A quick update on the status of the Enterprise Search survey.

We now have well over a hundred respondents. The more respondents the better the data will be, so please help spreading the word. We’d love to have  several hundred more. The survey will now be open until the end of April.

But most important of all, if you haven’t already, have a cup of coffee and fill in the survey.

A Few Results from the Survey about Enterprise Search

More than 60% say that the amount of searchable content in their organizations today are less or far less than needed. And in three years time 85% say that the amount of searchable content in the organisation will increase och increase significantly.

75% say that it is critical to find the right information to support their organizations business goals and success. But the interesting to note is that over 70% of the respondents say that users don’t know where to find the right information or what to look for – and about 50% of the respondents say that it is not possible to search more than one source of information from a single search query.

In this context it is interesting that the primary goal for using search in organisations (where the answer is imperative or signifact) is to:

• Improve re-use of information and/or knowledge) – 59%
• Accelerate brokering of people and/or expertise – 55%
• Increase collaboration – 60%
• Raise awareness of “What We Know” – 57%
• and finally to eliminate siloed repositories – 59%

In many organisations search is owned either by IT (60%) or Communication (27%), search has no specified budget (38%) and has less than 1 dedicated person working with search (48%).  More than 50% have a search strategy in place or are planning to have one in 2012/13.

These numbers I think are interesting, but definitely need to be segmented and analyzed further. That will of course be done in the report which is due to be ready in June.

We are proud to present the first video on our new Vimeo channel. Enjoy!

Successful search project does not only involve technology and having the most skilled developers, it is not enough. To utilise the full potential and receive return on search technology investments there are five main dimensions (or perspectives) that all need to be in focus when developing search solutions, and that require additional competencies to be involved.

This holistic approach to implementing search technology we call Findability by Findwise.

A couple of weeks ago, me and some of my colleagues attended the Enterprise Search Europe conference in London. We’re very grateful to the organizer Martin White at IntranetFocus for arranging the event, and having us as one of the gold sponsors.

For me it was the first time in years I attended a conference like this, and while it was “same old, same old” for many of the attendees, for me it was enlightening to meet up with the industry and have a discussion on where we are as an industry.

There were mainly software vendors and professional services/consultants there, as well a few customers or actual users of enterprise search… and I think the consensus of the two days were that we in the industry STILL haven’t really figured out what we should do with the enterprise search concept, and how to make it valuable for our customers. We at Findwise are not alone with this challenge, but rather it is an industry challenge. There are some vendors who seem to be doing some good work of delivering real value to customers, and also there are a few colleagues to us in the industry that do good professional services/consultant work. At first it was a bit of a downer to realize that we haven’t progressed more during the 10 years I’ve been in the business, but at the same time it was very inspirational to see that we at Findwise together with a few other players, seem to be on the right track with our hard work, and that we have the position to solve some of the real industry challenges we’re facing.

As I see it, if we gather our forces and make a focused “push forward” together now, we will be able to take the industry to a new maturity level where we better solve real business challenges with enterprise search (or search-driven Findability solutions, as we like to call them).

My simple analysis of all the discussions at the conference is that we need to do two things:

1. Manage the whole “full picture” of enterprise search – from strategy to organizational governance, involving necessary competencies to cover all aspects of a successful Findability solution.
2. Break down the customer challenge into manageable chunks, and solve actual business problems, not just solving the traditional “finding stuff when needed” challenge.

I think we are on the right track, and it’s going to be a very interesting journey from here on!

Providing spot-on results in an Enterprise Findability solution is one of the hardest tasks when rolling out Enterprise Search. Sure, it is doable to work out a generic model for ranking results based on the organization’s most common requirements on findability in conjunction with available metadata of the information made findable. But is it enough?

The burning question is: How can you ensure that the generic relevance model does not get outdated once the Findability solution has been in use for a month, half a year, a year and the implementation crew is long gone?

