Medium 9781449330446

Enterprise Search

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Is your organization rapidly accumulating more information than you know how to manage? This book helps you create an enterprise search solution based on more than just technology. Author Martin White shows you how to plan and implement a managed search environment that meets the needs of your business and your employees. Learn why it’s vital to have a dedicated staff manage your search technology and support your users.

In one survey, 93% of executives said their organization is losing revenue because they’re not fully able to use the information they collect. With this book, business managers, IT managers, and information professionals can maximize the value of corporate information and data assets.

  • Use 12 critical factors to gauge your organization’s search needs
  • Learn how to make a business case for search
  • Research your user requirements and evaluate your current search solution
  • Create a support team with technical skills and organizational knowledge to manage your solution
  • Set quality guidelines for organizational content and metadata
  • Get an overview of open source and commercial search technology
  • Choose an application based on your requirements, not for its features
  • Make mobile and location-independent search part of your solution

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12 Slices

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1. Searching the Enterprise

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It seemed like a normal day when you arrived at work and turned on your computer. Then, the phone rang. Colleagues of yours were just about to go into a meeting with a prospective customer, and they needed details about custom software they had proposed installing. You went to search for those details, and they werent in the standard specification sheet, nor were they in the release notes, nor were they in any of the first fifty results your companys search tool produced.

We have to make many decisions every day. Each of those decisions required enough information to make the decision as risk-free as possible. In many cases, though, we probably did not have the time needed to find all the relevant information. We probably prided ourselves on being good enough managers not to need information; our experience enabled us to make the decision!

Every day, however, people make the news headlines because they made the wrong decision. The financial meltdown on 2008 was arguably an information problem. Loans had been made to people purchasing homes without adequate security. The pressures of making sales targets led to an inadequate review of the circumstances of the people asking for loans and senior managers in the banks had no information about the scale of the problem. While your decisions may not result in you making the news, a failure to make the best decision possible on the basis of the best available information could be bad news for your career.

 

2. Enterprise Search Is Difficult

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Most people think that search is easy. All you have to do is type a word or two into the query box on Google or Bing. In a fraction of a second, thousands, if not millions, of results are ready to review. You dont know and dont care about how this was accomplished, and for searching the Internet thats acceptable. Even if you knew all about PageRank, BigTable, Markov chains and the teleportation matrix it would be of no value in using Google and the situation is similar with Bing. The nice thing about searching the web is that we are easily satisfied. Even if you dont find quite what you are looking for you will find something close enough to be useful and forget about the initial disappointment.

Enterprise search is much more challenging. From the evidence presented in Chapter1 it is clear that there is a significant dissatisfaction with enterprise search applications. One of the reasons for this is that the height of the satisfaction barrier. If you are looking for a specific document or specific information and cannot find it then your satisfaction is zero. Finding something roughly similiar is rarely good enough to risk your career on.

 

3. Defining User Requirements

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All effective systems are based on a good understanding of user requirements. We want it to work like Google is an aspiration and not a user requirement. In this chapter a range of approaches are suggested to help define user requirements. There is no single approach that is better than the others and usually a blend of several is required. However a balance needs to be kept. At one end of the spectrum is the Google approach, in which innovations are tested out on customers and if there is a positive reaction then the innovation becomes a Google product. Apple is at the other end of the spectrum. The late Steve Jobs commented that Apple needed to provide customers with what they wanted even though they dont know what this was.

One of the challenges of enterprise search is that almost everyone uses Googles public web search as the definition of best practice. In Chapter2 I pointed out that this is not a useful approach to defining the requirements for enterprise search but any discussion about user requirements will almost inevitably migrate towards a discussion about Google.

 

4. Planning for Search

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Given the potential benefits and challenges of enterprise search it is surprising that the 2012 Findwise Enterprise Search and Findability survey indicated that only 14% of respondents had a search strategy, though 30% were planning to develop a strategy in 2012/2013. This result is consistent with the Digital Workplace Trends report from NetStrategyJMC and tends to support the view that search is not seen as a business-critical element.

