modernization and standardization

Modernization and standardization for nonprofits: How automation can streamline core finance functions

Only 47% of nonprofit organizations currently have the ability to automate their financial processes. Without innovative tools to identify and reduce potential issues, notify decision-makers, and plan a course of action, nonprofits are struggling to execute on projects and maintain client, donor, and employee satisfaction.

As automation is a broad term encompassing a variety of tools, it is important to note the most effective means of automating back-office operations. Many companies are utilizing artificial intelligence (AI) and robotic process automation (RPA) to achieve their finance goals. AI and machine learning aid nonprofits in their finance analytics, risk modelling, and expense reporting. RPA can be used to reduce the amount of manpower required to process accounting and finance department transactions. Both tools augment finance teams and help them process work faster and improve accuracy by removing human-error and tediousness.

As great as automation for financial operations sounds, the transition to a modernized back office can be difficult. Organizations must evaluate their needs and standardize their finance processes to build a solid infrastructure where automated tools can function properly. Leading nonprofits have recognized the good that automation can do for their finance teams and how this translates to employee empowerment.

Leading Organizations Are Implementing AI and RPA

Innovative tools like AI and RPA allow finance teams to free-up coveted resources that can be used elsewhere within the company, optimizing productivity and decreasing costs. Leaders are far more likely than Followers to implement AI and RPA functions within their finance operations (Figure 1).

AI and RPA in financial processes
Figure 1: Use of AI and RPA in Financial Processes
 

With many nonprofits still transitioning into the digital age, the ability to extract data from printed and typed documents is critical. Leaders have recognized the importance of automated scraping and data extraction tools and are 1.3x more likely to currently have these tools on hand. Additionally, there are many repetitive, rules-based financial processes, such as accounting calculations, financial planning and analysis, and reporting, that AI bots can speed up and make more accurate.

Automation Improves Productivity and Resource Allocation

Investing in innovative technology can solve many of the problems nonprofits face as a result of disjointed processes and outdated, labor-intensive systems. Leading nonprofits are specifically using automation to increase visibility and control, along with productivity (Figure 2).

Strategic Actions to Address Nonprofit Data Challenges
Strategic Actions to Address Nonprofit Data Challenges
 

Implementing real-time visibility into project management, cash-flow, and donation statuses along with advanced predictive measures, fueled by AI models, improves agility, and helps prevent disruptions. Updating data systems to establish these automated capabilities decreases downtime and promotes greater accessibility and productivity for all teams. Greater productivity stemming from fluid processes rather than disjointed ones results in better customer experiences, and people experiences for nonprofit staff.

Leaders are also optimizing processes to increase the impact they can deliver with available funding. Resource allocation is a large part of financial operations within nonprofit organizations. Solutions that include field service management and operational reporting tools aid in proper donation distribution both externally and internally. Top nonprofit organizations are also 2x more likely than Followers to work toward minimizing back-office costs and strengthening donor relationships.

Empowering Employees to Make Data-Driven Decisions

One widely held myth regarding AI and RPA is that they are used to replace human workers. The truth is in fact the opposite: Automation allows people in non-traditional data and engineering roles to take advantage of complicated models and machine learning algorithms by acting to augment their abilities. They can see into the future with predictive analytics and precisely examine certain operational procedures to determine areas for improvement. Automation doesn’t rid the workforce of administrative roles; it elevates people in those roles to a more advanced level where they can generate data-driven insights and provide expert knowledge to decision-makers.

Automating finance operations and eliminating document-based communication provides nonprofits with the solid infrastructure they need to succeed and better serve their communities. Innovative modeling capabilities allow organizations to scale their finance operations effectively and keep up with changing business environments. Incorporating these analytical capabilities opens the door for complex modeling and tactful, data-driven decisions, especially in times of great uncertainty.

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sarah

Sarah Gaffney

Sarah is a Market Insight Analyst on the Research Team at Aberdeen. In addition to building, launching, and monitoring Aberdeen’s research surveys, she analyzes survey data across a variety of fields and writes content pieces highlighting key findings. Sarah holds a Bachelor’s degree in Mathematics with a concentration in Statistics from Colby College.