Blog Post
OCR is a widely used text-recognition software that will continue growing in use. In 2022, Grand View Research valued the global OCR market at $10.65 billion, with a compound annual growth rate of 15.4% until 2030. The market’s key stakeholders include familiar brands like Google, Microsoft, IBM, and Adobe.
This burgeoning usage spans multiple industries and sectors. According to Transparency Market Research, the deployment of OCR can be sub-divided into distinct categories, including transport and logistics, manufacturing, retail, and IT/telecoms, among others.
OCR (optical character recognition, or text recognition) software aims to enhance data accuracy and processing efficiency by scanning various documents, extracting the information, and translating it into a consistent, editable, machine-encoded format.
Document Types OCR Can Scan and Extract
Trade documents, legal contracts, photographs, superimposed subtitles, or any other unstructured information can be source material. The fundamental concept is that OCR software can accurately and efficiently convert the original, unstructured data into a machine-readable text file through either pattern recognition or feature detection algorithms.
There are several reasons behind the upward trend in OCR technology. Increasingly, organizations are searching for ways to enhance the productivity of human employees, part of which involves eliminating time-consuming data-entry tasks from their workload – tasks that OCR could (at least help) deal with.
Recently, there has also been an increase in demand for remote and/or mobile solutions to enable businesses to deal with multiple data sets from any location in the most time and cost-efficient manner possible. OCR fits comfortably into the bracket of software capable of facilitating this.
The most ambitious plans for the future of OCR include merging its capabilities with AI to extract and accurately comprehend unstructured data. Moreover, OCR has found numerous applications throughout society, including text-to-speech software, visually-impaired assistance systems, or a means of digitizing large quantities of historical, antiquated information.
Proponents of OCR believe that it has the potential to yield many core benefits for businesses, including sharp upticks in efficiency, increased productivity levels, and more rewarding, enriched customer experiences.
However, OCR is not a perfect data-capturing solution. Potential gaps and pitfalls exist when using OCR to extract text; it is prone to errors when processing some fonts, handwriting styles, or languages, and does not truly represent end-to-end processing.
In this blog post, we’ll examine seven core benefits OCR can provide an organization before a more detailed explanation of its issues and ultimately arrive at an effective way for businesses to include OCR as part of a broader digital transformation strategy.
7 Business Advantages of OCR
OCR technologies might be leveraged to significant effect by a wide range of businesses. Fundamentally, any benefit that may result from the implementation of OCR could be generalized as increased efficiency and effectiveness in operations.
Specifically, a more straightforward, more detailed list of benefits for an organization may include the following:
Increased productivity
Productivity, a core business metric that all operational leaders are concerned with, can be significantly boosted by implementing OCR. In theory, OCR can extract data from image files faster than a human employee. Its speed makes sense, given that it is the task OCR exists to perform, and that software does not require breaks, or experience lapses in concentration, for instance.
With OCR taking care of simple data extraction, your workforce can spend more time and energy focusing on other tasks — for example, communicating with supplier networks or addressing customer issues. However, OCR’s text output still requires human validation due to the frequency of data errors.
Additionally, with OCR helping to feed data into a centralized database, operational workflows can be streamlined and refined, allowing more to get done over time than was previously possible.
Improved accuracy
One of the inherent problems with having a human employee manually keying-in data is the ever-present risk of mistakes. It’s always possible that your employee misreads a piece of data or is simply having a bad day; human error is a natural, unavoidable consequence of manual input. In a 2008 study, Raymond Panko concluded that the likelihood of at least one error in a human-processed database is close to 100%.
Automated software such as OCR does not have bad days. It will extract data with maximum accuracy, though OCR cannot guarantee data accuracy to 100%. There are certain conditions under which errors become increasingly likely. OCR software is faster and more accurate than humans tasked with extracting data from images.
Reduced costs
A business opens up the potential for significant cost savings via the introduction of OCR technology. In the first instance, the software is a technology that you buy and, ideally, continues to work moving forward, so your business can reduce the costs of employing a team of humans to do work that a piece of software could do better. Similarly, a company could reduce the cost of employing data checkers since data extracted with OCR can be relied on with higher confidence.
OCR can help reduce costs in other ways. For example, rendering data in a machine-encoded format removes the need to use your budget on storage space, printing, shipping, and so on because employees can work on the data in a purely digital format. OCR also reduces the likelihood – and therefore the cost – of missing, lost, or stolen data.
Enhanced customer experience
Competition across industries is higher than ever before, and the customers of a business – whether B2B or B2C – demand an exemplary level of service, a personalized user experience, and a smooth, omnichannel journey as they interact with a company.
