Digital Business Automation (DBA) Reference Architecture and Process Steps

Digital Business Automation (DBA) enables organizations to streamline participation in business processes, automatically execute repeatable decisions, and provide users with the ability to edit and modify the business logic embedded in those processes, thereby improving operations.

DBA projects also aim to make documentation easy to store and retrieve, digitize document content (e.g., optical character recognition, OCR), and use software robots to automate data entry, commonly referred to as robotic process automation (RPA).

Process

Through an integrated automation platform, Digital Business Automation (DBA) improves how knowledge workers and other business users perform daily tasks. Organizations can benefit from implementing all DBA functions, but they do not need to adopt every capability at once. Many enterprises handle business entities such as loans, claims, orders, shipments, payments, or quotations, so the DBA story starts with the workflow concept.

Step 1 – A workflow is an organized series of industrial activities or management tasks that can be completed in seconds or over an extended period. In this context, workflows often span days or weeks, and for case work they may extend for years. Workflow management must provide persistence for long‑running processes so the organization knows what has been completed and who is handling each task. Real‑time workflow status is presented to users and managers via dashboards or portals, and custom forms can capture and display business data related to process execution.

Step 2 – To complete certain tasks, users may need to access documents and information stored and managed in an enterprise content management platform. The lifecycle of content benefits from explicit workflow governance, creating a bidirectional connection between workflow management and content management.

Step 3 – Enterprise content management platforms typically import and export data in conjunction with other content repositories. All DBA functions query or update data in the source‑of‑record (SoR) systems.

Step 4 – When digital or structured forms are unavailable, data‑capture technologies extract information from documents. These technologies include OCR, AI‑driven language understanding, document layout recognition, barcodes or QR codes, and signatures. Data capture can operate on unstructured content from fax, scans, images, email, mobile devices, or document repositories.

Step 5 – In addition to information residing in the content management system, workflows often interact directly—or preferably—through enterprise service bus (ESB) or API‑managed transformation and connectivity capabilities with other enterprise systems and applications, performing extract‑transform‑load (ETL) operations.

Step 6 – Workflows can invoke a special class of applications called decision services. Decision services implement business rules or events created, managed, maintained, and deployed in a decision‑management platform.

Step 7 – Workflows can call and orchestrate robots that perform tasks traditionally handled by human operators, such as entering data into third‑party user interfaces. Conversely, robots can be invoked by workflows to extract data from external applications or documents.

Step 8 – By invoking complex and frequently changing business logic implemented as decision services within the decision‑management capability, robots become smarter and easier to maintain.

Step 9 – Robots can automate direct interaction with enterprise applications without requiring APIs.

Step 10 – Capture capabilities can leverage robots to update other systems with structured data extracted from documents. Robots can also call reusable MetaBots to extract required data from unstructured content during task execution.

Step 11 – Decision services are intended to be called by other enterprise applications that follow service‑oriented architecture (SOA) principles, such as REST services.

Step 12 – Each DBA function can publish events to operational intelligence features, which include scalable storage and the ability to create dashboards that display real‑time business‑level key performance indicators (KPIs).

Functional Requirements

Design and manage end‑to‑end workflows: model, automate, modify, monitor, and optimize core business processes to improve consistency, productivity, and straight‑through processing.

Share and manage enterprise content: provide secure, compliant management of all content types, enable instant access, easily connect content to digital business applications, and ensure governance.

Use business rules to automate decisions: capture, automate, and manage business rules for rapid adaptation to change, improved decision consistency, auditability, and real‑time detection.

Use robots to automate manual tasks: record and automatically execute repetitive human tasks, eliminating copy‑paste and data‑entry errors while freeing staff for higher‑value work.

Capture and extract data from content: digitize business documents while extracting, storing, and understanding critical data, reducing manual entry, improving efficiency, and automatically deriving insights from unstructured data.

Original source: IBM Cloud Garage DBA Reference Architecture

Article source: IntelligentX Publication

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