Google.com consistently commands over 90 percent of the UK’s online search market, which has not only left its competitors scrambling for the last remaining morsels of market share, but has also sparked EU investigations into whether or not the search giant is acting in an anti-competitive manner.
However, it cannot be denied that Google offers an unrivalled service in the consumer search market. This has created an opportunity, argues Matt Eichner, Google’s general manager of enterprise search, to learn from Google’s experiences in this area and deliver similar services to the enterprise.
“If you look at Google in the search space, we are taking that consumer expectation that we developed on Google.com and packaged both the user interface and the algorithms behind it into an enterprise appliance,” says Eichner.
Google’s search appliance is an out-of-the-box solution that integrates with enterprise applications and can scale to support billions of documents. It can search 220 file types, including HTML, PDF, Microsoft Office and Lotus, and is supported by a number of security protocols, including single sign-on mechanisms.
Eichner says: “The appliance offers you an out-of-the-box experience that delivers the relevance that you come to expect from Google.com. It can be very powerful and it takes into consideration the enterprise context, such as security rules.”
“At Google we have billions of queries from Google.com coming in every day that we are able to analyse and deliver an enterprise tool that balances human behaviour and search relevance.”
Big Data is in the eye of the beholder
Advanced enterprise search capabilities are being driven by the growth of ‘Big Data’. This sees enterprises having to deal with unprecedented amounts of information due to increased capabilities to record data through mobile, online, social media and sensors.
Eichner describes Google as the world’s “biggest big data problem”, which has allowed it to focus on performance and scale. However, he is also keen to point out that it isn’t only organisations with billions of documents that need a sophisticated search tool.
“Big data is in the eye of the beholder. If I gave you 500,000 documents, which doesn’t sound like a lot, and I said to you find something in there – you would look at me and say, 'can I use a search engine?'” he says.
“From your perspective, 500,000 would be big data. We often lose sight of that. Insight needs to be delivered when you have more data than you can process. This can come in the form of 500,000 documents or hundreds of millions of documents.”
He adds: “The real mandate in the world today is to get up the competitive stack by being more knowledgeable about what you are doing more quickly – that’s the nature of the information economy.
“The imperative is to get better at assimilating the knowledge you have and acting on it. The inverse of this is if you have big data and you don’t have insight. That’s the equivalent of saying ‘I’ll take a guess, I won’t use the information and I’ll take a guess’”.
Open source does have a role within the enterprise
However, despite Google’s undeniable advantage in search experience in the consumer space, open source projects, such as Apache, have been making strong headway in the enterprise market. Eichner admits that these open-source tools can be extremely powerful, but also suggests that for searching across multiple applications the in-house skills required on an open source project would be too much of a drain on many organisations.
“Open source does have a role within enterprise search. If you have a lot of engineers and your goal is to adapt search to one specific application, then it works well. The Original Equipment Manufacturer (OEM) market is a classic example where companies have the internal engineering departments and competencies to manipulate the search outcome to be very specific to a single system – open source is a great for that,” says Eichner.
“However, when you like the idea of universal search and searching across multiple systems, much like Google on the web, I think it falls down. It doesn’t have the search relevance capabilities and it requires expensive PhD expertise to establish how that relevance should be calculated.”
Open source tools also then require enterprises to fine-tune the infrastructure, the hard drive and the CPU, something Eichner says can be really hard when compared with an out-of-the-box alternative.
Finding talent isn't easy
Another thing that is difficult is finding highly skilled scientists and engineers – which Eichner refers to as PhDs.
“One of the hardest things Google has to do is hire talented people. Imagine if you were trying to recreate the thousands of engineers at Google focused on search within your organisation – that’s hard,” says Eichner.
“It’s not that you couldn’t. Facebook has a great engineering team, but the question you have to ask is, is that you core competency? Hopefully your PhDs are doing something that is more related to your core business, not search."
He adds: “Google’s intention is to deliver the value of those thousands of Google engineers back into the package so that you can start at a higher threshold. You can still tune it from there, adapt it to your needs, but your starting point is going to be a lot more mature.”
Finally, Eichner is keen to urge organisations to consider the before and after value of implementing an advanced enterprise search tool, something which he says doesn’t happen often enough.
“I wish people would do this because it would allow them to invest more in advocating information visibility within their enterprise," he says.
“I sometimes use the example of two search boxes and put them next to each other. I’ll then say the one on the left is cheaper and the one on the right is more expensive, which one do you want? I can see people thinking the one on the left."
He adds: “I’ll then use the same example, except with two airplanes. You can then see people’s answer start to change because now it is important and it matters. That’s the challenge for us.”
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