What Is Digital Process Automation (DPA)?
Quick Answer: Digital Process Automation (DPA) is a discipline focused on digitizing and automating end-to-end business processes to improve operational efficiency and customer experiences. Coined by Forrester in 2017, DPA evolved from traditional BPM to emphasize customer-facing, digital-first process orchestration across multiple systems and departments. As of 2025, the global DPA market is valued at approximately $16.7 billion.
Definition
Digital Process Automation (DPA) is a discipline focused on digitizing and automating end-to-end business processes to drive operational efficiency and improve customer experiences. Forrester Research coined the term in 2017 to describe the evolution of traditional Business Process Management (BPM) toward customer-facing, digital-first process orchestration.
Unlike BPM, which historically focused on documenting and optimizing internal back-office processes, DPA emphasizes building automated digital workflows that span multiple systems, departments, and customer touchpoints. DPA platforms typically combine visual process designers, form builders, rules engines, and integration connectors into a unified environment.
Core Characteristics
| Characteristic | Description |
|---|---|
| End-to-end process scope | Automates entire business processes from initiation to completion, not just individual tasks |
| Customer-facing focus | Designed to improve external experiences (onboarding, claims, applications) alongside internal operations |
| Visual process design | Drag-and-drop process modeling accessible to business analysts, not just developers |
| Multi-system orchestration | Connects and coordinates actions across CRM, ERP, databases, and SaaS applications |
| Rules engine | Business rules determine routing, approvals, escalations, and exception handling |
| Analytics and monitoring | Built-in dashboards tracking process cycle times, bottlenecks, and completion rates |
How DPA Differs from BPM and RPA
| Dimension | BPM | DPA | RPA |
|---|---|---|---|
| Primary focus | Internal process modeling and optimization | End-to-end digital process orchestration | Task-level desktop automation |
| Scope | Process documentation and workflow routing | Full process lifecycle including customer interactions | Individual repetitive tasks within existing applications |
| Users | Business analysts, process engineers | Business analysts, IT, citizen developers | RPA developers, CoE teams |
| Output | Process models, workflow rules | Digital applications with integrated workflows | Software bots mimicking human clicks and keystrokes |
| Typical tools | Appian, Pega, IBM BPM | Kissflow, Zapier, Make, Power Automate | UiPath, Automation Anywhere, Blue Prism |
In practice, many organizations combine DPA and RPA: DPA orchestrates the end-to-end process while RPA bots handle specific steps that involve legacy systems without APIs.
Practical Applications
- Employee onboarding: A DPA workflow triggers account provisioning, equipment ordering, training assignments, and manager notifications across HR, IT, and facilities systems when a new hire record is created
- Insurance claims processing: A DPA process captures claim submissions, routes to adjusters based on claim type and value, triggers document verification, calculates payouts, and sends customer notifications
- Loan origination: A DPA workflow manages the full lifecycle from application submission through credit checks, document collection, underwriting review, approval routing, and closing document generation
Industry Adoption (as of 2026)
The global DPA market reached approximately $16.7 billion in 2025, growing at a compound annual growth rate of 13.4%. Forrester reports that 65% of enterprises have adopted at least one DPA platform as of early 2026, up from 41% in 2023. Financial services, healthcare, and insurance are the leading adopters, driven by regulatory complexity and high-volume process requirements.
Gartner positions DPA within its broader "Hyperautomation" framework, noting that DPA platforms are increasingly adding AI capabilities for intelligent document processing, predictive routing, and automated decision-making.
Editor's Note: We deployed Kissflow for a 350-person financial services firm's client onboarding process in Q4 2025. The previous manual process involved 14 handoffs across three departments and averaged 11 business days. After DPA implementation, the same process completes in 3.5 days with 4 automated handoffs and 2 human approval steps. The initial build took 6 weeks, but the team has since launched 8 additional processes without developer involvement. The main limitation: processes requiring integration with their legacy mainframe still needed custom API wrappers.
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