The way organizations manage company information sits at the crossroads of just about all business processes. Day after day and week after week, employees are wasting a significant amount of time dealing with the myriad of challenges related to working with company documents — across the entire document lifecycle. That wasted time is a silent killer to productivity, which can cost organizations a tremendous amount of money in opportunity costs.
In a recent study, IDC revealed that the unproductive time workers spend as a result of information management inefficiencies amounts to a loss of 21% of the organization’s total productivity, which costs the organization an astounding amount — nearly $20,000 per worker per year.
Early American colonist William Penn embodied this sentiment best when he said, “Time is what we want most, but what we use worst.” The data in this whitepaper was compiled from a research project commissioned by M-Files to better understand how companies across the globe are managing their growing store of company information. With resounding clarity, the consensus is that document management remains a challenge.
Artificial Intelligence: A Means To An End
Information management has changed from pure document management and archiving into a real business enabler. Today’s intelligent information management solutions offer ways to automate the time-consuming and often boring document-driven processes within a business.
One of the key drivers in this automation is the use of artificial intelligence and machine learning. AI and machine learning can reason and discover meaning as well as learn from experience. Metadata is information about a document that gives context to the content. An invoice, for example, might contain metadata related to the invoice date, the client, the salesperson, and the products or services sold.
This metadata force context on the invoice, allowing it to be searched and found much more easily by any associated content field.
Artificial intelligence systems can easily churn through lots of information to recognize patterns and categories in the metadata. From there, artificial intelligence can make metadata suggestions (or automatically assign metadata fields) based on past iterations of a document.
It’s an amazingly powerful tool for information management platforms.
How AI Can Clean Up Disconnected Data Repositories
Call it information sprawl. Call it content chaos. Whatever you call it, the problem is only growing along with the rise in data volume, velocity and variety. The challenge is primarily caused by company information scattered across multiple data repositories. The problem can only be remediated if organizations heed the call to tame the sprawl in a systematic and intelligent way, perhaps as a leg of their overall digital transformation strategy. It’s a status quo that remains alarming — the organizational penchant for storing and managing content across several information silos — ERP, CRM, network folders, email inboxes, file-sharing applications… the list goes on and on.
Sifting through a huge amount of clutter to find business-critical data among disconnected repositories is a very common problem in today’s offices. It’s estimated that only 0.5% of all organizational data is used for business decision-making. Artificial intelligence can help make sense of the other 99.5% of data by adding context to it and perhaps rendering that dark data more useful for organizations.
This intelligence paper drills down to the heart of document management, surfacing statistics on how organizations in nine different countries are managing company information and how they are facing the challenges presented by their ever-increasing store of data.
Artificial Intelligence And Document Contextualization
Whether you’re aware of it or not, artificial intelligence (AI) has a ubiquitous place in our lives today – think personalized playlists on Spotify or the ‘Recommended for You’ lists on Netflix, both of which use AI to curate a selection tailored just for the user.
Now its presence is being felt in the area of document management, with AI and cognitive computing set to revolutionize the ways in which we store, archive, process and extract information.
Smart document management systems are making healthy use of AI for a variety of functions — including automatic classification, processing and data extraction. Primarily, AI has opened the door for powerful contextualization of an organization’s information. AI can ‘read’ a document and, based on past iterations of similar documents, suggest properties that might be included in the metadata for that document — enhancing the user’s ability to find exactly what they’re looking for in information searches. How powerful would it be to enter an invoice and have AI suggest which account it should be tagged to, which employee might be responsible for processing it or which expenditure category to place the invoice in? AI makes companies more efficient, consistent and increases auditability — primarily by reducing user error and misclassification, and by properly coordinating the best context for a document based on its contents.
Badly-Named Documents and Finding Company Information
The old way of categorizing documents involves naming them the best way you can and putting them into a folder that hopefully matches the context of that document. But that process is wrought with challenges, since employees probably work differently when naming and foldering documents.
One piece of content can have valid reasons for being stored in multiple folders or locations; in traditional folder structures, an invoice, for example, could be placed in a folder for sales documents, a folder for that client, an invoice folder, or several other sensible folders. But then how does everyone find that invoice, when they need to? Where do they look? Furthermore, when it comes to naming that file, how can the company ensure a consistent naming convention that will make sense to the next member of staff who comes along to find that document?
The newer way is based on metadata — and the resulting ability to find and manage information by what it is rather than where it is stored.
Metadata is “data about data.” Although it may seem pithy, this is an accurate definition.
