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Digital Process Automation (DPA)

Updated: July 18, 2024

What is digital process automation?

Digital process automation (DPA) is the strategic implementation of technology to automate business processes. It leverages digital tools to automate manual tasks, integrate disparate systems, and orchestrate workflows across departments.

For instance, DPA can automate tasks like data entry, approval processes, and report generation. This eliminates human error and frees up employees from time-consuming, repetitive work.

DPA aims to improve efficiency, accuracy, and compliance within an organization. Automating repetitive tasks frees employees to focus on higher-value activities. DPA also streamlines communication and data flow, leading to faster turnaround times and improved decision-making.

Why is digital process automation important?

Digital process automation (DPA) is rapidly becoming essential for businesses seeking to optimize operations and decision-making. Automating repetitive tasks across departments, DPA eliminates bottlenecks and streamlines workflows, significantly improving efficiency and productivity.

32% of organizations identified ‘accelerating digital transformation’ as their primary reason for emphasizing process optimization and automation, while 37% anticipated it would be their main driver in the future.

This translates into faster turnaround times, increased output, and the reallocation of valuable human resources towards higher-level activities. Additionally, DPA minimizes human error in data entry and task execution, ensuring greater accuracy and reliability within business processes.

Most importantly, the data collected through automation empowers data-driven decision-making. Real-time insights facilitate informed choices, allowing businesses to adapt quickly and gain a competitive edge in today’s dynamic market.

What are the objectives of digital process automation?

Digital process automation (DPA) is critical in driving digital transformation. Its goals encompass a range of objectives and impact business performance, operational resilience, and strategic direction. Here’s a breakdown of each:

Business objectives

  • Cost reduction: Automating repetitive tasks minimizes labor costs associated with manual data entry, approvals, and report generation. Streamlining workflows also reduces operational overhead.
  • Revenue growth: Improved efficiency through DPA translates to faster turnaround times, enabling businesses to handle more projects or serve more customers. This directly translates to revenue growth.
  • Enhanced customer experience: Streamlined workflows and reduced errors lead to faster response times and improved service delivery, ultimately enhancing customer satisfaction and loyalty.

Operational goals

  • Increased efficiency: DPA eliminates bottlenecks and simplifies processes, leading to faster completion times and higher output. Resources are better utilized, boosting overall productivity.
  • Improved accuracy: Automation minimizes human error in data entry and task execution, ensuring greater accuracy and consistency in business processes. This leads to reliable data for informed decision-making.
  • Enhanced compliance: DPA can automate regulatory compliance checks and reporting, ensuring adherence to industry standards and regulations.

Strategic aims

  • Increased agility: Streamlined processes through automation allow businesses to adapt quickly to changing market conditions or customer demands. This facilitates a more agile and responsive organization.
  • Data-driven decision-making: DPA optimizes collecting and analyzing real-time data from automated processes. These data insights enable informed strategic decisions and improved business performance.
  • Employee empowerment: DPA frees employees from repetitive tasks, allowing them to focus on higher-value activities that require creativity, critical thinking, and strategic planning.

Who’s involved in digital process automation?

Digital business automation (DPA) within digital transformation requires a collaborative effort from various internal and external stakeholders. Here’s a breakdown of the key players:

Internal stakeholders

  • Executive leadership: CEOs, CFOs, and COOs play a crucial role in championing the vision for DPA, securing budget allocation, and fostering a culture of digital adoption within the organization.
  • Business process owners: These individuals (department heads, managers) have a deep understanding of existing processes and are responsible for identifying areas for automation and ensuring alignment with business objectives.
  • IT department: IT professionals are vital in selecting, implementing, and maintaining the DPA tools and ensuring their integration with existing systems.
  • End-users: Employees across different departments who the automation will directly impact. Their input and training are crucial for successful adoption.

External stakeholders

  • Technology vendors: These companies provide the software tools and platforms that enable digital process automation. It is vital to select the right vendor based on business needs.
  • Consultants: Consulting firms can provide expertise in identifying automation opportunities, selecting and implementing DPA solutions, and change management strategies for successful user adoption.
  • Investors: For companies seeking external funding, demonstrating a clear strategy for DPA and its potential impact on efficiency and profitability can be crucial to secure investment.

What is required for successful digital process automation?

Successful digital process automation requires a focused approach in several key areas. The key areas include:

Strategic alignment and planning

This foundational step involves securing strong leadership buy-in for DPA. Leaders must champion the vision, dedicate resources, and align DPA goals with the business strategy. Effective communication with all internal (employees across departments) and external (vendors, consultants) is crucial. This ensures everyone understands the “why” and “how” of DPA, breeding collaboration and buy-in throughout the process.

