When it comes to government deployment of automation and AI/ML, he often highlights high-level applications—whether it be to increase soldier performance on the battlefield, drive intelligence gathering or modernize citizen service delivery.
For this reason, it’s easy to miss a transformation underway in the “back offices” of the Department of Defense and civilian agencies, as adoption of RPA soars.
RPA directs a virtual software bot to mimic human actions in order to manually automate mundane, repetitive, and heavy tasks. Ideal automation candidates include processes that are highly standardized using electronic data inputs, such as streamlining data collection and processing, document management, identity verification, and automatically responding to information requests from citizens.
2021 Exploratory study UiPath found that 6 in 10 federal respondents—and half of the state respondents—view RPA technology as an essential building block for harnessing AI and machine learning, by speeding up data collection and improving data quality. why? For starters, RPA has the lowest cost of entry in the intelligent automation space and offers high rates of returns when implemented correctly.
RPA and the use of intelligent bots are proving to be of great importance to agencies seeking to automate the time-consuming, manual processes required to run a government agency. For agencies evaluating RPA, it is essential to first determine which processes are best suited for automation—a decision driven in large part by the impact on the amount of time, money, and frustration saved by using a new solution.
This article will detail how agencies at any level can identify the best applications for automation via RPA, as well as the key benefits that RPA provides.
Strategies for evaluating RPA candidates
When evaluating where RPA can have the greatest operational impact and impact on people, it is necessary to work through the backlog of candidate processes. In other words, before RPA technology development begins, comprehensive analysis, optimization, and standardization of potential automation. The selection of suitable candidates should not take place in a vacuum; Requires an understanding of the overall mission, business environment and IT systems. Given these considerations, the five strategies below can guide decision-makers toward the most effective candidates.
Is the process manual and repetitive?
Work best suited for RPA consists of repetitive manual processes that require the employee’s attention and involve following similar steps for each new piece of input. Processes that currently require person participation or supervision, such as data entry or personnel file processing, will benefit most from RPA, because process automation frees up employee time to do more important tasks.
Is the process repetitive or stressful?
Some operational processes need to happen monthly, some daily, and others on demand from thousands or millions of connected users. This consideration must be weighed against the burden of the operation.
Let’s take a look at a weekend report that takes four hours from an agency employee’s time to create each week, and compare it to year-end reports that take twenty hours to complete. Although year-end reporting is a more difficult task, weekend reporting is done more frequently, making it a higher priority candidate for RPA. Simpler but more repetitive process automation saves two hundred hours compared to the twenty hours consumed by the “larger” task.
Does the process use rules or templates?
AI powered RPA solutions Can Being able to accomplish complex decision making, but processes that follow a specific set of rules or instructions makes the most efficient use of intelligent automation. Even if the rules guiding the process are very complex—with branching paths of recommended next steps based on several different criteria for each input—a computer can internalize those rules far more efficiently than a human.
On the other hand, tasks that require a certain level of autonomy are more difficult to adequately approximate with a coded set of rules. Molded processes make for more meaningful applications of RPA, as AI can learn to perform complex analyzes of any inputs given the appropriate model from which to make sense of the data.
Does the process handle standard inputs and outputs?
Any operation that takes a standard type of data, such as a document, PDF, or spreadsheet, can be repeated by RPA trained to handle a particular static data format. Processes that accommodate many different formats, such as a mix of emails, paper receipts, and video recording, require more investment for automation. Standard output is also important – creating a file, recording information in the database, sending emails or updates on the network, and so on. Scanned physical documents can be converted through Natural Language Processing or Optical Character Recognition through automated processes to convert these documents into usable data.
How many business applications are involved?
The fewer business applications involved, the more efficient RPA can be out of the gate, as the AI only has to understand the inputs and outputs of a single program, and can interact with it directly. More advanced implementations can interconnect many applications and enable them to “talk to” each other, but this level of investment is most beneficial as the return on investment is expected to be high.
The benefits of RPA today and tomorrow
At the micro level, an illustrative RPA use case can be found with the Air Force’s Installation and Mission Support Center, which has had significant challenges processing Freedom of Information Act requests and responding to notification letters. Managers were overwhelmed with a backlog of hundreds of issues that took their time away from higher-value tasks.
The FOIA process has caused significant resource leakage due to the procrastinating nature of the existing process, thus it is an ideal application of RPA to eliminate the fault-prone process and strategically reorganize the existing resources. By replacing tedious manual tasks with automation, users can narrow their time investment to make critical decisions and review the work performed by intelligent “bots.”
The result: a 30% reduction in backlog and a significant increase in fee generation on requests answered in a timely manner. It also reduced processing time by 88% and increased accuracy to 99.9%. The implementation of RPA has resulted in an overall reduction in employee workload and 2,034 full-time hours of work from the government have been reallocated to better use of time.
What’s next for RPA? As more agencies achieve tangible results, there will be a desire to continue the journey to smarter automation. Robotic process automation is already evolving far beyond the rule-based chatbots often used to support customers and citizens. Today’s applications benefit from intelligent automation (IA), provided by Brookings Identifies As “…a type of RPA that includes AI, ML, or Natural Language Processing (NLP). When applied correctly, RPA technology and intelligent automation make for fewer stressed employees, more accurate and faster internal operations, and a more capable organization in the long run.”
Mark Hogenmiller is Chief Transformation Officer at Aeyon, a company that provides management consulting and data analytics services to the federal government.
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