Innovation Powered By Search

Slide 1.

Before we kick-off. Just, so I can get a feel, for the audience’s experience and knowledge of FAST, let me ask you some questions.

So, How many of you, have FAST installations in your organisation?

.. OK, quite a few then, no need for a sales pitch then. J

.. OK, not so many. Just yet. J

And, of those you, who do not have FAST installations. Hands up if you have you every used FAST?

Well, you may have unknowingly would you believe.

If you have every performed a search at the FT.com. Or perhaps purchased equipment at Dell.com. Well then, you have used FAST. You just didn’t know it.

Just as Rolls Royce is the unnamed engine behind the World’s largest and most powerful aircraft. FAST too is the unnamed engine behind some of the world’s most Mission Critical Applications.

Slide 2.

And as you will see later on in the presentation. the solutions we power, here, at these Market Leading companies. Are far evolved beyond simple intranet search solutions.

Slide 3.

I have 4 key messages that I want to share with you today. And they are.

1.The evolution of Information Management.

Moving from a Data Centric approach to a more User Centric approach.

Then we will look at .

2. Why Search 1.0 is outdated. And, How upgrading to search 2.0. Will enable us to address, a consumer-centric information management strategy.

Next we will look at.
3. How Microsoft’s Search will enable this end-user empowerment and allow organisation to truly unlock their tangle of data.

And finally.

4. We will look at Some examples of where FAST is enabling organisations carve out competitive advantage.

.. So let's get started.“

Slide 4.

The first thing I want to share with you is the shifting the focus from the owners of the content to the consumers of the content.

Slide 5.

What we see here in the graph is a transition of information control.

Away from a centralized containment and protectionism of information.

To a diffusion of information from a collaborative network of empowered employees and individuals. Each of which, themselves act as both consumers and producers of content.

An example that illustrates this shift. Is the movement of News media from the printing press. Then to online newspapers. And today individual journalist using the likes of Blogger and Twitter to report news.

And this brings enormous value in terms of speed, flexibility and reduced cost.

This was most recently demonstrated during the Mumbai terrorist attacks in India. Where the Breaking news was first revealed on twitter before television. And subsequently the most comprehensive news was ascertained from Twitter and not traditional media structures.

This transition of information control requires that IT moves with it and moves FAST.

We need to shift from the old mindset: I have all this data, how do I best store it and lock it away in a structured and manageable manner.

To the new mindset: I have all these ‘Information Assets’, How do I ensure I get the right intelligence. to the right people. at the right time. to make the right decisions?

Slide 6.

So that was the Paradigm in Information management and that was the first thing I wanted to share with you today.

The second thing I want to share with you today is. The paradigm shift required in Search in order to satisfy this new Information Management model.

Slide 7.

I’m sure we are all familiar with this search layout above. Popularised by the web's premier search engines.

The original search engines if you can remember them were Lycos, Excite and AltaVista. These were surpassed by Google who had the novel idea of using inbound links to calculate the authority weighting of a web page.

The premise held, that for 2 pages containing similar content. The page with the greatest number of links to it from other sites. Should have the more relevant content.

Using an analogy from the book world. For any two books on a similar topic. The one with the greatest number of citations - references to it – should be the more trusted.

However, CRM data. Office Documents and Emails within the enterprise are not linked. But that’s a whole other challenge for Search 1.0 and out of this scope.

Google’s model is very easy to use. You simply pop key words in that box up there and it regurgitates millions of links to matching documents via a one-size-fits-all relevancy.

I like to call it the Mac Donald's of search engines.

Many people turn to it for answers because, Let’s face it - Its quick. Its easy. And it satisfies.

But just as not every taste is satisfied by Mac Donald's.

Equally not all information requests can be satisfied by Google.

There are many unique, specialist and diverse tastes.

Especially within the enterprise. Where there are different departments, roles, offices and geographies have their own interests and needs. that a Mac Donald's type search will simply not satisfy!

We therefore need a more effective model to accommodate these diverse tastes and requirements.

Slide 8.

So, Just in summary of what Search 1.0 actually is.

It is a monologue interaction with a system that takes a users keywords. And responds with a directory of millions of references to where an answer may be found. Or may not!

There is little or no use of insight, no understanding or care for the users intent. The users role. Or the users context.

