No Hyperautomation Without RPA
“Hyperautomation has shifted from an option to a condition of survival,” said Fabrizio Biscotti, research vice president at Gartner. “Organizations will require more IT and business process automation as they are forced to accelerate digital transformation plans in a post-COVID-19, digital-first world.” This is why Gartner forecasts the worldwide hyperautomation-enabling software market to reach $532.4 billion this year. Given this development, it is also important for companies to take a serious look at RPA.
According to Gartner's definition, “hyperautomation is an approach that enables organizations to rapidly identify, vet and automate as many processes as possible using technology, such as robotic process automation (RPA), low-code application platforms (LCAP), artificial intelligence (AI) and virtual assistants.” But if there is no hyperautomation without RPA, where should you start?
First steps to RPA
Unless you occupy the C-Suite of your organization and are responsible for long-term strategic planning, you will need to find an executive sponsor or sponsors to assign your exploration of RPA. Look to the leaders of the Operations, Logistics, Innovation and Strategic Support teams you work with as primary stakeholders. You may need additional resources assigned as part of a project team whose members should represent expertise from different areas of the organization. If a project team is not possible, ask leaders to identify Subject Matter Experts (SME) from those areas to answer questions as you explore options.
Once your project team is established, begin by examining the current capabilities of your business. A key to the success of implementing RPA is to look for quick wins in current business processes. Consult your company’s Standard Operations Procedures (SOPs) for the most current approved business process documentation that describes activities across business units. Defining the scope of work is essential.
Here are some questions to consider in choosing where to start with the implementation of RPA:
- How many independent business processes exist?
- Which processes take the most time and cost the company the most in materials and employee resources?
- Does current documentation provide an accurate picture of how business processes truly happen?
- What software solutions are used by your company? How are they integrated?
- Which business processes are highly repetitive and best suited for automation?
- Which processes could benefit most from intelligent document capture and RPA?
- How would operations be impacted by RPA implementation in the short term?
Ideally, the first process to move to RPA should be able to be done in a sprint and tested for a few weeks, not months. Your analysis can act as a starting point for scheduling onboarding of other processes and business units to RPA in the future.
Use cases for RPA
Besides building a key foundation for hyperautomation, RPA brings some important short-term benefits. For example, it allows businesses to automate a recurring, manual process so that building and maintaining the process is easy and cost-effective. Processes that are repetitive, predictive, rule-based, have low exception rates and high volumes and are mature or stable are best suited for RPA consideration.
At a basic level, RPA can be used for manual processes such as “copy and paste” functionality, filling in data to populate a spreadsheet or running reports to post in a shared drive. Most likely, almost every department has tasks they do daily that require this basic functionality. Therefore, looking at deploying RPA pervasively throughout an organization is optimal.
Typical use cases for starting RPA projects include finance, accounts payable, customer or employee onboarding, insurance claims, processing loans, higher education transcripts and managing mailrooms, among others. Most organizations with a high volume of high-value documents that are used in repetitive processes are prime candidates for using an intelligent capture solution that feeds into an RPA solution. Additional and more specific use cases can be found here with 68 examples!
Mind the ROI and face the future
Without a look at ROI and taking a holistic hyperautomation approach of using multiple technologies, RPA initiatives are often doomed to fail sooner or later. RPA alone usually doesn’t result in success without using other technologies, such as intelligent document processing (IDP), AI, processing mining and others. IDP is a natural first step in the process to uncover and make data accessible. With the right data in a structured format, RPA tools will have a comprehensive dataset to deliver the best outcomes. IDP solutions route data into RPA systems, which then export data into other applications, such as business intelligence apps, ERPs, CRMs, workflows and other line of business systems.
Understanding your Key Performance Indicators (KPIs) will help you discover whether, for example, you need to measure cost savings in terms of headcount or perhaps what happened when you didn’t pay an invoice on time, resulting in fines. Or, do you need to survey your employees on if they prefer doing higher level, problem-solving and more creative work without doing mundane manual tasks? What is the cost of an audit and the preparation time versus a robot running a report and printing out all documentation within minutes or hours? Typically, as mentioned before, labor costs and time savings are the easiest to quantify.
After you have gained the first results, it is time to take the data you have gathered on the benefits of RPA tools and apply them to a comprehensive plan for the future of your business, focusing on hyperautomation as a long-term goal. But as this is an even bigger project, don’t forget that a change management strategy is necessary for employees to embrace and welcome new technology. Incorporating innovation and technology changes into your culture takes time and understanding. But looking at the benefits hyperautomation can bring to your company, it will definitely be worth the effort.
APIs: Their Role in Intelligent Document Processing Software
The ongoing American labor shortage has led businesses in a multitude of different industries to seek out ways to optimize productivity and streamline processes that are traditionally labor-intensive. While several such technologies are available, one of the most powerful is intelligent document processing (IDP).