Findwise recently released a large Enterprise Findability solution at a customer in the electrical power industry in Sweden. In the project we identified personalized and adaptive relevance as two key requirements for the findability solution to provide real, future-proof value-in-use to a large set of people with fundamentally different roles within the company. This blog post will focus on the latter requirement, adaptiveness: How can we make sure that an Enterprise Findability solution returns search results that become better and better as the solution is used?

Let user behavior improve the behavior of the search tool

The Enterprise Findability solution rolled out at the power company contains two features that, put together, build the foundation of a continuously improving relevance model:

1. A feature that promotes popular content given a query term – “social relevance”
2. A feature that continuously changes the relevance model by boosting the relevance of popular documents – “adaptive relevance

Social relevance

Inspired by e-commerce actors on the web, the delivered Enterprise Findability solution uses the logged behavior of its users to promote popular content. When an end-user searches for, e.g. “terawatt hours”, the solution by default offers search results ranked and sorted according to the generic relevance model. This is what any search tool would do. But this solution also uses search logs to promote popular content just as e-commerce sites have been doing for years – “Other people searching for ‘terawatt hours’ viewed ‘Current power production’ (intranet page), ‘Definition of terms in the electrical power industry’ (PDF document)” etc.

By combining the intel of the search logs (where the end-user behavior of an Enterprise Findability solution is constantly collected) and the best bets (editorially provided “sponsored links”) with the regular search result, end-users are presented with a rich set of information answering their original question from different angles. And the best part of it is that the social relevance feature constantly improves as the tool is used. People get better results as time goes by.

Adaptive relevance

In addition to the social relevance feature, the vast amount of real search behavior compiled in the search logs is used for improving the generic relevance model as well. The solution tracks changes in popularity of content and adapts the document-level scores of documents and web pages in the search index accordingly. If a document is accessed often through the search tool, the document will be deemed “more important” and start climbing towards top positions in the search result. And if a previously popular document becomes less popular as time goes by, the document’s impact on the relevance model is decreased. In the end, content that has great importance for a limited amount of time (such as news items and weekly lunch menus) will first peek and then dip in the search index. The search index and the generic relevance model attached to it will stay fresh.

From generic to personalized search experience

This blog post has pinpointed a couple of solutions for a continuously-improving, generic relevance model in an Enterprise Findability solution. Obviously, generic models are generic, i.e. good enough for the many, not perfect for the few. There are great ways to address personalization solving many of the role-based challenges of Enterprise Findability, but let’s leave that to another, future blog post. Stay tuned!

Canon has just published a study showing that half of the Swedish employees waste about 4000 Euros or 6000 USD per employee and year searching for information. The conclusion was drawn after interviewing over 1000 people of which over half used more than 10 hours per month looking for information. A quarter of the subjects in the study said that they spent up to 20 hours. These are very interesting numbers that show how profitable an investment in Findability can be.

Link to the article (only in Swedish)

Is “Findability” only a buzzword to describe the same thing as before when talking about search solutions, or does it bring something new to the discussion? I’d like to think the latter and this week I read a blog post describing the difference between search and findability in a very good way. I couldn’t have written it better myself

For the lazy one, I’ve picked a quote that is the key element in the post:

Findability: introducing the robot waiter

Imagine you’re in a futuristic restaurant and when the robot waiter approaches, you ask for ‘ham and cheese omelette’. In response he just shrugs his robotic shoulders and says ‘not found – please try again.’ You then have to keep guessing until you find a match for something you’d like to order.

Now imagine a second futuristic restaurant where the robot waiter says ‘Mr Grimes, how lovely to see you, the last time you visited you had A and B and gave them a 5 star rating. People who ordered x, also ordered y and found that the wines a, b and c went really well with it.’At first restaurant the menu was searchable (though regretably the ‘ham and cheese omelette’ query didn’t match anything), at the second restaurant the menu was findable.

To me, this analogy is spot-on. I dare to say that making content searchable is more of a technical issue while reaching great findability requries understanding of the business. Why is that?