Users are required to rejig their queries and Yo-Yo in and out across the surface of the results corpus. In the hope of finding more accurate and better information.

In the previous example a search for project management brought back over 23 million results. So if we were to look at only the first 4 pages that would still be less than 0.00002% of the available information. How can we be certain the information we are overlooking is not the most relevant.

Slide 9.

With FAST we have developed a system that plugs the holes left by search 1.0 to provide a richer and more effective consumer-centric user experience. We don’t see search as an excercise to get the best matching documents to the users key words. We see it as a process in which we match a users intent to the underlying content we know exists.

This starts with the enrichment of content. Unlike other search vendors that simply capture the content and dump it into the index. We can enrich the content by passing it through a series of content processing stages.

We see returning the documents as the easy part. We go one step further and from those documents, extract intelligence, facts and important people, places and companies. So the user is not required to.

Unlike other solutions, we provide a fully open and flexible relevancy model. A as opposed to our competitors one-size fits all, black box approach to relevancy.

We look at - Who are the users? What are they trying to achieve? What are they interested in? What are they not interested in? And based on this architect the most relevant relevancy model.

And we engage users in Dialogue. We provide methods that allow them to quickly slice open a result set in various ways to extract only relevant intelligence.

Slide 10.

So in summary.

So, rather than users having to YO-YO in and out of top 10 results. Re-jigging their query to find the relevant information. FAST provides an effective way of slicing open the results corpus to all users to EXPLORE the information as they desire.

And, as opposed to indentifying documents that contain the keywords and dumping out millions of links to these documents. FAST engages users in dialogue with the data to help them sharpen their query and thus provide the most accurate results.

To illustrate with an example. Lets say I have come to a new hotel in a new city and I want to go to a nice restaurant. There are two concierges at the counter. One wearing a Search 1.0 badge and one wearing a search 2.0 badge. I ask them both for a nice restaurant to dine at tonight but they both respond differently.

Search 1.0 concierge picks up a yellow pages directory of all restaurants in town and slides it over to me. And tells me to have a look through it for a restaurant.

Search 2.0 concierge engages me in conversation. What cusine would you like? How much would you like to pay? How far would you like to travel?

Slide 11.

What you will see here is an example of search 2.0 as powered by FAST.

As we cannot show you internal applications for non-disclosure reasons. I have chosen Globrix, a prpoerty search engine because it is something that we can all relate to.

ACCESS TO AGGREGATED CONTENT FROM 90% of the PROPERTY SITES VIA A SINGLE LOCATION SEARCHBOX.

Transforms UNSTRUCTURED queries into STRUCTURED queries (Advanced Query Processing).

EXTRACTS keywords and entities from UNSTRUCTURED LISTINGS (Advanced Query Processing, Entity Extraction) .

Navigation ADAPTS to users interests (Contextual Navigation) .

Ability to narrow/refine results set through INTUITVE VISUAL NAVIGATION (Advanced Results Processing, Geo-Targeting).

Ability to save/hide properties and SAVE SEARCHES and be ALERTED of new listings (Monitoring and Alerting).

Revenue via adverts powered by AdMomentum.

Slide 12.

So that was Search 1.0 versus 2.0 and that was the second thing I wanted to share with you today.

The third thing I want to share with you is Microsoft’s Vision for Search 2.0.

Slide 13.

So, this slide illustrates Microsofts vision for Search 2.0 within the enterprise.

Enterprise Search is about connecting the right people. To the right information. At the right time. To make the right decisions.

There are 3 pillars that encapsulate this vision of the Microsoft search experience:

- firstly, visual engagement. to identify trends and insights form your data.

- Secondly, Conversation handles. that drive dialogues with the data in order to guide users to answers.

- Finally. Search should be actionable. Search is simply the first step in performing a task. We want to assist in that task as best we can. Search does not become useful until we do something with the newly attained information.

An example of actionable search would be the ability to email a document URL to a colleague. Save a document to your search briefcase. Create a power point deck directly from your search results.

Slide 14.

In order to achieve this vision. search innovation will focus on 3 core areas:

User Interaction Management – Engaging users in interactive dialogues with a personalised relevancy. That addresses your tasks. Your role. Your context.

Contextual Matching – Continuing to architect scalable and easy to manage open & flexible platforms.

