Revolutionize Your Approach to Knowledge Management
Ninety percent of the world's data has been created in just the last two years. But when it comes to information, there is no immediate benefit to simply amassing exabytes of content. The real gains come when organizations are able to translate, understand and apply the insight that is contained within this flood of information.
One of the main challenges posed by today's information explosion is that content is fragmented into disparate "silos," such as file servers, collaboration suites, email systems and other repository types. Information is also being migrated to cloud deployments, effectively creating another silo. Traditional KM systems, however, are not equipped to derive intelligence from information scattered across different systems. Unfortunately, when an organization is unable to leverage information for its highest value, this can hinder its competitive advantage.
Getting the Most Value From Information
Within the volumes of big data, businesses today have more information than ever before about their employees, their competitors and their customers. This puts a greater emphasis on search capabilities to not only understand information generated by users, but also understand how the information flows and connects between users. In essence, users today each create their own unique social network. Systems that can leverage this shift enable businesses to get more from their information.
Traditional KM vendors have focused on the capture side of the equation: making people enter their information into document management systems, and relying on that process to provide intelligence. But that is not how people work today. To accommodate these changes, a different system is needed—one that mirrors the way people work and think.
In today's information-rich organization, there are three key capabilities that an intelligent search technology must support to deliver effective knowledge management in the era of big data:
Build a knowledge graph of the organization by analyzing social networks and deriving people's expertise based on employee behavior. This will expedite knowledge transfer, reduce duplicate efforts, and encourage a collaborative work environment. Generating a knowledge graph is a complex process, in the same way that people's relationships are multi-faceted and ever-evolving—it cannot be owned by a single content management system. That's why your search technology must understand relationships by analyzing a variety of information such as communication patterns, work groups, project hierarchies and other attributes.
Deliver contextualized search results personalized to the user. Without a context-aware solution, the same search query will mean different things to different people. The same search query could even mean different things to the same person when executed at different points of the day or on different devices. Your search technology should use context and profile data to not only personalize the delivery of content, but anticipate your needs and proactively push information.
Search across any repository from any device. Information is becoming increasingly fragmented, and the boundaries between personal and work productivity is blurring. In our BYOD world, people are putting personal and work items in Dropbox, Evernote, Yammer, Salesforce, Google Drive, and accessing content from desktops, mobile devices, tablets, "phablets" and any of the latest devices in the market. They are merging personal and work identities in their social networks. Your search technology must be able to access data from all systems, and understand the data in all its disparate forms.
Search for Today's Worker On-the-Go
Today's workers are increasingly on-the-go, embracing the newest mobile technologies to stay connected and productive, as they continue to fuel the migration of content to the cloud. In addition to driving the great shift of data to the cloud, there is also fragmentation of knowledge among multiple systems and repositories. Information today has many addresses. It lives in email, on mobile devices, in Dropbox and Evernote, and in whatever applications people may choose to install. The consumerization of content has also meant that devices and applications are used for both professional and personal purposes.
An important distinction to remember about information growth is that it is not just about documents. We are becoming a multimedia-focused world—watching and listening more and reading less. Many meetings are now conducted remotely over video, and training sessions are often recorded. This means your search technology is required to handle these new and pervasive content formats. The number of files, images, records and other digital information is predicted to grow by a factor of 67 from 2009 to 2020, with corresponding growth of IT professionals globally by a wimpy 1.4.
By eliminating barriers between repositories, devices, communication channels and deployment choices, you free the worker to be fully engaged and productive wherever they are. This search experience should be seamless and yield consistent results. To experience real agility, you must be able to search any repository from any device, and then search any file, regardless of its format.
This means your search technology must first have access to the system. If you can't search it, you can't find it. Secondly, your search technology should be advanced enough to derive contextual and conceptual signals. If you store all facets of your life in the cloud, for instance, is your search technology smart enough to return work-related items at the top when you query a common keyword? Or at least categorize them according to concept? Can it separate the relevant items from the noise?
There are many advantages to uniting a fragmented data landscape. Most obviously, the ability to find an item quickly will increase a worker's productivity. But it can also help organizations monitor social media or their email systems—even analyze embedded or attached rich media, to flag anomalies and find confidential data.
Successful search technologies should operate like a conversation, tailored to the user. Much like in the real world, the phrase "tips for conflict resolution" can mean different things depending on the location or context. For instance, at a customer site, you would want to learn more about customer service-oriented advice. At the office, tips geared toward coworker or managerial resolutions. And at the vendor site, better communication of goals. For this reason, search technology should also respond differently based on your context. Given today's paradigm of the ever-mobile professional, it's easy to see how big data can use a wide range of contextual elements—time, location, content, even weather—when delivering search results. This idea is an important one for today's organizations—one that can be applied in a wide range of business applications.