How is unstructured data impeding the digital progress of a company?
Unstructured data refers to any data that exists outside of an organized filing pattern like tables or spreadsheets. Think of emails, documents, contracts, SOWs, audits, images, audio, and video files, among others, that your company uses or generates through your day-to-day operations.
That said, unstructured data is a big deal because it can single-handedly freeze and even bring down your business’ digital progress while increasing risk.
A BCG survey showed that digital transformation is a HUGE challenge for most companies. Today, 70% of these projects are unsuccessful, and the absence of a data structure is among the key reasons for failure.
From hindering end-to-end automation to poorly performing websites, this type of data is hindering digital advancements in critical areas.
In this article, we’ll discuss five ways unstructured data is impending enterprise digital progress, and why it’s time to turn to an intelligent document processing solution.
Let’s get started.
1. Limited Automation
With unstructured data, companies cannot fully attain their RPA or automation objectives.
A well-executed RPA project is one of the biggest drivers of digital progress in organizations today. It is enabling employees to channel more time into productive work by alleviating the burden of iterative chores. It allows enterprises to fuel innovation, accelerates speed to market, enhances customer experiences, mitigates risk, and streamline operations.
Unstructured data requires human intervention at various parts of the task chain, thereby preventing full cycle implementation of RPA projects.
Any automation process, regardless of the magnitude, runs on the power and availability of structured data. Consider the simple case of a digital Contract Analysis Software, which depends on existing data for its analysis.
As dark data isolates important sections of information, people, workflows, systems, and technology are unable to understand what risk lies within their enterprise and furthermore fetch important contract clauses that businesses need to know about.
In this case, the RPA Software is underperforming not because it’s defective, but because of an absence or obscurity of data.
Consequently, this contract analysis tool needs to be supplemented with a human verifier, and hence cannot achieve comprehensive end-to-end automation.
What’s more, in the absence of verification, the ineffectiveness goes unnoticed. Over time, the consequences become magnified as businesses upscale the RPA implementation or abandon RPA altogether as the ROI is not being realized.
2. Restricted Digitization
For many companies today, hard copy data, which is one of the biggest contributors to unstructured and dark data, is still part and parcel of daily operations.
Despite the advancement in digital technology, most organizations are far from paperless going by a RecordNations study. Content Migration and Digital Preservation offer organizations a host of benefits waiting to be realized.
The report states the average employee in a business uses approximately 10,000 copy papers annually! So, if a business has about 20 office workers, that means over 200,000 documents that require sorting and labeling.
It’s often the case that there are no proper filing procedures. Consequently, many of these hardcopy documents get misplaced.
In companies heavily reliant on an unstructured, paper-based record system, digitization of records can be challenging.
Implementing traditional methods of digital content migration, without a proper data strategy, means some of that data gets left out of the equation. This unavailability of data results in an information system that is lacking in both reach and searchability.
While digitized, employees are still unable to find the data they need, when they need it. Therefore, the digital transformation endeavor becomes unsuccessful.
However, the solution lies in an expansive Content Intelligence Platform with in-depth data extraction technology, such as Adlib, for example.
This AI-powered content management software can discover and extract data from various corners – from any format. From print to word documents lost in heaps, Adlib can scan all types of documents, hard or soft, and compile these into secure and accessible cloud storage.
3. Underperforming Websites
Today, a website is a business’ front door. However, many company websites are not very useful because they’ve been built on unstructured or dark data and are unable to offer a complete depth of resources about the business.
Web designers have little company data to work with or must sift through mountains of data to find valuable information for the foundation of the website.
The situation becomes even direr when you’re talking about a business that wants to fully transform into an eCommerce platform.
With unstructured data as a reference, it becomes hard to have all your products, services, and general offerings available to clients in real-time. As a result, website performance falters.
According to a market study by Blue Corona, 47% of web users check the services or products section of a business before any other part of the website.
If clients don’t find what they’re looking for at first glance, they leave and their next stop is at your competitor’s site. So having clear, structured data is an important part of delivering the right user experience, creating & maintaining a highly converting website, and driving repeat business.
4. Confined Performance
Where does the true worth of software lie?
The worth of any automation or digital tool lies in continually fulfilling its objective under perfect scenarios of operation. However, its greatest value is in its ability to deliver the same results under data situations that are not ideal as well.
One of those imperfect scenarios includes unstructured data. When data is dirty or not so easy to locate, RPA software comes across situations that it’s not programmed for.
And this is usually the case more often than not. Going by a 2021 Gartner market report, 80% of companies today rely on unstructured data. That means that 8 out of 10 times, RPA software will have to work with data that is not in well-formatted or organized databases.
Consequently, the result is that RPA tools will be unusable most of the time because the majority of a company’s processes are fueled by data in unexpected layouts.
However, even if your RPA bot manages to find a way to run on that data, if it is not dependable or properly structured, possibly due to mismatch and errors, they’ll produce results of similar quality.
Structuring data is, therefore, the first step to success in enterprise digital progress.
5. Data Security
Businesses can only protect data that they are aware of. With unstructured data, knowing what information to protect, and where it is in the first place, is the furthest thing from the word straightforward.
In a large information cycle, sensitive details like personally identifiable information often mix in with general data, which keeps growing at a rapid pace each day.
If PII in general data flow systems is not encrypted, cybercriminals can easily exploit these vulnerabilities.
So if you have already launched digital projects on the foundations of unstructured data, you may have to go back to the drawing board and put in place an encrypted and properly structured format first.
This change will be a major step towards Data Privacy Compliance, or better still, shield you from falling prey to hacking and a costly, enterprise-wide data breach.
Conclusion
Unstructured data can be a big bottleneck for organizations wanting to embark on a successful digital transformation journey. The bigger the company, the bigger the problem.
Since data is often laborious to find in such cases, possible opportunities for business and digital advancement often go unnoticed. What’s more, digital projects can fail altogether due to the security threats posed by the lack of a clear data model.
Bots and RPA processes, in general, would be built upon unstructured data, which would sooner or later reduce the effectiveness and potential of automation efforts.
Therefore, it’s important now more than ever to have a structured data solution as a steppingstone to your company’s digital process success, and the intelligent document processing capabilities of our Adlibwill help by structuring your data.
A great option to do that is using AI-powered, Content Intelligence Cloud to tidy up data messes.
