5 Top Reasons Digital Transformation Will Fail Without OCR Software

The vast majority of digital transformation projects at the enterprise level are either not delivering on their full expectations or are failing altogether. And while there is often a complex combination of factors contributing to these failures – from a lack of appropriate skills and technology to not getting executive buy-in – there is one technology that plays a critical underlying role in companies’ ability to fully complete the digital transformation journey: Optical Character Recognition (OCR).

What is OCR?

OCR software allows for the conversion of images, handwritten or printed text, scanned documents, and embedded charts and tables into machine readable text. The digitization of organizational data is a precursor to digital transformation, allowing data to be utilized for analytics. The first step toward digitization is ensuring that content is in a format that can be easily accessed and processed.

The fact that most organizational data is unstructured suggests that too many companies are either missing this crucial first step or are using outdated OCR technology, which has limitations on its ability to convert mixed-format content.

Here are five top reasons digital transformation cannot succeed without state-of-the-art optical character recognition software.

1. OCR fuels data analytics

One of the most revealing sources of corporate insights is a company’s data – the vast stores of organizational information, both current and historical, structured and unstructured, that contain hidden patterns, trends, customer preferences, and other intelligence that can help executives make informed business decisions.

These data stores encompass huge amounts of information – far too great for manual processing. And it’s the very size of these data stores that gives them their statistical power: the more data that is included, the greater the accuracy and potential for hidden insights. But for many companies, this potential is locked in paper and other unstructured formats that cannot be accessed for machine processing. Enterprise-grade OCR technology accurately unlocks inaccessible data, converting previously unusable images into fully-searchable, readily analyzed text-based documents.

2. OCR paves the way to RPA

Another great promise of digital transformation that has yet to be truly realized is robotic process automation (RPA). RPA is the automation of rules-based business operations, using software instead of people to perform specific defined tasks. The integration of RPA can help businesses to streamline operations and reduce costs, as well as free up employees to perform more complex work that can drive greater business value. But like data analytics, the success of RPA initiatives is contingent upon having clean, accessible data from which machines can both learn and run processes. As such, reaping the benefits of RPA hinges upon effective OCR.

3. OCR identifies regulatory risk

The potential for data misuse and growing cybercrime risks that are inherent to the digital landscape have given rise to a slew of regulations aimed at safeguarding sensitive data such as personally identifiable information (PII). These include recent laws like GDPR and the California Consumer Privacy Act.

While the potential benefits of digitizing all of one’s content are huge, the storage of such vast amounts of digitized customer data does indeed carry regulatory risks. In order to reduce risk exposure, companies must take every possible step to identify sources of PII, and other sensitive data, and protect it accordingly. Failure to do so could result in hefty fines and irreparable brand damage. But before an organization can take steps to protect data affected by compliance regulations, it has to know it’s there – hence the need to illuminate so-called ‘dark data’ using OCR technology.

4. OCR accelerates innovation

Another thing that’s often hidden within unstructured data formats are little clues that can reveal new business lines, products and services, and that can reduce the research and development costs of bringing new initiatives to market. For example, an analysis by McKinsey estimated that the U.S. health-care system could see $100-billion in annual gains in part by better leveraging and integrating data from previous and existing clinical drug trials to speed up the development of new products. From banking to insurance, there are countless examples and opportunities across industries where data can be exploited to identify customer needs, or unexplored applications for existing products or services, and accelerate these new offerings. Of course, this can only happen if all related data has been digitized, including the conversion of inaccessible formats using OCR.

5. OCR improves customer experiences

Access to a single source of customer data has been the standard for some time now, but often that single source is incomplete. If a customer’s journey began with an in-branch or in-person paper application, or a transcribed phone conversation, then there’s a good chance that not all of the information contained therein would have made it into the database. It could be that some pertinent detail is left inaccessible to other branches or phone representatives, should that customer later seek a new product or support via a different channel. By making OCR a standard step in developing unified customer records, businesses can seamlessly ensure that employees have every possible tool to deliver the best customer experience at every interaction.

Wrap up

Companies will only be able to realize the many benefits of becoming a fully digital organization if they set themselves up to leverage every aspect of the data in their possession. While some of the digital data they possess may already be part of their decision-making process, a great deal of it is likely inaccessible. As a result, completing the digital transformation journey hinges on this first critical step: ensuring that all content is uniformly accessible by transforming any unreadable content into searchable text-based documents.