Major highlights from Elastic{ON} 2018 – Findwise reporting

Two Elastic fans have just returned from San Francisco and the Elastic{ON} 2018 conference. With almost 3.000 participants this year Elastic{ON} is the biggest Elastic conference in the world.

Findwise regularly organises events and meetups, covering among other topics Elastic. Keep an eye for an event close to you.

Here are some of the main highlights from Elastic{ON} 2018.

Let’s start with the biggest announcement of them all, Elastic is opening the source code of the XPack. This mean that you now not only will be able to access the Elastic stack source code, but also the subscription-based code of XPack that up until now have been inaccessible. This opens the opportunity for you as a developer to contribute back code.



Data rollups is a great new feature for anyone with the need to look at old data but feel the storage costs are too high. With rollups only predetermined metrics and terms will be stored. Still allowing you to analyze these dimensions of your data but no longer being able to view the individual documents.

Azure monitoring available in Xpack Basic. Elastic will in an upcoming 6.x release an Azure Monitoring Module, which will consist of a bundle of Kibana dashboards and make it really easy to get started exploring your Azure infrastructure. The monitoring module will be released as part of the XPack basic version – in other words, it will be free to use.

Forecasting was the big new thing in X-packs Machine learning component. As the name suggest the machine learning module can now not only spot anomalies in your data but also predict how it will change in the future.

Security in Kibana will get an update to make it work more like the Security module in Elasticsearch. This will also mean that one of the most requested security questions for Kibana will be resolved, giving users access to only some dashboards.

Dashboard are great and a fundamental part of Kibana but sometimes you want to present your data in more dynamic ways with less focus on data density. This is where Canvas comes in. Canvas is a new Kibana module to produce infographics rather than dashboards but still using live data from Elasticsearch.

Monitoring of Kubernetes and Docker containers will be made a lot easier with the Elastic stack. A new infra component will be created just for this growing use case. This component will be powered by data collected by Beats which now also has an auto discovery functionality within Kubernetes. This will give an overview of not only your Kubernetes cluster but also the individual containers within the cluster.

Geo capabilities within Kibana will be extended to support multiple map layers. This will make it possible to do more kinds of visualizations on maps. Furthermore, work is being done on supporting not only Geo points but also shapes.

One problem some have had with maps is that you need access to the Elastic map service and if you deploy the Elastic stack within a company network this might not be reachable. To solve this work is being done to make it possible to deploy the Elastic maps service locally.

Elastic acquired SaaS solution Swiftype last year. Since then Swiftype have been busy developing even more features to its portfolio. At current Swiftype comes in 3 different version:

  • Swiftype site Search – An out of the box (OOTB) solution for website search
  • Swiftype Enterprise Search – Currently in beta version, but with focus on internal, cloud based datasources (for now) like G Suite, Dropbox, O365, Zendesk etc.
  • Swiftype App Search – A set of API’s and developer tools that makes it quick to build user faced search applications


Elastic has also started to look at replacing the Zen protocol used to keep clusters in sync. Currently a PoC is being made to try to create a consensus algorithm that follow modern academic best practices. With the added benefit to remove the minimum master nodes setting, currently one of the most common pitfalls when running Elasticsearch in production.

ECE – Elastic Cloud Enterprise is big focus for Elastic and make it possible for customers to setup a fully service-based search solution being maintained by Elastic.

If you are interested in hearing more about Elastic or Findwise visit

elasticon 2018


Writers: Mads Elbrond, regional manager Findwise Denmark & Torsten Landergren, senior expert consultant

Enterprise Search Europe 2014 – Short Review

ESE Summit

At the end of April  a third edition of Enterprise Search Europe conference took place.  The venue was Park Plaza Victoria Hotel in London. Two-day event was dedicated to widely understood search solutions. There were two tracks covering subjects relating to search management, big data, open source technologies, SharePoint and as always –  the future of search. According to the organizer’ information, there were 30 experts presenting their knowledge and experience in implementation search systems and making content findable. It was  opportunity to get familiar with lots of case studies focused on relevancy, text mining, systems architecture and even matching business requirements. There were also speeches on softer skills, like making  decisions or finding good  employees.

