Productivity, Lost Time, and the Power of AI to Make Search Easier
How much of your life do you think you spend sifting through digital files just to find that one mislabeled 13th version of a deck, draft, film, or photo? For millions of workers around the world, those minutes are adding up.
According to a 2001 white paper by IDC, workers who manage, create, or edit documents for a company were spending up to 2.5 hours per day searching for what they needed. Sixteen years later, not much has changed. Despite leaps forward in file storage that could barely have been imagined when the paper was published, the challenge of locating information has failed to disappear.
In a more recent IDC white paper published in 2012, the authors share that a global survey of 1200 information workers and IT professionals found that they spend an average of 4.5 hours a week looking for documents. The people who need to find things the most, and who should be the best at finding them. Instead, they are spending half of those 4.5 hours searching for, and not finding, the files they need. Then they spend the other half recreating what they haven’t found.
The crux of the problem is that efficient storage isn’t the same as effective storage. Computer or, more recently, cloud-based storage are efficient methods for shelving information away. Whether it’s trivial or absolutely crucial, it’s theoretically all in one place. But between our hard drives, email, iCloud, Dropbox, and the dozens of other major cloud storage options, it’s like having a whole office full of unconnected filing cabinets. We might not need to rifle through physical drawers anymore, but moving from clunky paper storage systems organized by subject to digital systems organized by keyword hasn’t solved the problem of finding what you need. Just like with paper-based systems, naming something incorrectly or saving it in the wrong place can mean hours spent repeating work that’s already been done.
Ashu Syal, Head of Product at Diamond Inc., faced this frustration when he was interning at Scotiabank while still a student at the University of Waterloo. Despite the department being nearly paperless, a simple task could become overwhelmingly difficult if you didn’t know where to look for what you needed or, worse, if the person who’d created it didn’t put it in the right place or named it in a convention you weren’t aware of. This often meant Syal had to redo work that he knew was somewhere in their system, he just couldn’t figure out where.
He points out that “finding information is something you learn from your school librarian. You go to the library and learn about the Dewey Decimal system and how to find things. You have this perfect paradigm of how things are organized.” Then, he says, “You leave and enter the workforce and nothing is organized.” Suddenly, the systems that you’ve been taught to rely on for finding information no longer exist and you’re off on your own trying to sort through locations, folders, filenames, and keywords.
It can be frustrating and, Syal says of his experience, even isolating. During his internship, he felt that not being able to find information was never an excuse to slow down, so he wouldn’t tell anyone about the challenge.
With an increasing percentage of the workforce working remotely, and with teams often spread across the globe, the need for better functioning search technologies is becoming more dire. Furthermore, divisions between teams or offices can result in information that is isolated and practically unreachable for everyone outside of the core group. Collaboration tools have come a long way, but as more information goes into those tools, whether it be a Dropbox folder or an internal system, they get more crowded, more messy, and harder to navigate.
Syal, who is now leading the development of Diamond’s universal search tool, says that the difficulty is rooted in a divide between how we store information in our minds, and how it’s stored in our computers.
“There is a great amount of effort required to maintain a mental map of where your information is. The effort solely rests upon you and, despite even your best efforts to try and organize that information, sometimes you don’t have control of it.” Diamond, he says, can take some of that cognitive load off of a worker, empowering them to focus on their true tasks and to not have to worry about maintaining a complex mental model.
Time spent looking for things isn’t just a frustrating waste for the employee, though; it’s a waste for companies. Being able to access accurate information quickly is also the basis for good decision making, and not having all the information can mean rushed or ill-informed decisions. The cost is also monetary. The time workers spend looking for information can, at it’s worst, be as if 1 out of every 5 employees simply didn’t go to work. That’s 20% of the workforce scrambling around looking for mislabeled files in forgotten places.
Pierre Arys, the Founder of Diamond Inc., sees his product as a fix for this monetary and managerial mess. He believes that the number of documents we have is, “a continuous flow of data that keeps coming,” and the ways we try to sort through them are outdated and unnatural. Diamond offers a fix because it works with your mind by adapting to how you think and organize, rather than forcing your mind to work with it. McKinsey agrees with this methodology. Research published by the McKinsey Global Institute reports that creating a searchable record of knowledge that is integrated and inclusive can reduce the amount of time spent searching for internal information by up to 35%. “At the end of the day,” Syal says, “when you’re trying to get a task done, you’d rather work on it than spend your time trying to remember where the information you need is.” This might sound trite, but for millions of workers that’s just the problem they’re facing. Work should be about getting work done, not looking for what you need before you can even get started.
by Pippa Biddle (Content @Diamond Inc.)
Diamond uses AI to help users access what they need more quickly and more intuitively. Diamond’s models learn along with their users behavior, so each time a person enters a keyword or executes a search, they’re helping it get better.