Accelerating Digital Transformation: Simple Solutions for Complex Problems

Companies in their infancy and those that have stood the test of time have at least one thing in common: the need for digital transformation and innovation. But pursuing digital transformation is complicated—especially for companies with years of business history and data. The first step of digital transformation is to ensure your data is digital. The fact is, 80% of information remains in unstructured formats, or in a variety of antiquated formats, such as paper and fax. Sometimes the information you need is stuck in interpersonal messages between employees.

The key to successful digital transformation is to find the right technology—the type that identifies and sorts a myriad of documents, recognizing the information and converting it into valuable data. That is why tech providers offering high-volume processing hardware with software that can communicate directly with legacy systems (or the cloud) have the upper hand in the battle to digitally transform the world’s companies.

Digital Transformation Across Industries

Many industries—banking, healthcare, and government sectors, to name a few—rely on information accessibility (and security) for day-to-day operations. Of course, the complicated, classified, and otherwise mission-critical documents need to be processed, but with the increase in remote work, employees need to learn best practices and compliance standards even more quickly. Unfortunately, this leaves room for manual data entry errors and bottlenecks—ultimately threatening ROI and company security.

My company solved its first complex digital transformation conundrum when it invented a solution for the airline industry. In the old days, airline tickets were printed on red carbon paper, and ibml’s system uniquely captured information from these messy documents and converted it into usable data.

Automating critical aspects of document content management—like taking unstructured documents, digitizing them, and sorting them—makes it easier to centralize data and develop meaningful analytic insights into operations. Leaders can identify inefficiencies, vulnerabilities, and bottlenecks before they begin to impact the bottom line. Corporations can quickly access a holistic view of performance metrics and assess their influence when all of their historical data is available for analysis.

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The Power of Historical Data and Modern Tech Tools

Historical data provides a better context for trends in business performance and can help inform innovation, technological, and financial decisions within an organization. In fact, all AI and machine learning depend on good data. So all leaders wanting to employ these technologies at scale must first invest in a fast, accurate, and secure digitization effort. That’s a key mission of companies in this space.

Like every other industry, Intelligent Document Processing (IDP) greatly benefits from artificial intelligence (AI) and machine learning (ML) technologies. AI and ML are used in IDP to understand document patterns and classify types so that the most relevant information from those documents can be extracted and made available with minimal human intervention, reducing costs and improving accuracy in information capture from unstructured documents.

In pursuit of digital transformation, companies must build clear frameworks to guide the process. And they must realize that the process is complex, especially when dealing with legacy systems, unstructured data, and many documents.

To stay ahead of the competition, companies must build their plans around tools that help validate and organize data into actionable insights. Improving performance, decreasing inefficiencies, and opening up new avenues for innovation and development is the key to ensuring a smooth transition from the physical world to the digital one.

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