6 Main Characteristics of the Digital Workforce
To help financial organizations understand why Intelligent Automation solves problems that earlier RPA solutions couldn’t handle, IDC’s Sneha Kapoor has published an insightful report that defines cognitive automation and makes a compelling case for why it’s a game-changing leap forward for enterprises with aggressive digital workforce transformation and cost-reduction initiatives.
Notably, this report — “Robotic Process Automation Game Changers Advance Financial Services Institutions Toward Intelligent Digital Workforce” — takes a firm stand on how to define “intelligence” in automation software. It’s a strong validation for operations who choose AI-driven automation products like WorkFusion, and it’s a great guide to a digital workforce experience for those who are transitioning from first-generation RPA to Intelligent Automation.
Let’s consider IDC’s six key characteristics of the intelligent digital workforce.
1. Simple, usable and reusable by business users
Before RPA, integrating applications required IT expertise, and lowering the cost of operational work required business process outsourcing (BPO). An intelligent digital workforce gives business people— the people in charge of functions like customer onboarding, trade settlements, and anti-money laundering efforts (AML) — the power to automate, on their own.
Intelligent Automation software with enhanced ML and QC capabilities automates cleansing data and the learning models of the digital workforce training machine. The IDC report mentions “improving data quality, redesigning processes and automation workflows, interoperability and integration.” A unified platform approach simplifies integration of critical tools such as OCR, BPM and rules engines.
2. Ability to deliver enterprise-wide scale
IDC acknowledges the “rapidly growing demand for an agile digital workforce solution that can offer a single unified platform with a centralized view and management of enterprise-level automation across various IT systems and technologies.” In other words, neither end-users nor executive sponsors want rogue projects, cobbled together with disparate tools. To ensure automation success at a business-wide level, the smartest businesses select one primary platform to automate cross-operational functions and generate robust analytics.
3. Security and governance as foundational tenets
IDC highlights the importance of “financial organizations’ ability to address the issues around data quality, data usability and data governance.” The inability of first-generation RPA products to monitor data quality is one of the biggest reasons complex businesses have struggled to scale their automation programs. Also, no one should overlook the growing challenge of regulatory compliance — essential for banks, insurers, healthcare providers and other organizations. Intelligent automation products with native OCR, AI and RPA can process documents at massive scale. They also provide audit trails and explainable algorithmic decisions, which let compliance teams give regulators proof of success and comprehensive documentation of process.
4. Availability of real-time operational analytics
To measure ROI and achieve strategic resource planning, it’s critical to know both the performance of individual bots and of the functions they automate. Enterprise customers who choose products with unified platform models — i.e., “all-in-one” products — can see real-time performance and predicted performance of bots, people and functions. The latest generation of intelligent automation platforms also generate prescriptive insights: recommendations toward optimal operational performance.
5. Intelligence powered by cognitive/AI technologies and innovative digital workforce tools
IDC points out that “progressing to more advanced digital workforce technologies will stand a higher chance of delivering better business value and success.” Though there are many success stories, there are also numerous automation programs that have stalled — and those have first-generation RPA products to blame. Products with native AI make it possible to automate complex, non-standardized, and less repetitive tasks. IDC says: “Most vendors offer these digital workforce capabilities through third-party partnerships; only a few have proprietary solutions” — and we are proud to say that WorkFusion pioneered native cognitive/AI automation, plus it’s the only product that delivers end-to-end process automation without third-party vendor integrations.
6. Strong support extended by the ecosystem
Despite the increased simplicity of modern products, most large enterprises work with partners to deploy and scale intelligent automation, i. e. develop the digital workforce. Products with a unified platform model and native AI eliminate the brute force integration work that partners are often paid to do and allow expert resources to focus on the most valuable work: identifying processes to automate and deploying the product across the business.
In every growing technology category, buyers have many choices. Enterprise leaders with a long-term, strategic view of their business want to reduce costs, drive revenue, and improve the experience of both their customers and employees. An intelligent digital workforce is key — and knowing what to look for when it comes to taking automation efforts to the next level helps leaders make the best decisions for their organizations.
Note: This article responds to only part of IDC’s “Robotic Process Automation Game Changers Advance Financial Services Institutions Toward Intelligent Digital Workforce.” In another article, we discuss the report’s definitions for an “intelligent digital workforce” and “cognitive/AI” solutions. WorkFusion has licensed the report, so if you’re interested in reading more, you can freely download a copy here.
Also published on Medium.