Businesses have more data than ever before. Undoubtedly, this data contains a wealth of value that can be leveraged to improve cost savings, redefine processes, and establish a competitive advantage. But the biggest barrier is that much of its value is trapped and not easily accessible.
With the growing amounts of unstructured data, in the form of documents, images, emails, etc., companies keep starving for insights. The sea of data is meaningless unless it can be turned into business value.
For a long time, getting value from unstructured data has been challenging. Companies were unable to process and analyze the sheer volume of facts, figures, and documents manually. It was time-consuming, error-prone, and expensive.
However, the recent advances in innovative technologies made it possible to automate the processing of vast amounts of data. Allowing companies to unleash the full potential of their content in a cost-efficient manner.
By applying intelligent technologies for unstructured data management, businesses can benefit in four major ways:
Let’s discuss in more detail each of these benefits.
No matter how valuable or useful your data is, it is useless if no one can find it when it's needed. The goal is to move from recreating information to reusing it over and over again.
However, for many organizations, the findability of information is still a big challenge. On average, an enterprise with 1000 workers wastes from €2.2 to €3.1 million per year searching for nonexistent information, failing to find existing information, or recreating information that can’t be found (Source: IDC).
To improve information findability, some companies have already turned their paper documents into digitalized machine-readable text. It’s easier to find the right information in a digital space rather than going through each paper file physically. The digitalization of paper documents is incredibly important but often underestimated first step. If done incorrectly, all the files will be digitalized but still challenging to find.
Why? Let’s start at the very beginning.
Once the paper has been scanned, a digital document is created. Usually, it exists only as a non-text format. So, you can read it from the screen, but the computer doesn’t recognize any words in it. To convert scanned documents into searchable and editable text files, Optical Character Recognition (OCR) technologies should be applied. OCR adds a text layer on top of the scan, making documents machine-readable. In this case, they are easily retrieved, edited, and searched on.
But there is a catch.
Even the most sophisticated OCR technologies make mistakes and misinterpret characters.
As a result, the information that you store digitally can be incorrect, and thus it can be challenging to find it back.
This is the reason why we’ve developed our unique intelligent solution named Post-OCR. By using dictionaries and learning from the specific business language, Post-OCR corrects the misinterpreted characters and improves the quality of data that you store. To learn more about Post-OCR, check out our previous blog post.
Intelligent Content Management solution, such as Doculayer.ai, improves findability and increases the quality of data that you store. Ensuring that you will always find your documents back when you need them.
Unstructured data is difficult to process and organize because it has no pre-defined format. Think of the various types of documents like employee contracts, vendor agreements, onboarding materials, etc. They all have different formats.
To bring structure to these unstructured documents and improve the use of information, employees have to create metadata. It’s a basic description of the document that may include the contract number, deal details, or names of the parties involved.While metadata is crucial for search, information compliance, retention policies, and workflows, it is usually maintained poorly. In fact, very few employees bother to do this, and if they do, this is often inconsistent across an organization. Manual metadata creation is a slow, painful, and error-prone process. As a result, companies typically misfile up to 20% of their records - thus losing them forever (Source: ARMA International).
Fortunately, AI solutions can automate metadata extraction and eliminate human errors. They can “read” and “understand” the content of the documents and extract key values such as company’s name, contract due dates, locations, etc. This significantly reduces the time spent on document processing, and allows employees to focus on other work that brings more value to the organization.
Robotic Process Automation (RPA) proved to be an ideal solution to improve company efficiency by automating simple, repetitive tasks. However, unstructured data is still a significant challenge for RPA.
RPA can only replicate pre-established actions. It needs to be explicitly programmed to extract metadata for every document type. And with unstructured documents, it is nearly impossible to teach the bot exactly where to extract the relevant information. Hence, there is a need for Intelligent Automation. AI solutions can analyze documents intelligently the way as a human would.
Additionally, unlike RPA, AI solutions continuously learn from experience and improve performance overtime automatically. They can operate with little to no human interventions.
For instance, with Doculayer.ai, we aim to create a collaboration between human and artificial intelligence. We give computers the tool to learn from the knowledge experts to make decisions. When the machine is in doubt, it requests employees to validate the results. And in case of an error, the algorithm is retrained. This process allows Doculayer.ai to learn constantly with the human expert in the loop.
The final major benefit that Intelligent Content Management solutions offer is improved compliance. As we mentioned earlier, data has hidden value. But at the same time, it might contain hidden risks. Failing to comply with GDPR regulations can incur fines up to €20 million or 4% of your company’s annual global revenue. Taking care of own data and ensuring its compliance, is a top priority for all the organizations.
AI solutions, for example, can detect sensitive information in documents and flag them for special handling. Automatic classification and processing can ensure that documents will be retained according to the legal and legislative requirements. Intelligent solutions can determine the required retention periods based on the document type and trigger a workflow to review the document when it’s needed.
The potential for AI-powered Content Management solutions is incredible. The biggest benefits of using AI for unstructured data are being able to find it, structure it, and take actions. And Intelligent Content Management is the only way for organizations to cope with the growing amounts of unstructured data.
Do you want to know more about how your unstructured data can be turned into actionable insights with Artificial Intelligence? Then join our upcoming webinar on November 7th.