Intelligent document processing applications facilitate end-to-end intelligent automation. These technologies accurately capture and extract data from documents and deliver it to a company's various systems of record, databases or other downstream applications.
Although IDP represents the first step to automation and business productivity, these solutions cannot function as seamlessly without application programming interfaces (APIs).
In this exploration of APIs, we examine what application programming interfaces are, their benefits and their role in next-generation business optimization.
What Are APIs?
An application programming interface can best be described as a "software intermediary." In simple terms, APIs allow applications to communicate and share information. When you use applications on your phone, tablet, or desktop, these applications communicate with your device's software via APIs.
There are a few different API protocols and architectures. These protocols include specific rules that outline which types of commands and data can be processed by the API. The most common API protocols include SOAP, JSON-RPC and REST.
Another more generalized category of application programming interfaces is "Web APIs." These APIs are accessible using the standard HTTP protocol. There are several sub-types of web APIs, which include:
- Open APIs
- Closed APIs
- Internal APIs
- Partner APIs
- Composite APIs
Open APIs vs. Closed APIs
Let’s focus on Open and Closed APIs. Open APIs are the type of application programming interface used to facilitate communication between intelligent document processing solutions and other software.
Open APIs are also referred to as public APIs or external APIs. These types of application programming interfaces are available to outside users and developers. Not only are open APIs available to third parties, but they minimally interfere with those entities' ability to access the technology.
Some APIs in this category are 100% open. This designation means that users can access them by simply downloading the API from the developer's library. Other open APIs require users to register with the developer and obtain an API key.
In addition to open APIs, there is a class of application programming interfaces that are considered "closed." Closed application programming interfaces are internal APIs. These APIs are designed specifically for use within a company. Internal APIs allow various departments and teams to exchange information or share resources.
Why Are APIs Useful?
Application programming interfaces have become the preferred solution for developers who need to facilitate intercommunication between two pieces of software. Modern APIs offer a multitude of benefits when compared to traditional integrations or alternative interface solutions. Some of the most notable benefits include the following:
Preventing Data Silos
Data silos are one of the most significant barriers to data-driven decision-making. These silos are formed when organizations collect and store information using different software platforms that do not communicate and share data.
This situation is pervasive in large businesses and enterprises, as each department may use a different suite of software solutions. APIs enable various applications to communicate and exchange data. In turn, this eliminates data silos and allows businesses to better use all the information they gather.
Facilitating Inter-app Communication
The primary function of APIs is that they facilitate inter-app communication. Developers create APIs designed to bridge the gap between a specific piece of their software and another type of software so clients can work more efficiently.
Although a separate API will be needed to form each inter-app communication pathway, installing these application programming interfaces is still far more efficient than creating manual integrations.
APIs make innovative technologies like intelligent document processing software more accessible to businesses that would otherwise be unable to leverage these solutions. Modern APIs also decrease the company's time to value and allow them to achieve a return on investment much faster.
Simple APIs do not just make life easier for technology adopters but developers as well. During a recent survey of developers, 52% of respondents stated that APIs accelerate innovation, and another 36% indicated they believe that these technologies create business value.
Offering Exceptional Functionality and Reliability
Application programming interfaces are incredibly reliable pieces of software that rarely experience breakages that are severe enough to cause long-term business disruptions. A survey published in February of 2022 revealed just how reliable APIs have been for major organizations.
Some 60.4% of organizations using external APIs state that their application programming interfaces do not malfunction "frequently enough to matter." Another 20.9% of respondents stated that their APIs only experienced one breakage monthly.
APIs are critical to the function of various applications, including intelligent document processing solutions. Fortunately, the above figures demonstrate that external APIs have exceptional reliability. Cumulatively, 81.3% of respondents experience API breakages monthly or less frequently.
APIs and IDP: What's the Connection?
Application programming interfaces facilitate seamless and reliable communication between an organization's external applications and its intelligent document processing software. However, APIs not only enable these solutions to communicate, but they also allow for true, real-time integration. What does this mean exactly?
Once an organization uses a developer's APIs to integrate their applications with IDP software, businesses can obtain actionable data and easily use it with other systems. Ultimately, once end users can leverage their data, they can make faster, better decisions and help improve customer experiences. Additionally, real-time integration via APIs decreases an organization's time to value and yields a better ROI.
Tasks that employees can perform following an IDP and external application integrations include:
- Data extraction
- Data structuring and classification
- Digitization of physical documents
- Complete OCR
However, a robust API, such as Ephesoft Transact's Open API-Compliant web services, is required in order to achieve high-level reliability and real-time integrations. Schedule a free trial if you are eager to learn more about Ephesoft's intelligent document processing technologies or how our Transact can connect with your existing systems.
What are Accuracy Rates in IDP?