The time sales reps and CSRs save by having manual data handling lifted from their workload can be more effectively invested in nurturing and developing those valuable customer relationships. Without OCR, an organization is often forced to ‘waste’ their sales staff on manually extracting order details from a. For example, an organization with OCR implemented would automatically extract those order details, leaving sales staff available and ready to deal with customers and enhance their overall experience.
OCR technology can also improve data accessibility by helping to store and retrieve data efficiently. This ability can dramatically cut the time a customer spends waiting for information when they make an inquiry, which can only positively impact their backend satisfaction levels.
Data security
When you store data in paper documents, the risk of loss, destruction, or theft is far greater than when data is stored digitally. OCR enables an organization to digitize and centralize its records; data formatted as a digital text file can be secured and backed up, therefore dramatically insulated from the risks inherent in paper-based formatting.
In addition, a business can exercise a more nuanced control of who gets access to which data, when, and what they can or can’t do with it – this constitutes a significant preventative measure against data mishandling.
Data flexibility
Particularly with trade documents, it’s often the case that initially extracted data needs to be updated or otherwise manipulated at a later date, subject to shifting conditions. OCR software allows users to quickly and easily make such edits, because it extracts and formats data into a flexible text file.
Similarly, OCR enables more effective data recovery in a disaster or emergency. Consider an organization that stores personal customer information on paper, which could be destroyed if the warehouse suffered a flood or fire. But in an organization that digitizes and centralizes customer information through OCR, the vital data is electronically distributed throughout the organization, meaning it is safer if one or more facilities face an emergency.
Efficiently-stored data
Another significant advantage of implementing OCR systems is its enhanced search functionality. Data processed via OCR is completely text-searchable, meaning that employees can quickly and accurately look up precise information such as names, dates, addresses, or order details. This kind of quick search is not possible in manually processed and stored data.
This digitized, efficient method of storing data removes the need to collect and organize vast quantities of paper; this is a significant step to an organization creating a truly paperless system of records.
Imperfect Processing: Issues & Problems with OCR
However, OCR alone will not yield genuinely reliable and accurate processing. The shortcomings of OCR prevent it from being a fully functional data-capturing system for businesses.
Not an answer for end-to-end data structuring
Many organizations are unaware that implementing OCR technology alone will not complete the journey from unstructured to structured data.
The technology can scan, analyze, and translate data into a digital text file with continually-enhanced and improved systems. Nonetheless, even if the data is extracted with 100% accuracy, OCR can only take you so far. A business will need to leverage other technologies and software suites, or a human employee, to go on and work with or manipulate that data.
Unavoidable inaccuracies
Irrespective of advancements and technological sophistication, there will always be the possibility of an error taking place. No OCR software will ever be able to guarantee 100% data accuracy – the range of variety in source materials is too great.
Even without the risks of challenging fonts, languages, or scripts, something as simple as a paper document being scanned with its orientation tilted by a few degrees can throw OCR software. Similarly, lens reflections, blurred edges, low resolution, or shaded backgrounds may also prevent OCR from correctly scanning and analyzing data. These characteristics are unavoidable for many of the documents countless businesses use to operate.
Indecipherable text formats/fonts/languages
There are specific formats, languages, writing styles, fonts, and compositions that OCR struggles to recognize. An ongoing problem is the misidentification of calligraphy and other archaic handwriting styles – this is unlikely to be an issue for businesses. OCR has also demonstrated inconsistency and unreliability when processing Arabic and Chinese alphabets. This limitation could damage an organization’s operations dealing with an international supplier network.
Moreover, the difficulty in distinguishing lookalike characters, such as ‘1’ and ‘I,’ or ‘O’ and ‘0’, often results in inaccurate OCR analysis.
The Search for True Data Accuracy
The technology presented by OCR is undoubtedly impressive in its capabilities. In a business context, given the right conditions (which an organization cannot always guarantee), text recognition software can dramatically improve efficiency and productivity, yielding cost savings and increasing the effectiveness of data handling systems.
Viewed from a broader societal perspective, OCR technology has proven invaluable in assisting visually-impaired users, facilitating text-to-speech applications, translation services, or the indexing of historical documents.
But in purely business terms, OCR is not enough. That’s why, at Conexiom, we don’t use it for our automated trade document processing software (though for image files, there’s no alternative). Instead, we merge customizable data mapping with automated business rules to extract and transform document-contained information with 100% accuracy.
To find out how Conexiom could help implement touchless trade document automation in your business, get in touch and request a demo today.