Content Analytics – The continued development of exstensible frameworks that enable organisations to cleanse, Normalise and enrich data before it enters the index as well as extracting inteeligence, trends and entities.

Slide 15.

So that was Microsoft’s vision for search and that was the third thing I wanted to share with you today.“

The fourth and final thing I want to share with you is some examples of where FAST is using search to drive innovation within market leading organisations.

Slide 16.

As in the first slide, where I described the different organisations, where you may not have known that FAST was behind the scenes.

There exits too, many business areas that you may not suspected FAST was providing solutions.

FAST is more than a Search Engine as it provides capabilities to build solutions to support various business initiatives and or solve business problems.

An initiative can be as simple as conventional site search or it could as innovative and complex as mining transaction information to identify fraudulent activity.

If you are to take anything from this presentation it is this.

As much as Google, may want you to believe it. Search is not simply about typing in queries to a search box to get back millions of links to documents.

At FAST Microsoft, we use search technology to SOLVE CRITICAL BUSINESS CHALLENGES.

• It is about solving business problems that require.

• Finding Documents.

• Matching Content.

• Cleansing Data.

• Classifying Content.

• Aggregating Information.

• Extracting Intelligence.

• Identifying Trends.

Here, typically the use of other technology such as databases is extremely costsly or impossible.

Slide 17.

An example of search beyond the search box, keywords, text-link paradigm can be viewed at the New York Times “Topic Pages”.

These are self POPULATING AND SELF ORGANISING PAGES that are automatically constructed using search.

Each of the frames, is what we call a searchlet. These searchlets carry some keywords. In this case “climate change”. They point to different content repository in the back-end of the New York times. These may be editorial content. User-generated content. Multimedia repositories. Picture databases.

For each repsoitory they extract all content from that relates to “climate change”.

This contented is presented together to form a “Topic Page”.

They exist for countries, politicians, celebrities et cetera.

Applying this to the enterprise we could have pages populating for different projects. Different departments. Different initiatives.

Benefits:

• Hundreds of topic pages – dynamically-generated pages that give users an overview of content on a certain topic
• Up-to-date information – refreshed with each viewing.
• Minimum editorial and site design workload – search as the portal.
• Increase stickiness through contextually related content.

Slide 18.

At Dell.com, a FAST customer. They utilised our Search Business Centre to analyse logs and report on the search activities. They found that generic searches for 'laptop' where quite prominent. This is a very generic term so it is difficult for a user to determine the relevancy of one over the other, but interestingly those laptops at the top of the stack yielded more sales. Armed with this information Dell were able to boost those products with the greatest margins to the top of the stack. This has lead to higher conversions on high margin items and increased profits.

Dell have also linked FAST flexible relevancy API to their ERP system. Here a rules engine promotes items based on availability and profit margin. If surplus, promote for increased conversions. If out of stock, temporarily block from results. For a generic search like laptop or server Dell will promote to the top of the results. They items with the greatest profit margins for Dell. Smart eh.

AT NASA Fast have provided a measurable return on investment with major improvements in data access and retrieval. Reducing days of research and retrieval time to minutes.

FAST also and provides the invaluable benefit of capturing and preserving engineering decisions, best practices and lessons learned which prior to this capability were in large part lost as consequence of workforce attrition.

NASA was initially using a competitor until they realised that they were haemorrhaging money trying to configure and tune the black box . Every time they needed to tune the engine, they had to bring an integrator to do so.

They also had several other search engines in use like Verity K2 and Google and wanted to standardize on one platform.

They now use FAST to provide recommendations to researchers in similar domains.

Person to Person recommendations. You and your peer are working on Shuttle cooling systems, your peer enjoys these documents. You may also enjoy these documents.

Item to Person recommendations. You have profile X,Y,Z. These documents may appeal to you.

Item to Item recommendations. You search for this item often. These items are similar to that item. You may be interested.

Slide 19.

Telstra Voice to text search . Globrix maps. Contoso sliding search.

Slide 20.

FAST is used by Dept of Agriculture in the United States to help fight against illegal plants being sold over the Internet.

FAST is also used by an Asian Enforcement agency to monitor child pornography, and by the Norwegian Toll and Excise department to monitor transactions in and out of the country. A German police force uses Fast to ensure they can match incidents to people across a myriad of different storage systems located in multiple police stations