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Data Digitization
May 26, 2022
Min Read

Successful Digital Transformation Depends on Unstructured Data

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super.AI
Chief AI for Everyone Officer
SUMMARY

The 2022 GBS & Shared Services State of the Industry Survey found that data digitization is the top priority for companies in 2022. The survey also revealed most enterprises that have started digitization are currently only focusing on documents, and the majority just documents in the procure-to-pay (P2P) and order-to-cash (O2C) processes.

Digital data powers digital transformation

Data digitization is the process of converting information into a digital format. For example, scanning paper documents and converting them into digital files (e.g., PDF). Digitization is a foundational component of digitalization, which refers to leveraging technology and digital data to enable new processes or improve existing ones. Digitization and digitalization are stepping stones to the ultimate goal of digital transformation, where business activities, processes, products, and models fully leverage the opportunities of digital technologies.

In order to succeed with digital transformation, companies need to drastically expand the scope of data they leverage. An estimated 2.5 quintillion bytes (exabytes or 10^18) of data is generated each day, and 80-90% of it is unstructured—think documents, emails, texts, social media posts, videos, audio, and images. This information is scattered across organizations, with more than half (52%) of businesses reportedly keeping their data in five or more storage platforms.

This raw resource is waiting to be mined for valuable insights that can radically transform customer experience and lower costs. However, most enterprises today are focused on automating business processes that rely on structured data, while deprioritizing or altogether ignoring unstructured data.  What they don’t realize is that nimble, AI-first startups in every niche of their business are hard at work delivering products and services that delight customers at a fraction of the cost of incumbents. Tackling unstructured data today is paramount for remaining relevant in an increasingly competitive and dynamic environment, as well as succeeding with digital transformation.

It all begins with the right data digitization solution

Digital transformation is fueled by data, which makes selecting the best platform for processing, analyzing, and digitizing data paramount to success. Data accuracy and flexibility are key to any digitization effort. Without accurate data, digital transformation efforts are destined to fail. Without flexibility, businesses will struggle to process new data types (or handle variability in *any* data type). For example, many intelligent document processing (IDP) disappoint users because they fail to accurately extract data from documents that aren’t formatted in a specific manner. solutions boils down to issues with accuracy and flexibility.

Many companies are still struggling to digitize and process documents because they are using rigid platforms that are incapable of dealing with the complexity and variability inherent to documents. When it comes to data digitization, selecting a platform that is capable of processing unstructured data can help mitigate or altogether eliminate accuracy and flexibility limitations. Keep these tips in mind as you begin your search for a data digitization platform:

  1. Select a flexible platform: Make sure the digitization platform can handle all the forms of unstructured data. For example, many enterprises are adopting IDP solutions that are great at processing structured or semi-structured documents, but can't handle unstructured documents, emails, images, etc. This means adding yet another tool to the box.
  2. Guaranteed accuracy: Enterprises need to deliver business outcomes and for that they need quality, speed, or cost guarantees. AI solutions typically offer only confidence levels for results, and have limited capabilities to guarantee speed when humans are involved. Look for solutions that allow you to make trade-offs between quality, cost, and speed with guaranteed results.
  3. Ease of setup and maintenance: There are a wide variety of document processing solutions in the market. Some are cloud-based, others require on-premises deployments.  Some have pre-trained models for specific use-cases, others require extensive training for every use case.  None of them provide an on-demand crowd-sourced workforce for training/data labeling during the setup phase. Make sure the solution you select provides instant access to a crowd-sourced pool of experts during the setup phase, can leverage the best pre-trained model available for any current and future use case, and can deliver enterprise-grade AI applications for your specific use case in days, not months.
  4. Human-in-the-loop (HITL) capabilities: Unstructured data solutions rely on AI models that learn from humans. However, humans are often an afterthought when automating business processes. Unlike bots, humans need to be hired, trained motivated, and recognized. They also take vacations, get distracted, and make errors.  Make sure the platform includes access to curated crowd-sourced specialists that can simplify HITL, quality control metrics that continuously monitor output, gamification to keep workers engaged, and sophisticated workflows with built-in escalation rules to satisfy service level agreements (SLAs).

Additional data digitization resources:

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Data Digitization
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