In a word, ESE 2014 summit was great chance to meet highly skilled professionals with competence in business-driven search solutions. Representatives from both specialized consulting companies and universities were present there. Even second day started from compelling plenary session about the direction of enterprise search. Presentation contained two points of view: Jeff Fried, CTO in BA-Insight and Elaine Toms, Professor of Information Science, University of Sheffield. From industrial aspect analyzing user behavior,  applying world knowledge or improving information structure is a  real success. On the other hand, although IR systems are currently in mainstream, there are many problems: integration is still a challenge, systems working rules are unclear, organizations neglect investments in search specialists. As Elaine Toms explained, the role of scientists is to restrain an uncertainty by prototyping and forming future researchers. According to her, major search problems are primitive user interfaces and too few systems services. What is more, data and information often become of secondary importance, even though it’s a core of every search engine.


Despite of many interesting presentations, particularly one caught my attention. It was “Collaborative Search” by Martin White, Conference Chair and Managing Director in Intranet Focus. The subject was current condition of enterprise search and  requirements which such systems will have to face in the future. Martin White is convinced that limited users satisfaction is mainly fault of poor content quality and insufficient information management. Presentation covered  absorbing results of various researches. One of them, described in “Characterizing and Supporting Cross-Device Search Tasks” document, was analysis of commercial search engine logs in order to find behavior patterns associated with cross device searching. Switching between devices can be a hindrance because of device multiplicity. That is why each user needs to remember both what he was searching and what has already been found. Findings show that there are lots of opportunities to handle information seeking more effectively in multi-device world. Saving and re-instating user session, using time between switching devices to get more results or making use of behavioral, geospatial data to predict task resumption are just a few examples of ideas.

Despite everything, the most interesting part of Martin White’s presentation was dedicated to Collaborative Information Seeking (CIS).

Collaborative Information Seeking

It is natural that difficult and complex tasks forced people to work together. Collaboration in information retrieval helps to use systems more effectively. This idea concentrate on situations when people should cooperate to seek information or sense-make. In fact, CIS covers on the one hand elements connected with organizational behavior or making decision, on the other – evolution of user interface and designing systems of immediate data processing. Furthermore, Martin White considers CIS context to be focused around the complex queries, “second phase” queries, results evaluation or ranking algorithms. This concept is able to bring the highest values in the domains like chemistry, medicine and law.

During the CIS exploration some definitions appeared:  collaborative information retrieval, social searching, co-browsing, collaborative navigation, collaborative information behavior, collaborative information synthesis.  My intention is to introduce some of them.

"Collaborative Information Seeking", Chirag Shah

1. “Collaborative Information Seeking”, Chirag Shah

Collaborative Information Retrieval (CIR) extends traditional IR for the purposes of many users. It supports scenarios when problem is complicated and when seeking common information is a need. To support groups’ actions, it is crucial to know how they work, what are their strengths and weaknesses. In general, it might be said that such system could be an overlay on search engine re-ranking results, based on users community knowledge. In agreement with Chirag Shah, the author of “Collaborative Information Seeking” book, there are some examples of systems where workgroup’s queries and related results are captured and used to filtering more relevant information for particular user. One of the most absorbing case is SearchTogether – interface designed for collaborative web search, described by Meredith R. Morris and Eric Horvitz. It allows to work both synchronously and asynchronously. History of queries, page metadata and annotations serve as information carrier for user. There had been implemented an automatic and manual division of labor. One of its feature was recommending pages to another information seeker. All sessions and past findings were persisted and stored for future collaborative searching.

Despite of many efforts made in developing such systems, probably none of them has been widely adopted. Perhaps it was caused partly by its non-trivial nature, partly by lack of concept how to integrate them with other parts of collaboration in organizations.

Another ideas associated with CIS are Social Search and Collaborative Filtering. First one is about how social interactions could help in searching together. What is interesting,  despite of rather weak ties between people in social networks, their enhancement may be already observed in collaborative networks. Second definition referred to provide more relevant search results based on user past behavior, but also community of users displaying similar interests. It is noteworthy that it is an example of asynchronous interaction, because its value is based on past actions – in contrast with CIS where emphasis is laid to active users communication. Collaborative Filtering has been applied in many domains: industry, financial, insurance or web. At present the last one is most common and it’s used in e-commerce business. CF methods make a base for recommender systems predicting users preferences. It is so broad topic, that certainly deserves a separate article.

