7 Ways to Measure the ROI of Data Automation

7 Ways to Measure the ROI of Data Automation

November 30, 2024

Getting the buy-in of key decision-makers to invest in data automation software is a persistent yet universal challenge for digital transformation leaders across industries. Measuring and communicating the return on investment (ROI) of data automation software is hence an essential step in consolidating a successful business case to justify the expense.

Benefits of Data Automation

There are a variety of data automation tools available on the market, many of which deliver function-specific benefits based on their unique functionality. However, end-to-end data automation tools like fileAI now allow businesses to reap the benefits not only within the isolated scope of individual tasks, but also across workflows from end to end.

Intensely manual and tedious tasks like data entry can now easily be eliminated, with intelligent character recognition (ICR) technology negating the need for even handwritten documents to be keyed in manually. Furthermore, the AI-powered mapping of data has also enabled the complete digitalization of the process of transferring information from one legacy system to another. Equipped with machine learning modules, automation systems can also cross reference documents, matching and categorizing documents and information without human assistance.

Whilst time and cost savings are clear wins that businesses may achieve with data automation, there are a myriad of long-term enhancements that may be significant but not immediately apparent upon implementation. The following outlines some short and long term returns that businesses can expect when investing in data automation.

1. Increased Productivity

The implementation of data automation software can bring productivity gains that will be observed not only within one department, but multiple and oftentimes even across the business as a whole.

The reassignment of tedious and repetitious tasks to intelligent process automation (IPA) systems reduces instances of human error, enhances time efficiency and allows processing to be triggered in real-time, providing a consistently accurate view of the business’ financial health at all times.

Furthermore, features of market-leading data automation software like fileAI, such as in-chat document submissions via mobile app, or entirely customizable approval workflows also supercharge productivity by enhancing communication and encouraging collaboration. A significant return on implementing data automation is hence the improved ability to best allocate resources and maximize revenue generation.

2. Compliance and Audit

By replacing traditionally paperwork-heavy practices with entirely digitalized and automated workflows, a transparent and indisputable digital trail is made available for access and audit across multi-tiered workflows. With most businesses having a history of staggered implementation of purpose-specific legacy software, data sources are often disparate, hindering audit-readiness and complicating compliance reporting. By enabling one integrated database to act as the single “source of truth” across business functions, data can easily be consolidated for compliance reports, displacing the need to manually retrieve and compile data from multiple document sources.

Furthermore, as new regulations such as carbon emissions or diversity indicators become mandatory scopes of reporting, the flexibility of present-day IPA systems will also allow businesses to simply augment existing systems with new data fields without significant investments in future. As such, data automation systems, if implemented thoughtfully, can guarantee long term returns in demonstrating compliance, auditability and the efficient provision of documentation.

3. Data Management

With the considerable spectrum of functions available to intricately customize means through which data is to be ingested, processed, exported, and stored, data automation software empower businesses to elevate their data management capabilities across the workflows.The practice of manually handling sensitive data also presents avoidable risks to cyber security, access to data, and version control. End-to-end data automation software inherently mitigate such risks, eliminating all human-centric detriments to optimizing data management.

4. Scalability

With legacy systems primarily targeting only specific use cases, the significant accumulated implementation costs for any series of isolated solutions can easily become a deterrent in stakeholders’ willingness to support the expansion of automation capabilities. Furthermore, with the onboarding and training typically required for new software to be rolled out effectively, the time and effort required may aggravate reluctance to invest in such tools.

However this is not the case with the latest automation technologies. Systems once implemented can be easily replicated across use cases with similar flows, or easily tweaked to cater to a variety of contexts. This significantly reduces the time, costs and effort of scaling the adoption of automation solutions across organizations, functions, departments and even across affiliated businesses.

5. Employee Satisfaction

When an organization implements data automation software across tedious and manual tasks, employees are no longer weighted with the completion of administrative or operational tasks ad nauseam. Furthermore, leaders are empowered to reallocate both finances and manpower towards higher-value tasks, optimizing efficiency in resource allocation. By expanding the scope of upskilling opportunities, such movements not only benefit individual employees, empowering them with more valuable skills and task sets, but also increase the productivity of the organization as a whole.

6. Streamlined Process

From generating physical documents to coordinating the flow of documents between one stakeholder to the next, managing and enabling information transfer based workflows is traditionally a tedious process in and of itself.

With the capability of modern solutions to integrate with existing technologies, implementing data automation can not only replace pre-existing solutions, but improve inefficiencies without the necessity of additional training or familiarization of new tools.

Benefits of Data Automation

With data flows being natively integrated across workflows from the initial point of data ingestion to the final export destination, the implementation of data automation instantly improves both the accuracy and consistency of reporting.

When using traditionally manual methods of data entry, inconsistencies are expected to arise as a result of incompetence, negligence, disorganization or even instances of internal fraud. As such, incorporating automation software into key processes can help increase confidence in process-governance and audit-readiness by eliminating problems stemming from human error.

Beyond accuracy of the source data, analytics are now also available in real-time, providing an on-demand visualization of data with a variety of documentation consistently ready for production and downloading. This empowers leaders to achieve enhanced accuracy in forecasting at any point in time.

Connect with a fileAI financial automation expert

fileAI is a leading provider of AI automation solutions that leverage artificial intelligence to process any file end-to-end directly into any system without manual intervention. With a commitment to innovation and customer success, fileAI enables organizations across various sectors to unlock manpower stuck doing low-value tasks for higher value work.

7 Ways to Measure the ROI of Data Automation

Getting the buy-in of key decision-makers to invest in data automation software is a persistent yet universal challenge for digital transformation leaders across industries. Measuring and communicating the return on investment (ROI) of data automation software is hence an essential step in consolidating a successful business case to justify the expense.

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