Search does need to be planned. It is technically challenging, users have both high expectations and a high dependency on the success of search and there is going to need to be a substantial investment in personnel for the search support team. As you read through this book you will find there is just one single theme. I call it Whites Rule of Search Investment:

The impact of search on business performance depends more on the level of investment in a skilled team of people to support search than it does on the level of investment in search technology.

There is a corollary:

 

5. Search Technology Part 1

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There are two fundamental components of any search application. An index of documents is created and then a search query is made which identifies which of those documents satisfies the enquiry. If only that was all there was to search process. The reality is that any search application consists of a set of modules, each of which carries out a specific task in the search process. Some of these modules may be bought in by the search vendor and others will be developed internally. The same is true of open-source software development.

Users should not have to know anything about search technology to be able to use it effectively but understanding the elements of search technology is important in the selection, testing and management of a search application. This is because one or more of these modules may be especially important in being able to meet a specific user requirement. It is very much a question of the whole only being as strong as the weakest link in the chain. If there are some limitations in the way that content is indexed then it does not matter how elegant the user interface looks information will be not able to be found that could be critical to the operations of the business.

 

6. Search Technology Part 2

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In this chapter some of the more sophisticated aspects of search technology are described. All search applications will have the technology components described in Chapter5 but few will have all the technologies set out in this chapter. In selecting a search application it is of little value to use this chapter as a check-list, making a short list from those applications having the greatest number of ticks.

The reasons for this are:

Selecting a search application has to be based on user requirements, and it could be that just one of these features correctly implemented will be quite sufficient to meet these requirements.

The more of these features that are implemented the greater the cost of implementation and administration, ease of upgrading may be reduced, and users may need more training and support.

The concept of entity extraction is to be able to use the search application to identify automatically personal names, locations and other terms that can then be used as query terms without the need to manually index these terms. The technical term for this process is named entity extraction and analyses not just an individual word but also a sequence of words to determine index terms that could be of value in responding to queries. When organizations choose English they are also choosing a language with over 1,000,000 words, a result of invasions and the scale of perhaps the British Empire. The result is a language full of synonyms and polysemes. Fortunately words do not appear in isolation (other than in tables and charts!) so an analysis of a sentence will help substantially in determining the meaning of a word. The mathematics of entity extraction is largely based on the mathematics of Markov Models. A Markov Model describes a process as a collection of states and transitions between states, each of which can be given a probability. Although a knowledge of Markov Models, Hidden Markov Models and the Viterbi algorithm are not a requirement for a search support team it does illustrate the extent to which search is based on mathematics. These and many related mathematical models will be used in different ways by each search vendor and will lead to subtle differences in search performance. These can only be assessed through careful testing at a Proof of Concept stage.

 

7. The Business of Search

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Compared to most sectors of the enterprise applications business the enterprise search business is quite small. The total annual sales of search software may only amount to $3billion at most, which in IT terms is a niche market. In total there are probably no more than 80 companies in the business at present, and these are listed in AppendixB. It is very likely that business and IT managers will not be aware of any of these companies with the possible exception of Google. Most of them have revenues of less than $50million and many may have revenues of less than $10million. However this figure excludes the revenues of the search modules in large enterprise suites from IBM, Oracle, SAP and Microsoft, as well as sales of Google search appliances.

Another way of looking at the search market is the installed base of enterprise search. Excluding the enterprise suite market probably only Ultraseek (acquired by Autonomy when it purchased Verity), Isys-Search and Google have reached the 10,000 installed base mark, but the majority of these implementations are relatively small-scale.

 

8. Specification and Selection

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Now that all the work has been done on identifying user requirements and reviewing the performance of the current search application perhaps the time has arrived to specify, select and install a new enterprise search application. In many respects the processes for selecting an enterprise search application is just the same as for other enterprise applications but there are some differences.

These include:

The company will not have undertaken the procurement of an enterprise search application before so there is no prior experience to go on.