Process optimization before automation

Simply automating inefficient processes can amplify inefficiencies. Therefore, a thorough analysis of existing workflows is vital. This involves identifying processes ripe for automation, streamlining them for optimal efficiency, and ensuring data accuracy. Clean and consistent data fuel successful automation; dirty data leads to unreliable outcomes.

Change management and user adoption

While automation streamlines tasks, it can also disrupt work habits. A well-defined change management strategy is essential for user adoption. This includes providing employees with clear communication, comprehensive training on the new DPA tools, and ongoing support. Addressing concerns, fostering a culture of learning, and highlighting the benefits of DPA encourages user acceptance and maximizes the return on investment in automation technologies.

Why does digital process automation fail?

Digital process automation (DPA) holds immense promise for streamlining workflows and boosting efficiency. However, even the most well-intentioned DPA projects can fall short.

According to a study by Ernst & Young, 30% to 50% of robotic process automation projects fail globally. 

Here’s a look at some of the major reasons why DPA initiatives might struggle:

Overemphasis on technology over strategy

One significant reason for DPA failures is overemphasizing technology over strategic alignment. Organizations may prioritize adopting the latest automation tools without first aligning them with broader business objectives. This lack of strategic integration can lead to disjointed processes, missed opportunities for efficiency gains, and difficulty demonstrating ROI.

Complexity and scalability challenges

DPA initiatives often struggle with complexity and scalability challenges. As organizations scale automation efforts across departments or functions, they encounter issues related to integrating existing systems, data management complexities, and maintaining consistent performance. Without a scalable architecture and robust growth planning, DPA projects can become unwieldy and unsustainable.

Insufficient governance and oversight

Another critical factor contributing to DPA failures is insufficient governance and oversight. Without clear governance frameworks and effective oversight, organizations may face issues such as inconsistent implementation practices, compliance risks, and inadequate resource allocation. Lack of governance can result in project delays, budget overruns, and failure to achieve the desired outcomes from automation initiatives.

Digital process automation use cases

Digital process automation (DPA) isn’t a one-size-fits-all solution. Its power lies in its adaptability to various business scenarios.

Here are three examples showcasing how DPA streamlines workflows and boosts efficiency across different departments:

Financial industry

Scenario

Imagine a bank traditionally onboarding new customers through a paper-filled process. Account applications, verification checks, and KYC (Know Your Customer) procedures were manual, leading to delays and frustrated customers.

Method

The bank implemented DPA tools to automate the customer onboarding journey. Online forms streamlined data collection, while DPA software integrated with credit bureaus and other verification systems for faster checks. 

Outcome 

The bank significantly reduced onboarding time, improving customer experience and satisfaction. DPA also minimized errors and freed up staff to focus on more complex customer needs.

Supply chain

Scenario

Imagine a manufacturing company grappling with a mountain of paper invoices from multiple suppliers. Manual data entry, verification, and approval processes were time-consuming and prone to errors.

Method

The company adopted DPA software with intelligent character recognition (ICR) technology. Invoices were scanned electronically, and ICR technology extracted data for automatic population into the system. 

Outcome

DPA streamlined invoice processing, significantly reducing turnaround times and improving cash flow management. The automation also minimized errors and enabled data-driven insights into supplier performance and spending patterns.

Marketing teams

Scenario

Think about a marketing team struggling with manual processes for creating and approving marketing materials. Content creation, version control, and approval cycles were slow and cumbersome.

Method

The team implemented a DPA solution with a centralized content management system. Automated workflows facilitated collaboration, allowing team members to seamlessly access, edit, and share content.

Outcome

DPA boosted productivity and agility within the marketing team. Faster content creation and approval cycles allowed them to capitalize on marketing opportunities more effectively.

People also asked

What is the difference between DPA and RPA?

DPA (Digital Process Automation): DPA focuses on automating end-to-end business processes that involve complex workflows and decision-making. It often includes integrating multiple systems and applications to streamline operations and improve efficiency. DPA solutions are designed to handle more sophisticated processes beyond simple repetitive tasks.

RPA (Robotic Process Automation): RPA, on the other hand, specifically automates repetitive, rules-based tasks that are typically manual and time-consuming. RPA robots mimic human actions to interact with software systems and perform tasks such as data entry, form processing, and transaction processing. RPA is often used for tasks that are high in volume, repetitive, and prone to human error.

What is the difference between DPA and BPM?

DPA (Digital Process Automation): DPA focuses on automating and optimizing specific business processes through digital technology. It typically involves integrating various systems, applying business rules, and orchestrating workflows to improve efficiency and reduce manual intervention.

BPM (Business Process Management): BPM encompasses a broader approach that includes designing, modeling, executing, monitoring, and optimizing business processes. BPM can involve both manual and automated processes, aiming to improve overall organizational performance, agility, and responsiveness to customer needs. DPA is often considered a subset of BPM, focusing more narrowly on the automation aspect.