CIS Barriers

Regardless of all these researches, CIS is facing many challenges nowadays. One of them is information security in the company. How to struggle out of situation when team members do not have the same security profile or when some person cannot even share with others what has been found? Discussed systems cannot be only created for information seeking, but also they need to  provide managing security, support situations when results were not found because of permissions or situations when it is necessary to view a new document created in cooperation process. If it is not enough, there are various organization’s barriers hindering CIS idea. They are divided into categories – organizational, technical, individual, and team. They consist of things such as organization culture and structure, multiple and un-integrated systems, individual person perception or varied conflicts appeared during team work. Barriers and their implications have been described in detail in document “Barriers to Collaborative Information Seeking in Organizations” by Arvind Karunakaran and Madhu Reddy.

Collaborative information seeking is exciting field of research and one of the search trend. Another absorbing topic is gamification adopting in IR systems. This is going to be a subject of my next article.

Intranets that have an impact

Recently I attended Euroia, the European information architecture summit, where experts within the area meet up to discuss, share, listen and learn.

For me, one of the highlights was James Robertson from Step Two Designs, presenting some of the results from their yearly intranet awards. Intranets are fascinating in being large systems with such potential to improve daily work. However, more often than not they fail in doing so. As James Robertson put it “organizations and intranets is the place where user experience goes to die”.  So, what can we do to change that?

Robertson talked about successful companies managing to create structured, social and smart intranets. Two examples were the International Monetary Fund and a Canadian law firm. Both needed easy and secure gathering and retrieval of large amounts of information. Part of their success came from mandatory classification of published documents and review of changes. Another smart solution was to keep a connection between parent documents and their derivatives, making sure that information was trustworthy and kept up to date.

Companies that excelled at social managed to bind everything together; people projects and customers. I was happy to hear this, as we have been working a lot on this at Findwise. Our latest internal project was actually creating our own knowledge graph, connecting skills, platforms and technologies with projects and customers. What we haven’t done yet but other successful companies have, is daring to go all in with social. Instead of providing social functionality on the side, they fully integrate their social feed into the intranet start page. This I’d like to try at Findwise.

The ugliest but smartest solution presented by James, combined analytics with proper tagging of information. Imagine the following; a policy is changed and you are informed. However, you don’t need the policy until you perform a task months later. Now, the policy information is hidden in a news archive and you can’t easily find it. Annoying right?

What CRS Australia does to solve this problem is simple and elegant. They track pages users visit on the intranet. Whenever someone updates a page they enter whether it is a significant change or not. This is combined with electronic forms for everything. When filling in a form, information regarding policy updates pop up automatically, ensuring that users always have up to date information.

These ideas give me hope and clearly show that intranets needn’t be a place where user experience comes to die.

Uncover hidden insights using Information Retrieval and Social Media

Arjen de Vries’ talk at ESSIR 2013 (Granada, Spain) highlighted the opportunities and difficulties in using Information Retrieval (IR) and social media to both make sense of unstructured data that a computer cannot easily make sense of by itself and realise deeper hidden information.

Today social media has become more important as interactions on sites have developed to include user-generated content of all types from ratings, comments and experiences to uploaded images, blogs and videos. Users now not only consume content and products but also co-create, interact with other users and help categorise content through means of tagging or hash-tags. All of which may result in ‘data consumption’ traces.

Some of these social media platforms like Twitter provide access to a variety of data such as user profiles, their connections with other users, their shared or published content and even how they react to each other’s content through comments and ratings. Analysis of this data can provide new insights.

One example is a case from CIW research. They calculated a top music artist popularity chart for each of the following different music sites: EchoNest, and Spotify. Further research was then done for the band The Black Keys, where it was found that their popularity did not vary over time for either or Spotify. However when using data from tweets about the band for the very same period, it was found that interest in them rocketed after their Grammy win in the States, information that was not apparent from the previous research.

