The old saying, “It’s not what you know, it’s who you know that matters” is in desperate need of a 21st-century makeover.
In today's digital workplace, a more appropriate adage might be, “What you know depends on who you know.”
Pioneering businesses have recognized this and replaced outdated hierarchical management structures with dynamic cross-functional teams. That, in turn, has fueled unprecedented innovation.
Yet even as advances in collaboration and technology allow people to collaborate in ways unimaginable a generation ago, the pace of change and volume of data has made finding experts and their invaluable knowledge more challenging. That’s forcing many leaders to think outside the (search) box.
The average worker wastes nearly two hours a day looking for information. That’s 120 minutes when they aren't ideating, innovating or producing anything. They're just plugging words into an intranet search box hoping to uncover the most relevant, up-to-date results so they can do their jobs more effectively.
Think of it this way: the equivalent of one out of every four employees spends all day, every day simply trying to find critical information and expertise. Multiply that by 25 percent of your workforce by their average salary and you’ll begin to get a sense of just how important (and expensive) search has become.
2 Big Barriers to Search: Fragmentation and Expectations
There are plenty of barriers to successful enterprise search, but they broadly fall into two distinct categories: fragmentation and expectations.
The average modern enterprise has data spread across 329 business applications.
This explosion of apps has resulted in more choice and innovation in the enterprise than ever before. It has also meant specific lines of business and key vertical functions finally have the solutions they need to help them do their jobs better.
Across the board, routine work is being automated, which is freeing employees to deliver even more value. And they are — individuals and teams are thriving in the digital workplace.
But all of that goodness comes at a cost.
Organizations are struggling to efficiently achieve desired business outcomes, largely because of this technology fragmentation. It's more challenging to work across teams, find content and experts, and gain insights about how work is happening across the organization.
As a result, some estimate productivity growth has flattened and valuable corporate memory is getting locked away inside of all those tools. The proliferation of enterprise apps is clearly hamstringing search as well. There goes another two hours wasted. Tic tock.
That spectacular fragmentation is happening at the same time that people’s expectations for technology have radically changed.
Over the past few years, digital has become fully engrained into our daily lives. But consumer technology doesn't play by the same rules as the enterprise variety. Take Google's PageRank search algorithm. It has access to a vast world of free and open information and analytics, which can be used to constantly influence and refine and the relevancy of results.
Compare that to the enterprise, where there are hundreds of separate tools, each with their own complex entitlement systems, access requirements and varying support of APIs. Under those conditions, delivering an experience that meets user's expectations may seem next to impossible.
Is the Solution to Enterprise Search Problems in Sight?
As human beings, we have a fixed amount of attention and time we can devote to solving problems. However, as we have seen over and over again, technology can efficiently and effectively deal with a ton of information, and the solutions to today's barriers are not that far off.
Some forward-looking companies are already bringing more intelligence into their organizations through the latest AI-powered systems.
Artificial Intelligence and the Work Graph
The growing adoption of artificial intelligence in the workplace will eventually help internal search engines overcome the performance and accuracy limitations that currently prevent them from matching expectations from consumer solutions.
With organizational network analysis (ONA) as a framework, businesses are beginning to utilize machine learning and predictive analytics in order to glean insights from their "work graph" (the relationships between the people, content and communities within an organization) — an approach that closes the gap between expectations and information surfaced.
To get ready for that kind of enterprise search, companies need to knock down the barriers to information gathering.
A Little Help from the Hub
A collaboration hub can help defragment organizational silos by integrating and connecting solutions. This approach aggregates data across systems to better understand the relationships between people and content.
By using topic and sentiment analysis, content can be ranked based on the relative strength of people’s interactions. The enterprise search of tomorrow will emulate the success of consumer search engines like Google by going beyond keywords. It will analyze real people’s behavior patterns at work, and deliver results that are contextual to a company’s unique culture and organizational metadata (i.e. who knows what and who knows whom). [PDF]
Reason for Hope
Knowledge — and our ability to access it — has never been more important.
Keyword searches won’t cut it as a long-term solution in this era of non-routine work and information overload. As the amount of data continues to grow exponentially, organizations will look to artificial intelligence to take on many important business functions, including search.
As systems including AI, ONA and the work graph evolve, search will improve as well, eventually anticipating answers in advance. Only then will employees win back their time and companies their precious resources. And, in the end, isn't that a result worth searching for?