Ask most knowledge workers what they find most frustrating at work, chances you won’t have to speak to many people before ‘not being able to easily find the information to perform my job’ comes up.
In fact, depending on which study (although most research seems to broadly agree) the average information worker spends between 26 and 30 hours a week looking for and obtaining information. For clarity, that’s not surfing Facebook, but searching for the very information that enables them to do their job effectively.
Interestingly when you break down most needs for information, people tend to be looking for one of just six things:
- work product (usually an MS Office document or similar)
- a system, for example to book a room, file their expenses or report an IT problem
- a policy or reference document where the items name is known, but its location is not.
- a person (or the contact details of a person they already know)
- A collaboration destination (usually a team working space or community)
- a record of some sort (usually a customer record or artefact)
Focusing on the first, work product – the need to retrieve previously generated content is clear. I discussed this in a previous post “Doing work is harder than it should be – but what’s the problem?” where I spoke about how every day across an organisation, numerous documents, thoughts and ideas are generated, collaborated-on and then lost.
Until recently the only way to retrieve information was to search, and over the years, the phrase I’ve heard the most in relation to search is why can’t my organisation’s search just work like Google.
And it’s a fair question. For years as knowledge and information management professionals we’ve defended our inability to do just this with a complex series of arguments, all of which were true enough at the time. But the truth is the web, like most organisation’s repositories, is full of useless, low value information, but most of us never see it because search engines hide it away until that one time an obscure piece of content is relevant to us.
Generally one of the reasons public search engines are able to display results seemingly so accurately is because millions of others have run the same search before, which allows their algorithms to work out and refine the best answer.
Indeed public search engines like Google have another trick to refine their results, each search consists of the typed search string, but when combined with the user’s location (often taken from the user’s IP address) and previous searches from the same IP address allow the search engine to have a pretty good guess at who’s using the computer and where they are located, city, country and organisation/user type. Indeed Google has profiled the users of its services further, so they now can say with a relatively high degree of accuracy on many demographic items including your sex, age, interests.
The search engines used within organisation’s could learn a trick or two from their publicly accessible cousins, far from being worse than their public counterparts, the organisational search engine has access to far more meta data about each of its users. For example most searches are conducted from behind an authenticated portal or digital workspace, that means the search engine knows exactly who initiated each search, but they have access to more than that…
If the search is part of integrated part of the digital workplace (any why wouldn’t it be) then the the search algorithm knows not only the name, but the division, grade, skills and interests of the user.
This is important because if the search knows the background of each user it can refine results before they are displayed. An example might be if I as a PM working in IT search for Network Analysis Requirements Document, the system could return results that were based upon my department and role (so I’m probably looking for IT authored documents) and those documents that are official “Requirements Documents”.
If you expand the concept even further the system knows every document the user viewed or authored, every conversation taken part in and every comment ever added. Building further still, the digital workplace knows who the user is connected to through a LinkedIn type professional connection capability, but more over it also knows the division, grade, skills and interests of each of the user’s connections.
And this is where the genius comes in, or more precisely where the humble “Like” can help solve the world organisation’s search problems.
Now I don’t know who came up with the concept of the “like” function, now synonymous with Facebook and YouTube videos, but the “like” allows individuals to share an emotive response with the originator without needing to find words.
By adding a simple like to a document, or for greater accuracy a star rating between let’s say one and five the user can add their personal reputation and collateral to a piece of content.
So as in the example above, lets say there are 50 Requirements Documents, all have been added in the past 6 months so should be current. But two have been authored by people in my Department and five of my colleagues (not connections) who share the same Job Title and Department Head as me have liked the document, as well as some other users who are more senior to me have also contributed to the document history. This propels these two documents to the top of the list, combined with an electronic scan of the documents to check they do actually contain relevant content.
So the future of search, is actually Social where the search engine uses all the social data available to it as possible value indications can massively improve search for everyone.
Of course this relies on the uses of the system storing their work product in the system and employees understanding the real value of the like feature. And unlike the traditional ‘pull’ Search (where we actively pull the search engine for information), I believe there is an equally, if not more valuable system push search of information driven by our role and our known interests, that is not what you are searching for, but would be interested to see if you had the foresight to go look for it – in the future, perhaps the role of push search is somewhat more limited than it it today.