Reflection on data extraction accuracy stats and actionable take-aways
There is a lot of debate and hype about the accuracy of intelligent document processing (IDP) solutions. I am sure you’ve seen claims boasting 80%, 90% and even 100% accuracy rates and everything in-between. The important question to ask here is, what does ’accuracy’ in this context actually mean?
Accuracy Rates Might Be Different Than What You Think
You guessed it, accuracy rates are not created equal. There is an important distinction to make between ‘machine accuracy’ and ‘machine + human-in-the-loop (HITL) accuracy’ which many people are not considering when assessing an IDP solution. In my experience, most people assume the advertised accuracy rates are achieved by the machine alone – yet, this is rarely the case. Let’s take a look at why exception handling by humans is, in fact, not only inevitable in almost all cases, but actually a critical step in the process.
I would like you to consider all of the documents entering your organization – are they all in legible machine print with no smudges, stains, missing words and other errors? Are they all from the same vendor, using the same format and the same language? If the answer was yes to all, 100% accuracy is technically possible. However, this does not sound like a likely scenario for enterprises and government organizations that are processing thousands or millions of documents every year. Does it? The moment you introduce just one variation, 100% accuracy achieved by the machine alone is not realistic for a high volume of documents.
Let’s take invoices for example. They come in many shapes and forms and from many, often varying, vendors. Can you set up your IDP solution to process known invoices and achieve high accuracy rates? Yes, absolutely if you have a good, customizable solution. But what if you get an invoice from a new vendor using complex tables or if one of your existing vendors changes up their invoice format? The accuracy rate will be impacted.
Human-in-the-loop (HITL)
So, what is needed to address this issue? A human-in-the-loop. Leading IDP systems, like Ephesoft, use business tolerance rules or confidence scores when extracting data. For example, if our system can’t detect a letter or other mishap, it will get kicked out of the touchless process and trigger an exception alert for human review. This keeps the user in control and assures high accuracy rates as an end result. In addition, Ephesoft Transact allows users to improve the automated data extraction results over time. Ephesoft makes this process intuitive and easy for the user.
Improvements Over Time
With the help of AI, machines are certainly improving to accommodate variations and errors in documents and I am sure we’ll see significant progress in the near future. However, as it stands today, a 100% accuracy rate requires a human-in-the-loop (unless you only have perfect documents). The fact is, the accuracy rate will depend on your specific documents and how flexible and adaptable your IDP solution is to get the best results for your particular use case(s).
See It to Believe It
My recommendation is to put your IDP solution to the test with sample documents and see the results rather than relying on advertised accuracy stats. You’ll not only see the results firsthand but also experience how it is to work with the solution provider, which should also be an important criterion in your selection process.
The Inner Workings of Automation and Accuracy
Another interesting dimension when discussing accuracy specific to IDP is the various stages a document goes through during the data extraction process each of which can introduce accuracy failures:
1) Image Processing – During this stage the system normalizes, cleans up, rotates and makes other adjustments to the image which is critical to how well the image can be read. If there is a problem at this point, accuracy will be impacted down the line. Ephesoft leverages best-in-class image cleanup technologies achieving the most optimal results.
2) Document Classification – During this stage, the document type entering the process is identified; it is also commonly called “indexing.” This is where the software detects if the document is, for example, a bank statement, tax form, identification card, invoice or any other document type. Be aware that there are significant differences in classification capabilities across IDP vendors. Ephesoft Transact is recognized to provide the most advanced classification methodologies with a user-trainable model for ML search classification and separation, pre-trained ML classification models, key-value classification and HITL classification review and model updates.
3) Data Extraction – In this stage the rubber meets the road. The system pulls the data out of the previously cleaned-up and classified document. Here is where you can measure the true machine accuracy. During your assessment make sure to look at real life and a good variety of documents for your specific use case(s). As mentioned above, human-in-the-loop processes are important here to address exceptions and make system improvements over time. Note that some IDP providers send the data abroad to substitute their automated data extraction with manual data entry behind the scenes. For everybody who has documents with private information, this might introduce compliance and data privacy issues.
In Ephesoft Transact, the user can look at any of their documents to determine whether the information was correct. The system is color-coded to help the user easily identify if there are any documents that did not get accurately pulled from the identified fields. The output of the data is influenced by the previous image processing step. Behind the scenes, the application is programmed to the customer’s business rules and tolerance or confidence levels. Based on the level, the customer can set it up to always have a HITL or push the data straight-through if there are no potential errors detected.
Take-away
While accuracy rates are essential for the evaluation of your IDP system, they are not as straightforward as you might think. Make sure to consider the different definitions of accuracy and understand what they translate to for your specific needs both in the short and long term.
If you like to see your documents in action, send us your sample documents and we’ll process them at no cost to you! Contact us here to get started.