Even if there are existing search applications the level of knowledge inside the IT department about how they work and how to evaluate an enterprise application is likely to be low.

There is probably no single business owner of search and yet it is because of the poor performance of existing search applications that the company is now undertaking the selection of a new application.

Most of the companies in the business are totally unknown to either the IT department or to procurement.

 

9. Installation and Implementation

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The way in which the installation and implementation of the search application is conducted will be very specific to a particular company. The milestones for an open-source project will also be somewhat different to those for a commercial application. In this chapter a distinction is made between installation and implementation. Installation covers the provisioning and testing of servers and networks, loading all the modules of the search application, checking that user authentication is being managed correctly and undertaking User Acceptance Tests (UAT) that confirm that the base performance criteria are being achieved on a test collection.

Implementation is the process of extending the application to work on live servers and content, and moving the acceptance testing to the search support team and a small group of testers. Overall this could take at least a month to achieve and may be longer with more complex federated search implementations.

Installing and implementing an enterprise search application is a complex project with perhaps forty or fifty individual work packages. There will be little or no previous experience of installing enterprise search so this project calls for the best project manager the organization employs or hires. The availability of this project manager will decide when the project can begin, and of course the project will begin perhaps one or two months before the software arrives as the vendor begins the task of fully understanding the content, information architecture and security management environment.

 

10. Managing Search

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No matter how good the search technology and how closely it meets user requirements without an appropriate level of investment in the search support team the chances of continuing to meet the requirements of the organization and the individual requirements of users are going to be close to zero. My main objective in writing this book was to get this message across as clearly as possible.

Implementing search should never be a project. The work of ensuring that users continue to have high levels of search satisfaction will never come to a close. Each week, and perhaps even most days, there will be something that needs attention. The role of the search support team is not just to be reactive but to anticipate when changes to the search application need to be made, or to identify a training requirement that will address an issue that is just starting to show up on the search logs and user satisfaction surveys.

The strange thing is that for other applications organizations seem more than ready to provide a high level of support staff. Research from Computer Economics Inc. in 2011 suggested that the median level of support for an Enterprise Resource Planning application is 75 users per member of the support team. Translate this into 20,000 users of a search application and the result would be a requirement for a support team of nearly 600 people! Research carried out by Findwise suggests that a median figure for an enterprise search team is probably 300 people!

 

11. A Future for Search

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Writing about the future of search is a challenge because the very rapid pace of technical development could make sections of this chapter look very dated by the time the book is published. My objective in doing so is to illustrate that after a long period of benign neglect it would seem that there is a renaissance in enterprise search. The consensus view is that the rate of growth of enterprise information and data is now so high that action now has to be taken to ensure that the organization can benefit from this information. As the adoption of enterprise search accelerates search vendors will feel more comfortable investing in research and development to bring new functionality to the market.

This chapter summarizes some of the areas in which evidence of this investment will be most evident. In a period of rapid change it is even more important than it has been in the past to have a search strategy that is grounded in business reality and user requirements so that these developments can be assessed in terms of the possible impact they could have on business performance.

 

12. Critical Success Factors

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After eleven chapters and over 60,000 words I thought you might find it useful to have a short list of 12 critical success factors.

1. Invest in a search support team

Before you do anything else set up a search support team with the skills, enthusiasm, organizational knowledge and networks to get the best of the current search application(s). Even if the team is initially a team of one put the budget, headcount and job descriptions in place so that it can grow ahead of the requirements for support.

2. Get the best out of the current investment in search

There is usually much that can be done to improve the current search applications once the search team and the search vendor focus in on options and priorities. The information gained from search log files is a very important element of defining search requirements and setting benchmarks for any new search application

3. Enterprise search is an approach and not a technology

Implementing one single all-encompassing search application is unlikely to be successful and usually carries more risks than benefits. Enterprise search is about creating a managed search environment that ensures employees find the information they need to achieve organizational and/or personal objectives.

 

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