People have become used to having a world of information at their fingertips. ‘Just Google it’ is a personal mantra for many of us once we start doing anything in front of a computer screen – whether its checking the latest news, looking up movie times, comparing prices, finding a holiday destination, or getting details on a new product. But that doesn’t necessarily happen in the workplace where internal information assets can be massive and hugely complex – and not at all easy to access.
New research commissioned by Smartlogic and conducted by MindMetre Research demonstrates clearly that, in far too many cases, organisations are simply not meeting the ‘enterprise search’ expectations of their own managers and directors. Enterprise search is defined as the process for finding the information you need from within your company, quickly and accurately.
The survey of more than 2,000 managers and directors in the UK, US, France and Germany found that 52% cannot find the information they seek within what most define as an acceptable amount of time, using their own internal search facility. A ‘good search experience’ was described by nearly two-thirds of those surveyed (65%) as taking less than two minutes. Unfortunately only 48% of respondents reported being able to achieve that result in their own organisation – a glaring 17% gap between their expectation and their enterprise search reality.
The figures demonstrate that, even with the arguably weak ‘within-two-minutes’ timeframe as a benchmark for a ‘good search experience’, an alarming proportion of enterprises – more than half – are failing to meet even this basic standard with their own internal search platforms. What’s more, over a quarter cannot even meet the lowest benchmark offered in the study – completing a search within four minutes – which nearly 90% indicate is an unacceptable timeframe for finding a result.
This failure of enterprise search platforms to meet expectations in too many organisations is largely the result of information management evolving in silos and the fundamental lack of a unifying technology that surmounts this problem. Much of the information held by enterprises (such as product sheets, business pitches, white papers, research, briefings, reports, emails, memorandums, letters, blogs, client files, articles, and other key documents) is typically saved in a range of formats, stored on various sites by different departments, and tagged by countless people who each have their own methodologies, individual priorities and opinions.
Overcoming these issues and improving ‘findability’ to enable information recovery is crucial for nearly any organisation that relies heavily on accessing information assets to serve its marketplace or community, generate income, create internal efficiencies, and enable the smooth running of day-to-day operations.
Most organisations have powerful content management platforms and search mechanisms for leveraging information assets – including Microsoft SharePoint, FAST and Google Search Appliance – but releasing the full potential of these systems requires additional solutions. Taking a ‘semantic’ approach to enterprise search can be central to enabling ‘findability’ for organisations hoping to harness the full power of their information management systems.
Any enterprise search solution that really works for a business needs to have the capability to work out the context of any document or communication to unlock its full meaning, so that a search does not get clogged by unrelated pieces of information that simply share some of the same terms. That means creating a ‘semantic model’ of the relevant business vocabulary – called an ontology – which brings together all the key terms that an enterprise would use in its business and forms a basis for information classification so that documentation can be placed in context when it is being searched. This enables an enterprise search platform to bring up only directly relevant documents, experts, references, and other related materials.
The ‘semantic model’ can then be used to drive an automatic metadata classification process, a fundamental step in the information recovery process. This helps eliminate the human biases, inconsistencies and errors that crop up within most organisations because documents have been tagged manually – if they have been given electronic labels at all. And if an organisation has failed to tag its archive of documents, the manpower costs back-tagging all its business information manually would be huge – to the point of being impractical in most cases.
Instead, an organisation that aims to make all its information recoverable through its enterprise search facility needs to be able to apply metadata consistently, repeatedly, economically, according to its standards and in a way that can be demonstrated to be trustworthy and accurate – as well as affordable. An automated system is arguably the best solution. Semantic software can be put in place to scan documents and accurately tag them with the correct metadata, so that they can be placed in context and terms can be cross-referenced to ensure that all relevant information comes up in a search.
Making internal search work is essential for any organisation, as failure to be able to effectively locate and utilise information assets will continue to be an important issue. Getting more out of all information resources to hand will be critical to all enterprises as they reach out to their markets in the face of a tough economic climate.
