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A person taking a photo of a document in order to utilize OCR to extract data.

OCR: The next wave of digital transformation

OCR helps to bridge the gap between analog and digital for everyday users as well as businesses trying to transform and step into a more connected future. In the middle of an ongoing global race to digitize, companies like Apple are innovating around OCR, indicating that it’s here to stay.

OCR — More useful (and necessary) than you may think

In the recent release of iOS 15, Apple officially promoted Optical Character Recognition (OCR) into a native feature of the iPhone as a tool called Live Text. While this may seem like a small add-on feature, it speaks volumes about the future of digital transformation and how a large visionary company like Apple views the world evolving.


Image credit: Apple


Apple’s Live Text allows users to take photos of things like signs, posters, or documents to pull out useful information like contact information or addresses. Users can also use Live Text to translate text into different languages. Instead of manually typing unfamiliar foreign words into a tool, a user can snap a photo, select the text in question, and translate. 

An OCR-less future? Maybe one day, but not yet

In a perfect digital world, OCR would be unnecessary because everything would be digitized, making textual information more readily and immediately usable. 

OCR is primarily used to read text that’s printed from some kind of software. Common examples are bills, insurance forms, and restaurant menus. In each of these cases, if your iPhone could talk directly to the accounting software, your insurance provider, or the restaurant's software, you could access the text directly without OCR. 

Each of these industries is evolving. Many insurance providers, for example, are starting to offer their services online or through mobile apps, but it's going to take some time — potentially an infinitely long time — before every element of our lives is digitally connected.

Why we need OCR

That future point where everything is perfectly digitized is far off enough that Apple, whose best interest is to create a seamless experience where your phone is able to “talk” directly to any restaurant through their proprietary ecosystem, believes that it's worth having OCR built into their operating system to serve as that bridge for now.

This problem is an order of magnitude more exaggerated in B2B settings where complex networks of businesses interact in sectors like manufacturing, healthcare, and insurance with business documents like invoices, claim forms, and loss run reports. Here, standardization is especially difficult because peers, who are often incentivized to work against each other (think insurance providers and hospitals), would have to agree to use the same software and protocols. 

In certain cases, the pace of innovation is limited by government regulation (e.g., requiring wet-ink signatures for certain financial documents). In each of these cases, businesses are faced with only two practical options: 

  1. Process information manually, or
  2. Use OCR technology.

Layering OCR into digital transformation objectives

In short, digital transformation refers to using digital technologies to transform a business process. This can be as simple as taking a paper form and making it an online form, or it could be automating a certain process using an artificial intelligence (AI) or machine learning (ML) solution.

To date, digital transformation has been fueled with a simple "standardization" formula: Pick an analog business process, model its data relationally, and develop workflow software to plug data in and out of a structured database. 

When it works, this approach can be very efficient. Human Resources Information Systems (HRIS) and Enterprise Resource Planning (ERP) systems have been massively successful in their respective industries at reducing costs, driving standardization, and enabling business intelligence. In each case, they hold some important properties in common:

  • The underlying information can be modeled relationally
  • The systems are primarily internal facing (i.e., its users, inputs, and outputs are within the four walls of the company)
  • The task (e.g., managing human resources) is roughly the same across companies and industry verticals

What about unique, non-standard business processes?

The reality is that there are a number of business processes that simply don’t fit this mold and are therefore much more challenging to standardize. For example, sending invoices between companies breaks all three constraints listed above. 

Thankfully, AI and affordable cloud computing have progressed to the point where we have an option other than standardization to accomplish digital transformation.

The next wave of transformation

The revised formula looks something like the following:

  • Identify the unstructured data sources (e.g., PDF documents, emails, etc)
  • Extract the underlying data into a relational format using AI-powered OCR
  • Integrate this data into other structured or AI-based systems (e.g., accounting software).

This approach has a number of benefits. First, it can be accomplished without standardization. Organizations are finally free to digitally transform without depending on all of their business partners to transform at the same pace. Second, there is little to no workflow required to plug data in and out, resulting in overall less manual data entry than the traditional solution. For example, a CRM supercharged with automation does not require a salesperson to manually check each order form they receive to ensure it has all the data or documentation it needs to be fulfilled.

Finally, in many cases where structured options exist, it’s cheaper for an individual organization to transform this way because it can be implemented on top of existing processes (think hyperautomation or RPA) and updated incrementally as data evolves.

A call for startups

The OCR-driven approach is very flexible and general, but it is no substitute for the application- and domain-specific expertise required to power digital transformation. 

At Impira, we believe that no one company will build every OCR application. Instead, we believe in a budding ecosystem of automation startups aimed at various industries, and we are fortunate to work with dozens of them as customers.

Looking across these customers, we've observed the following key traits of successful automation companies:

  • They have a clear vertical focus. Automation is very nascent and such a massive opportunity that you need a very clear understanding of a customer's pain points to develop the right solution.
  • There is a strong operations team that can fill in gaps where AI software can’t perform (yet). Great automation companies are relentless about driving the operations team's feedback into their product roadmap.
  • They combine multiple best-of-breed technologies, like Impira's AI-powered OCR into a single package the customer can consume.

We believe strongly that this breed of next-generation automation companies will outpace their standardization-requiring counterparts in driving digital automation. If you’re building a company in this space, we would love to swap notes and help if we can. Reach out to us at info@impira.com to get the conversation going.

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