Well, making a content repository searchable you “only” need to hook up a connector, index the repository and display a search box to the users. To succeed with this, it doesn’t matter if the content is movie reviews, user manuals, reciepes, a product catalog or whatever. What you need to know is the format of the repository (is it a SQL database, filesystem, ECM, etc.).

But if you want your users to find what they want in your repositories, business knowledge is a requirement. It’s true that you help your users find information by implementing technical stuff likequery completion, facets, did-you-mean, synonym dictionaries, etc. But if they are to be of any help you need to present facets that are useful, populate the synonym dictionary with terms used in your organisation,etc. For example, a good synonym file targeted towards nurses and doctors would be very different compared to one targeted at employees at an insurance company.

We have previously introduced Findability by Findwise, involving solutions that make optimal use of search technology to support and strengthen the business of our customers. In a series of blog posts we will present how Findability solutions can be deployed within different parts of your organisation. Initially I will focus on how efficient implementation of search technology can improve your customer service offering.

Ultimately, the goal of most customer service interactions is to increase customer satisfaction and thereby improve customer retention in a cost efficient way. In times when the amount of available information increases by the minute, one key success factor is to provide both customer service agents and customers with quick and easy access to relevant information. A Findability solution based on state-of-the-art search technology and optimised along the Findability dimensions will fuel your customer service offering in two primary ways:

1. Improved support to customer service agents
2. Improved online customer service

Findability in Customer Service

Improved support to customer service agents

While more traditional customer service interaction solutions tend to be based on a knowledge database, that needs to be built and maintained, a Findability solution is more dynamic in its nature and is based on a dynamic search index created by the already existing data residing in corporate systems. In other words, the solution makes optimal use of existing information and systems to support customer service agents in accessing relevant information. The positive effects are illustrated by the case study below.

Case study: Telecom call centre
Findwise implemented a Findability solution at a call centre for a large Swedish mobile operator. The solution introduced the powerful ability to search in the most important information source, which previously only had been accessible via tree-structure navigation.

The graph below presents the result of a test performed by the call centre agents to evaluate the new search function. The test encompassed a number of tasks in which the agents compared using the search functionality to the traditional navigation, in terms of both level of difficulty and time consumption in finding desired information. The graph shows that the agents found the search function very helpful, making the information both easier and less time consuming to find.

Search vs. Navigation

The most evident effects of improved support and information access via search technology are:

• Reduced handling time
• Higher first time resolution
• Reduced Tier-2 escalations
• Increased customer service agent satisfaction
• Increased agent productivity
• Less training needed to introduce new agents

In a white paper, Google has also pinpointed, and quantified, the above benefits of implementing a Findability solution in call centre operations, in this case fuelled by the Google Search Appliance (GSA) search platform. For example, Google states that handling time can be reduced by up to 20% on average and that is it possible to save up to 25% on training costs for each new call centre agent. The full article is available here.

Improved online customer service

Naturally a Findability solution can also improve your online customer service offering. Below I have outlined three solution elements that will help drive customer self-service and thereby deflect issues from being forwarded to the customer service organisation.

Improved search functionality
As in the case of agent support, a powerful search functionality that provides relevant information from all required sources in a user-friendly way will increase the ability of customer self-resolution.

Personalised user interface
Using the power of an enterprise search platform you can customise the self-service experience, in a dynamical way, to the individual and the incident to simplify and speed up the process of finding answers.

Dynamic FAQ
Self-service can also be fuelled by providing a relevant and updated FAQ section. The information can be made dynamic and include answers to the most recent questions by using both query log information, i.e. what users are searching for, and call centre comments as input to the FAQs.

For many enterprises, self-service is seen as the solution that can provide customers with the support they need while significantly reducing customer service costs. However, self-service must do more than just cut costs. When customers perceive self-service as simply a means to shift interaction costs onto their shoulders, it can reduce customer satisfaction. Customers need a self-service experience that provides them with higher levels of interaction convenience and information availability, faster issue resolution and more personalised interactions. A Findability solution including the above elements provides that.

