IDP Obstacles and How to Overcome Them

IDP Obstacles and How to Overcome Them

by Sujith Parakkunnath, on October 6, 2022 11:30:00 AM PDT

Recently, Gartner published the report Hype Cycle for Natural Language Technologies, 2022, that evaluated various natural language technologies (NLT). In this report, Intelligent Document Processing (IDP) is referred to as a technology that is increasingly important in creating operational efficiencies in business processes.

The report also mentions four IDP-related obstacles:

IDP industry is adolescent
An IDP partner can be difficult to identify
IDP has integration challenges
IDP, as an industry, bleeds into insights engine, RPA, and conversational AI

Facing these obstacles may not be a choice, but succumbing to them may be. These are relevant obstacles, but as a leader in the IDP space, it is Infrrd’s responsibility to address them, guide you to overcome them, and help you not only scale your business faster, but also make you more efficient and competitive. So, let us explore how a detailed analysis of these obstacles can shed some light to choose the right automation or right IDP solution for you.

The IDP Industry is Adolescent

IDP is considered by many a new industry, but actually, it is not so new. It is primarily transforming or bringing a paradigm shift to traditional document processing, such as legacy OCR-based extractions or the BPO-based manual extractions. Even though businesses are increasingly realizing that IDP is the best option to stay competitive and scale their business faster, IDP has still not taken off in a big way. And, that is the reason Gartner says this industry is in the Growth or Adolescent stage. However, the early IDP adopters of today will be the leaders in document processing when IDP reaches maturity.

Challenges in Identifying the Right Partner

As IDP is constantly evolving, it is crucial to choose the right IDP solution. Picking the wrong partner for automating business processes can be a detrimental move for your business. Some of the probable causes or reasons for picking the wrong partner may be as follows:

Choosing what you believe to be the ‘best’: When you make a choice based solely on brand reputation, things may go south real quick. For example, Sony or Samsung may be known for manufacturing the best electronics in the world, but when buying a smartphone for everyday use, would you go for a Sony or Samsung, or would you choose a Pixel Pro from Google, a company originally known for its search engine? Similarly, some IDP solutions work best with invoice processing but may not be very efficient with mortgage documents, and vice versa. It is important to check which company or product can work best for your business and use case.
Choosing a low-budget IDP solution: This is a fundamental mistake many businesses make. Don’t choose a vendor purely on budget. The low-cost automation solution might end up costing you way more after implementing and using it. If an IDP solution solves the problems of today and also can make day-to-day operations more efficient with time, it is likely to save you more business dollars in the long run. If you find such an IDP partner, increase your budget and choose the right solution.
Falling for the 'Great Start' trap: Several IDP solutions in the market initiate the automation process with vigor but lose their momentum midstream. If an IDP solution uses AI technologies and machine learning-based algorithms, it is important to evaluate – in great detail – the quality of data processing, which is primarily based on proprietary ML algorithms, and assess how effectively the system matures as the data extraction progresses.

Here are some useful insights in regards to selecting a good IDP partner:

Figure out your key complexity: Do not try to evaluate everything but rather focus on the most complex extraction needed for your documents. For example, if you are dealing with invoices that have tabular information, focus on how efficiently and effectively the IDP solution extracts data from tables.
Take a demo with the top players: There are many IDP vendors in the market. Do some research and shortlist the top three vendors based on your bandwidth. Ask for a demo with the shortlisted vendors and be sure that you ask them to show how the complex data point you identified, such as tables or handwritten text, is handled by the solution.
Try Before You Buy: After the initial evaluation, choose the best – or at the most – the top two solutions and use their trial versions if available to then conduct a proof of concept (POC) with the vendor. Ensure that all your critical and complex variations are discussed and tested thoroughly but also ensure to focus primarily on your critical requirements to keep the POC shorter, faster, and more effective.
Great start vs. great finish: During the trial, ensure that you do not fall into the “great start” trap. There are several template-based OCR solutions that solve simple problems quickly and provide the impression of a good start but they may fail to offer a good finish. Evaluate the extraction capabilities of the IDP solution to get a high-level understanding of how the IDP solution is designed, how AI-based technologies are implemented, and how superior their ML algorithms are.
Check references: Before signing any contract, check in with some existing customers to get references about the potential IDP vendor and gain insights into their experience using the solution.

For detailed information, check out our blog on evaluating an IDP partner.

Integration Challenges

Most of you may already be using an OCR solution or depending on BPOs for data extraction. However, looking at the scalability and efficiency perspectives for the future, you may have decided to choose better or more intelligent ways of processing data, say an IDP solution. One of the main advantages of an IDP solution is that it not only intelligently extracts data or makes predictions, but also helps classify, transform, and/or manipulate extracted data based on business requirements or priorities.