The main goal is to enable users to quickly determine which document they need to view from their search results — based on the context of that document. While traditionally metadata has been entered manually, some document management systems are now making use of AI to intelligently suggest context cues that should be included in the metadata for a file. This ultimately reduces error-prone manual entry and provides for a consistent method for organizing documents to make them easily classifiable, and thus findable.
Just over four in five (82%) respondents find it challenging to name or tag a document when saving it to ensure that it can be easily found by their colleagues and over nine in ten (93%) report that at some point they have been unable to find a document because it had been badly named or tagged when filed.
This is not a surprise given that only 27% of respondents report that their organization has completely clear guidelines in place as to how a document should be labelled when saving to a system, showing that organizations have work to do if they want employees following the same process.
The Benefit of AI-Enabled Contextualization
Respondents were also asked if it would be of at least some benefit to them and their colleagues if the system they used could automatically name or tag the document for them.
It is hardly a surprise that more than eight in ten respondents report that it would be a benefit to have a system which could automatically name or tag a document. The benefits of AI-enabled contextualization in document management are self-evident and far-reaching:
Automatic document classification and processing: By virtue of suggesting metadata context for documents, the process becomes less error-prone and more automatic. In one use case instance, optical character recognition (OCR) has made document capture a breeze, but AI takes this a step further by being able to “read” the information on that document, classify it appropriately and automate workflows based on that classification – at a fraction of the speed a human could. While the AI-driven metadata engine is initially directed by a set of rules, its identification and processing capabilities continue to advance using machine learning.
In other words, it can learn from frequent exposure to similar documents, as well as from the actions taken by personnel on those documents.
Data extraction: By being able to precisely read information and understand context, an AI-powered document management system can take data extraction to the next level — a capability that is crucial as organizations are besieged with more and more data
Document clustering: With AI, documents can be easily grouped by common themes, fields or topics. This can help organizations recognize how documents relate to one another within a broader context and help them find parallels and make inferences that might not have otherwise been possible
Advanced security: Companies can enhance security and protect customer data with an AI-powered document management system.
The technology can detect sensitive and personal identifying information and flag those documents for special handling or enter them into a specific workflow. Automatic classification and processing also mean that documents aren’t assigned to an unsecured file location, waiting to be actioned.
Clearly the research supports the notion that workers across the globe still have nagging issues when it comes to the most basic document management functions — issues that will worsen as time goes on and the store of information gets larger. Businesses face a multitude of pressures — some of which can be mitigated by a simple information management strategy. A few of these challenges that could be assuaged include the weight of:
- Keeping up with the demands of an everchanging workforce, one that includes millennials and digital natives that carry expectations of a flexible/mobile work environment.
- Gaining a competitive advantage through the ability to attract and retain the best young talent.
- Optimizing productivity, especially by freeing up key personnel to work on mission-critical or strategic tasks rather than spending an inordinate amount of time searching for the correct information.
- Ensuring compliance and auditability in an environment of mounting regulations like GDPR.
- Safeguarding quality standards with a traceable and auditable document trail that can be called upon in minutes rather than days.
Unless information management issues are addressed in an intentional and meaningful way, companies will continue to suffer from less-than optimal productivity.
The Solution to the Problem
The good news is that there is a solution for organizations seeking to modernize the way they manage documents. All the challenges faced by the employees surveyed in this research and those billions of others around the world can be mitigated by an intelligent information management system. Think about the issues cited in this research:
- Finding documents easily
- Locating the most recent version of a document
- Document chaos caused by scattering of information across several repositories
- The process for reviewing, approving and signing documents
- Enabling the mobile workforce to manage documents away from the office
- The risks of personal device and file-sharing app use
- Contextualization of documents
Every single one of these issues has a single solution — an intelligent information management platform. Documents are the lifeblood of an organization and fast, secure access to the correct versions of documents can be the difference between success and failure.
Research from Forrester suggests that 70% of organizations have a poor content strategy — if at all. Companies cannot afford to settle for the status quo and let the problem get worse.
Document Management: Integral to Digital Transformation (and the ability to compete) Information systems are the foundation of modern IT. Thus, integral to any digital transformation initiative is the implementation of a flexible and intelligent information system.
Yet, while digital technology is opening the door to completely new ways of doing business, some organizations flounder in their ambitions and instead stand pat without improving existing ways of operating. Some $2 trillion dollars will be spent annually worldwide on digital transformation technologies, according to analysts, while as many as 70% of enterprises polled admit that they don’t have a coherent plan.
Over the past few years, document management strategies have progressed significantly, driven by other trends in the IT market and the more widespread use of intelligent information management systems. Organizations that do not embrace digital transformation will be less likely to outclass competitors and reach the pinnacles of their markets. Modernized document management is central to the digital workplace and the adjustments necessary to compete.