Digital Process Automation (DPA) — Overview And Trends For IT

Digital process automation (DPA) tools are used to automate and optimize end-to-end business workflows that include IT operations, infrastructure, data warehousing, and more. By optimizing the full workflow, organizations can streamline processes that are critical to customers and daily operations.

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Digital process automation streamlines data for business orchestration

With so many ways to automate business processes —BPM, BPA, RPA— where does digital process automation (DPA) come in and how should organizations apply it? 

What is Digital Process Automation?

Digital process automation refers to the digitization and automation of recurring business processes. While this sounds similar to other automation practices, like business process automation or robotic process automation, DPA has several key differences.

Primarily, DPA focuses on automating systems and processes first, and then optimizing the end-to-end flow of information between business applications, systems, employees, and customers. In practice, DPA seeks to support the customer experience by ensuring employees and customers have access to real-time data. This is in contrast with robotic process automation, which looks to automate simple, rules-based tasks within a workflow, whereas DPA optimizes the entire end-to-end workflow.

Digital Process Automation vs. Business Process Management 

Market demands constantly shift, which means so do business requirements. To remain competitive, organizations are implementing a wide range of technologies and applications as part of their own digital transformation initiatives. Ironically, this often results in complexity, preventing organizations from achieving the efficiency and speed that they’re after.

In the ‘90s, organizations relied on business process management (BPM) tools to standardize business functions and reduce operational costs. Today, DPA emphasizes a customer-centric approach to digital transformation by moving away from traditional BPM practices that focus on cost-reduction, to instead focus on streamlining operations to provide a better customer experience.

Digital Process Automation vs. Business Process Automation

Starting in the 2000s, BPM tools were no longer enough and organizations began implementing business process automation (BPA) solutions to streamline operations. BPA involves the automation of repetitive tasks that otherwise require human intervention, such as employee onboarding, file transfers, back office processes, and more. However, BPA is also used not just to automate day-to-day business tasks but to achieve end-to-end orchestration across the enterprise.

Digital process automation, while closely similar, varies from BPA by optimizing communication between multiple tools and systems as well as employees and customers. Additionally, DPA looks to automate not just business functions but data management within the business to make information available in real-time for business users and customers alike.

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What Are Some Digital Process Automation Examples?

Digital process automation tools can be used to make data readily available for employees, so they can quickly and accurately provide solutions and services to customers. For example, many organizations configure user portals for customer service initiatives. DPA tools help ensure those systems are constantly updated with accurate information that customers can easily access.

By optimizing data and BI processes from end to end, DPA improves analytics and reporting to provide valuable insights that organizations can use to quickly innovate and improve operations. As a result, businesses can quickly adapt to changing market trends and customer demands.

Intelligent Digital Process Automation

DPA platforms don’t always offer intelligent automation capabilities. For example, many DPA tools do not provide machine learning for data analytics, which can be useful in optimizing workloads. However, DPA can be used to integrate artificial intelligence capabilities into end-to-end processes.

Additionally, DPA software cannot always integrate with legacy systems that don’t support APIs. In this case, a workload automation solution can be used to seamlessly integrate DPA solutions with aging infrastructure.

How to Successfully Implement DPA

Forrester’s recent report, “The Forrester Wave™: Software For Digital Process Automation For Deep Deployments, Q2 2019,” identifies DPA software vendors that can optimize a range of processes, including application development and delivery, so professionals can choose a provider based on their requirements.

Here are a few key capabilities you should look for when choosing digital process automation software:

Low-Code Development

The most prominent capability of powerful DPA software is the low-code assembly of complex processes. For example, some DPA platforms offer drag-and-drop workflow designers that enable users to quickly assemble workflows using prebuilt connecters. This makes it easy to manage data, dependencies, and business rules across endless applications and systems, drastically reducing time and resources spent writing custom scripts.

Real-Time Alerting 

To help manage operations and to streamline troubleshooting, DPA tools should proactively monitor workflow progress and, based on an organization’s needs, send alerts to the appropriate teams. Alerting functionality should also support auto-remediation for any workflow that overruns, underruns, displays exit codes, or is in danger of breaching an SLA.

End-to-End Integration

DPA software should enable IT to automate, monitor, and manage workflows across the enterprise, pulling together IT infrastructure, data warehouses, and business platforms. Whether through prebuilt connectors, native integrations, or via APIs, DPA software that can assemble integrations into end-to-end workflows will be able to provide businesses with endless opportunities to orchestrate and optimize its processes, operations, and customer experiences.

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Cassie Doheny was a contributor to IT Automation Without Boundaries, covering workload automation, data center automation, cloud management, and more.