However, while adopting IDP, you may encounter a few integration challenges as follows:

Compatibility: The first question to ask is whether you want IDP as an extension of your existing solution or should it be an absolute replacement of the existing solution. If you decide to use IDP as an extension to complement your current solution, one of the significant issues can be compatibility with legacy systems. Perform relevant quality checks to address this challenge.
API: Most IDP solutions allow you to integrate with third-party systems through their APIs. However, if the APIs do not perform consistently or are of low quality, you might face connection errors often leading to integration issues. So, ensure the API quality - it should be secure, resilient, discoverable, robust, and consistent.
Out-Of-The-Box Connectors: Some IDP solutions offer connectors so that you can connect different systems without much support from a Tech or IT team. Good quality connectors reduce integration challenges to a large extent.
Geography: More than technical limitation, this is more of statutory compliance or limitation. Some businesses require their servers to be hosted within the country to meet statutory compliance or their own company policies. In such cases, you need to ensure your IDP solution offers cloud instances in your country.
Security Compliance: As a business, there may be mandatory requirements that your IT infrastructure team runs on any third-party solution. Ensure that the IDP solution meets the security requirements laid down by your company. For example, some businesses may not allow integration with any solution that is not ISO-compliant or SOC-compliant.

IDP Bleed into other implementations - Chatbot, Low-Code, RPA

IDP is often misunderstood as a solution that competes with AI-based automation technologies, such as a Chatbot, low-code implementations, or RPA. However, in reality, IDP is more of a booster for other implementations.

RPA, chatbots, and low-code platforms are a great start to help cut manual costs, reduce process times, and improve customer experience, but as business processes get increasingly complex, these technologies fall short of reaping higher efficiencies.

The reason these technologies fall short is due to their inability or lack of expertise in handling unstructured data, such as understanding an expense receipt handled by a chatbot, figuring out what is being shipped where from shipping instructions attached to an email message monitored by an RPA engine, or reading data from W2 forms from mortgage applications in a low-code platform. To solve these issues, manual processing will have to intervene to make sense of the documents received by these automation tools, and then feed them the data to complete the task. This means your automation journey is only halfway there.

IDP can complete this automation journey by complementing your existing investments in other automation technologies and further broadening the range of functions that can be automated.

Let’s look at how IDP integrates with other implementations:

Chatbot: Chatbots are designed to handle conversations in short bursts and make sense of programmed sentences. For example, a chatbot handles your expense management process. Here, you may need the user to take a picture of the expense receipt and upload it to the chatbot. Since these documents do not follow a fixed format, chatbots cannot easily extract information from these receipts such as the nature of the expense, amount, date of transaction and currency, etc. This is where an IDP receipt classification and extraction model can complement the chatbot by extracting the receipt information and making it available in a structured format. Once the chatbot has this information, it can further manage the process.
Low-code Platform: In the past, businesses spent months and millions of dollars working with system integrators to develop tools for handling various processes. Some of these business processes can now be handled by configuring process flows in these low-code platforms. But as these flows get more complex, they too will need to handle documents. With a complementing IDP platform, you will be able to automate data extraction from these uploaded documents and present it to the underwriters in a ready-to-use format.
RPA: This is one of the most widely used and deployed automation technologies that can deliver quick efficiency by automating simple manual tasks. Even though RPA tools have process automation capabilities, it usually depends on unstructured data being converted to structured format and delivered to them as CSV files. This is where IDP can come in handy. When RPA is integrated with an IDP platform, the RPA bot can send this document for understanding and receive a CSV file with all the relevant information. Based on this information, it can decide where to route this document and make other business decisions.

For detailed information, check out one of our earlier blogs on how IDP acts as a booster shot for RPA, Chatbot, and Low Code implementations.

Is your automation intelligent?

As discussed in the “Hype Cycle for Natural Language Technologies, 2022” report, IDP as a technology, is increasingly becoming important in creating operational efficiencies in business processes. Ensure you address the IDP obstacles effectively to choose the right solution for your business so that you not only scale faster but also make your business more efficient in a competitive market.

GARTNER and HYPE CYCLE are registered trademarks and service marks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Topics:Intelligent AutomationAI ReadinessIntelligent Document ProcessingMachine LearningIDP Insights

About this blog

AI can be a game-changer, but only if you know how to play the game. This blog is a practical guide to turning AI into real business value. Learn how to:

  • Make sense of complex documents and images.
  • Extract the data you need to drive intelligent process automation.
  • Apply AI to gain insights and knowledge from your business documents.

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