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In this opinion piece, Scott Francis, Technology Evangelist at document scanning solutions provider PFU America, Inc., explains why the secret ingredient often overlooked when discussing digital transformation is data hygiene – and how organizations can change that.
Organizations recognize the untapped value in their paper archives, both as potential training data for artificial intelligence (AI) and as a way to cut physical storage costs. However, unlocking this value from can be a cumbersome challenge for many companies and the inability to fully leverage archived documents can stymie organizations’ digital transformation initiatives.
The challenge isn’t isolated: according to recent research from Wavestone, 87.9% of participants listed investments in data and analytics as a top organizational priority. More than 82% said they are increasing their investments in data and analytics. Yet, despite the jump in investments, only 48.1% of survey respondents said they’ve created a data-driven organization.
The disconnect between the investment in the proper use of data for business insights and execution can be costly and inefficient for a variety of reasons. Not being able to find accurate data quickly is one of the top reasons employees skip this step. When your employees can’t find data, they’re left to their own devices to compensate. This costs companies money, drains productivity, and leads to a loss of customer trust. However, there’s more to successful digital transformation then just finding data—it has to be current, relevant, and “clean” in order to make an impact on business decision making and result in positive outcomes. The secret ingredient that often gets overlooked in the bigger digital transformation conversation is data hygiene.
Data hygiene: a critical success factor in digital transformation
Data hygiene—the process of identifying, correcting, and removing inaccurate, incomplete, irrelevant, outdated, or duplicate data—is not flashy, but it is very necessary. If not done correctly and thoroughly, poor data hygiene can result in bad decision-making and inefficiencies. Proper data hygiene practices are the cornerstone of data quality, making it more reliable for analysis, reporting, and use for daily operations.
In addition to data accuracy, there are three main aspects of data hygiene that work together to ensure that data is accurate, consistent, and usable:
- Data Consistency: Ensuring that the data is consistent across different sources and systems involves checking for discrepancies in formats, units of measurement, and categorization to make sure that the data is aligned across databases.
- Data Completeness: Data hygiene includes filling in gaps or identifying when data is incomplete or outdated, and then making efforts to gather the missing pieces.
- Data Validity: In a best-case scenario, data should meet predefined rules or standards. This includes validating the data against a set of rules, such as acceptable ranges, value formats, or specific conditions that the data should meet (e.g., phone numbers in the correct format).
Once these initial data hygiene steps are accomplished, teams can apply these same principles to digitized paper documents that are captured using a combination of professional document imaging scanners and software. Organizations can then rest assured that their data is sound and proceed to classify and index the data, including the implementation of secure access rights.
Another important component of “data cleaning” is anonymization and redaction. Using advanced document imaging software, organizations can thoroughly automate the anonymization and redaction of sensitive data, including personally identifiable information (PII). This enables companies to meet stringent data privacy laws and regulations—including CCPA and GDPR—avoiding potential legal action. The software approach is an effective means to minimize exposure to sensitive data during document capture workflow and ensuring documents that include sensitive data aren’t integrated into content management systems.
Solving the dark data mystery
Dark data—data that organizations are storing but not using—is a fact of life. It’s such a widespread issue that a recent global survey by Splunk estimates that 55% of an organization’s data is considered “dark”, or it could be hidden, untapped, or unknown. Organizations gather dark data through various processes, unused logs and records from transactions or system monitoring. Emails, documents, or multimedia files that aren’t actively analyzed, also fall into the dark data category.
The challenge is in finding ways to analyze and extract value from dark data, which can be both digital as well as in hard copy paper archives. Once paper documents are digitized, the same data hygiene best practices can be applied to dark document data which can then be integrated into relevant systems or LLMs and be fully leveraged, along with born-digital data. This untapped data can provide dramatic impacts on business intelligence, innovation, and provide a competitive advantage.
Beware of bad data
Despite all the resources and time spent on data hygiene and harnessing the power of dark data, it’s still possible for bad data to infiltrate systems and wreak havoc on digital transformation efforts that negatively impact decision-making, strategy, customer interactions and overall business performance. Bad data can result from entry mistakes or typos, for example, incorrect numbers, dates, or categories.
In the case of document scanners or image capture devices, bad quality scans due to outdated equipment, low resolution, or worn-out components can lead to distorted images or illegible text. Or a scanner might misread barcodes, text, or images due to issues like low resolution, poor image quality, or inferior scanning sensors. This could result in incorrect data being input into a system—especially if the text is optical character recognition (OCR)—based-processed, and lead to significant productivity loss, especially if the error is detected “downstream”. In worst case scenarios, bad data may even result in regulatory-driven fines due to a PII breach.
Create a culture of digitization
For companies to achieve their digital transformation goals, it’s important they create a “culture of digitization” because so many businesses still rely on paper-based records alongside digital data. By integrating adhering to foundational data hygiene best practices, then integrating data from both paper and digital sources, organizations can gain a more complete understanding of their operations, leading to more accurate decision-making, improve efficiency, and ensure seamless operations.
About the Author
Scott Francis, Technology Evangelist at PFU America, Inc., brings more than 30 years of document imaging expertise to his position where he’s responsible for evangelizing Ricoh’s industry leading scanner technology. With over thirty years of experience in the enterprise content management industry, he frequently provides thought leadership on document scanning use cases and best practices in addition to the overall benefits of digital transformation solutions. To find more news from PFU America, Inc., click here.
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