Using social media data to enrich information

The challenge that remains for IR research however is that these social media platforms vary in functionality. What they let users do will often determine the usefulness of the resultant data. For example, YouTube and Flickr will only let the up-loader tag their own content, while the film site IMDb allows tagging but the tags are not registered personally, rather they go into a pool. Arjen cited ‘Red Hot Chilli Peppers’ as a simple example of the usefulness of such social media data in allowing disambiguation either through implicit metadata from a user comment about eating chillies and/or information derived from the organisational data from say Flickr where a picture of red hot chilli peppers is grouped with other pictures of fruit and vegetables.

The key point here is that researchers often bemoan the fact that they do not always have access to log server files. Social media data left by users about content or objects can at times provide a richer representation in matching an information need and the response to that need. The potential benefits here for Information Retrieval are several:

  • The expanded content representation
  • The reduction in the ‘vocabulary gap(s)’ between content creator, indexers and information seekers
  • The increase in diversity of view on the same content
  • And the opportunity to make better assumptions about a user’s context and the variety of contexts that may exist

Allowing all users to tag all available content improves retrieval tasks

Where information about users on media sites is ‘open,’ (sometimes it is not, sites like Facebook and Linkedin are notoriously difficult to retrieve data from) there is the ability to discover which user labels what item with what word, and in some cases, even what rating they give. In essence many new sources play the role of anchor texts, be they tags, ratings, tweets, comments or reviews. The standard triangle of user, tag and item allows a unifying research approach based on random walks and can answer many questions. The talk emphasised that the area clearly has ample opportunity for researchers to make their mark.

One example of the research potential was shown in the case where was used to detect synonyms. The website allows users to keep a record of books they have read, tag, rate and comment on them. From these connections a synonym detector was created, allowing the example query word of ‘humour,’ to have a proposed list of synonyms created that included: ‘humor (US English), funny, humorous and British humour.

Analysis of this type of research has shown that allowing all users to tag all available content improves retrieval tasks, and that combining tags and ratings may both improve search and recommendation tasks even though there are some cases where lost relations between user, tag and item may occur.

The takeaway from this talk was that there is no one means or approach in retrieving information from Social Media due to the many complexities involved – not least because the limitations of user interactivity in some platforms but also due to limitations in the usage of data accessed. As Arjen demonstrated though, it is possible in certain cases to be innovative in the collection of rewarding data – an approach that may be utilized more and more, particularly as users/customers move closer to product and service providers through increased online interactions.

Solving Diversity in Information Retrieval

How to solve diversity in information retrieval and techniques for handling ambiguous queries was a topic of interest at the SIGIR 2013 conference in Dublin, Ireland, which I attended recently.

The issue of Diversity in Information Retrieval was covered at a number of presentations at the conference. It is search engine independent, since it uses only the set of result documents as input. When applied to the world of search it basically means an aim to produce a search result that covers as many of the relevant topics as possible.

This is done by retrieving, say 100-500 documents, instead of the normal 10.
These documents are then clustered based on their contents to create a number
of topic clusters. The search result is then constructed by selecting
(the normal 10) documents from the clusters in a round-robin fashion. This will
hopefully create a diverse search result, with as broad coverage as possible.

The technique can not only be used to solve the problem of ambiguous queries,
but also queries with several sub-topics associated with it. By iteratively
running a clustering algorithm on the result documents with 2 to 5 (or so)
clusters and measuring the separation between them and choosing the outcome
with the greatest separation, a diverse result set of documents can be created.
The clusters can also be used to ask follow up questions to the user, where
he/she is allowed to click on one of several tag clouds, containing the most
central terms of each cluster.

A cluster set of size 2 with a good separation would indicate that the query
may be ambiguous, with two different semantics meanings, while a size of 3-5
likely means that the there are a number of sub topics identified in the
results. In a way these clusters can be seen as a dynamic facet, but it is
still shallow since it only operates on the returned documents. Yet, it does
not require any additional knowledge about the documents other than the
information that is returned. This could also be extended by using topic
labelling to present the user with a single term or phrase, instead of a tag

Regarding the conference itself I found it to be a nice and professional arrangement with lots of in depth topics and nice evening activities, including a historical tour of Dublin.

Predictive Analytics World 2012

At the end of November 2012 top predictive analytics experts, practitioners, authors and business thought leaders met in London at Predictive Analytics World conference. Cameral nature of the conference combined with great variety of experiences brought by over 60 attendees and speakers made a unique opportunity to dive into the topic from Findwise perspective.

