to some buyers,” said Alison Close, research manager, Finance and Accounting, BPaaS, and Analytics Services at IDC.
“For BPO providers to be successful with RPA or AI implementations, sharing use cases will be critical – specifically, the investment required (software licenses, implementation fees, maintenance fees, etc.) and the cost and productivity savings achieved,”