The most evident effects of an improved online customer service offering gained from the use of search technology and search analytics are:

• Less number of incoming calls/e-mails
• Increased customer satisfaction
• Increased browser- to-buyer conversion rate
• Increased knowledge of user interests and behaviour (to fuel additional sales)

Visit our website to learn more about Findwise Findability solutions that make our customers truly benefit from state-of-the-art search technology.

BI and search is a never ending story.
A number of years ago Gartner coined “Biggle” – which was an expression for BI meeting Google. Back then a number of BI vendors, among them Cognos and SAS, claimed that they were working with search strategically (e.g. became Google One-box partners). Search vendors, like FAST, Autonomy and IBM also started to cooperate with companies such as Cognos. “The Adaptive Warehouse” and “BI for the masses” soon became buzzwords that spread in the industry.

The skeptics claimed that Enterprise Search never would be good at numbers and that BI never with text.
Since then a lot a lot has happened and today the major vendors within Enterprise Search all claim to have BI solutions that can be fully integrated (and the other way around – BI solutions that can integrate with Enterprise search).

The aim is the same now as back then:  to provide unified access to both structured (database) and unstructured (content) corporate information. As FAST wrote in a number of ‘Special Focus’: “Users should have access to a wide variety of data from just one, simple search interface, covering reports, analysis, scorecards, dashboards and other information from the BI side, along with documents, e-mail and other forms of unstructured information”.

And of course, this seems appealing to customers. But does access to all information really make us more likely to take the right decisions in terms of Business Intelligence. Gartner is in doubt.
Nigel Rayner, research vice president at Gartner Inc, says that ” The problem isn’t that they (users) don’t have access to information or tools; they already have too much information, and that’s just in the structured BI world. Now you want to couple it with unstructured data? That’s a whole load of garbage coming from the outside world”. But he also states that search can be used as one part of BI: “Part of the problem with traditional BI is that it’s very focused on structured information. Search can help with getting access to the vast amount of structured information you have”

Looking at the discussions going on in forums, in blogs and in the research domain most people seem to agree with Gartner’s view: search and BI makes a powerful combination, but the integrations needs to be made with a number of things in mind:

Data quality
As mentioned before, if one wants to make unstructured and structured information available as a complement to BI it needs to be of a good quality. Knowing that the information found is the latest copy and written by someone with knowledge of the area is essential. Bad information quality is a threat to an Enterprise Search solution, to a combined BI- and search solution it can be devastating. Having Content Lifecycles in place (reviewing, deleting, archiving etc) is a fundamental prerequisite.

Data analysis
Business Intelligence in traditionally built on pre-thought ideas of what data the users need, whereas search gives access to all information in an ad-hoc manner.
To combine these two requires a structured way of analyzing the data. If the unstructured information is taken out of its context there is a risk that decisions are built on assumptions and not fact.

BI for the masses?
The old buzzwords are still alive, but the question mark remains. If one wants to give everyone access to BI-data it has to be clear what the purpose is. Giving people a context , for example combining the latest sales statistics with searches for information about the ongoing marketing activities serves a purpose and improves findability. Just making numbers available does not.

BI and search in a combined dashboard - vision or reality within a near future?

So, to conclude: Gartner’s vision of “Biggle” is not yet fulfilled. There are a number of interesting opportunities for the business to create Findability solutions that combines BI and search, but the strategies for adopting it needs to be developed in order to create the really interesting cases.

Have you come across any successful search and BI integrations? What is your vision? Do you think the integration between the two is a likely scenario?
Please let us know by posting your comments.

It’s soon time for us to go on summer vacation.

If you are Swedish, Nicklas Lundblad from Google had an interesting program about search (Sommar i P1) the other day, which is available as a pod

Have a nice summer all of you!