Dive into Big Data

In the Opening Keynote, presented by Program Chairman PhD Geert Verstraeten, we could hear about ways to increase the impact of Predictive Analytics. Unsurprisingly a lot of fuzz is about embracing Big Data.  As analysts have more and more data to process, their need for new tools is obvious. But business will cherish Big Data platforms only if it sees value behind it. Thus in my opinion before everything else that has impact on successful Big Data Analytics we should consider improving business-oriented communication. Even the most valuable data has no value if you can’t convince decision makers that it’s worth digging it.

But beeing able to clearly present benefits is not everything. Analysts must strive to create specific indicators and variables that are empirically measurable. Choose the right battles. As Gregory Piatetsky (data mining and predictive analytics expert) said: more data beats better algorithms, but better questions beat more data.

Finally, aim for impact. If you have a call center and want to persuade customers not to resign from your services, then it’s not wise just to call everyone. But it might also not be wise to call everyone you predict to have high risk of leaving. Even if as a result you loose less clients, there might be a large group of customers that will leave only because of the call. Such customers may also be predicted. And as you split high risk of leaving clients into “persuadable” ones and “touchy” ones, you are able to fully leverage your analytics potencial.

Find it exciting

Greatest thing about Predictive Analytics World 2012 was how diverse the presentations were. Many successful business cases from a large variety of domains and a lot of inspiring speeches makes it hard not to get at least a bit excited about Predictive Analytics.

From banking and financial scenarios, through sport training and performance prediction in rugby team (if you like at least one of: baseball, Predictive Analytics or Brad Pitt, I recommend you watch Moneyball movie). Not to mention Case Study about reducing youth unemployment in England. But there are two particular presentations I would like to say a word about.

First of them was a Case Study on Predicting Investor Behavior in First Social Media Sentiment-Based Hedge Fund presented by Alexander Farfuła – Chief Data Scientist at MarketPsy Capital LLC. I find it very interesting because it shows how powerful Big Data can be. By using massive amount of social media data (e.g. Twitter), they managed to predict a lot of global market behavior in certain industries. That is the essence of Big Data – harness large amount of small information chunks that are useless alone, to get useful Big Picture.

Second one was presented by Martine George – Head of Marketing Analytics & Research at BNP Paribas Fortis in Belgium. She had a really great presentation about developing and growing teams of predictive analysts. As the topic is brisk at Findwise and probably in every company interested in analytics and Big Data, I was pleased to learn so much and talk about it later on in person.

Big (Data) Picture

Day after the conference John Elder from Elder Research led an excellent workshop. What was really nice is that we’ve concentrated on the concepts not the equations. It was like a semester in one day – a big picture that can be digested into technical knowledge over time. But most valuable general conclusion was twofold:

  • Leverage – an incremental improvement will matter! When your turnover can be counted in millions of dollars even half percent of saving mean large additional revenue.
  • Low hanging fruit – there is lot to gain what nobody else has tried yet. That includes reaching for new kinds of data (text data, social media data) and daring to make use of it in a new, cool way with tools that weren’t there couple of years ago.

Plateau of Productivity

As a conclusion, I would say that Predictive Analytics has become a mature, one of the most useful disciplines on the market. As in the famous Gartner Hype, Predictive Analytics reached has reached the Plateau of Productivity. Though often ungrateful, requiring lots of resources, money and time, it can offer your company a successful future.

Microsoft is betting on cloud, mobile and social for SharePoint 2013 – Impressions from the SharePoint Conference 2012

Over 10,000 attendees from 85 countries, more than 200 sponsors and exhibitors, and over 250 sessions. Besides these impressive numbers, the 2012 SharePoint conference in Las Vegas has also marked the launch of the new version of SharePoint. Findwise was there to learn and is now sharing with you the news about enterprise search in SharePoint 2013.

In the keynote presentation on the first day of the conference, Jared Spataro (Senior Director, SharePoint Product Management at Microsoft) mentions the three big bets made for the SharePoint 2013 product: CLOUD, MOBILE, and SOCIAL. This post tries to provide a brief overview of what these three buzzwords mean for the enterprise search solution in SharePoint 2013. Before reading this, also check out our previous post about search in SharePoint 2013 to get a taste of what’s new in search.

Search in the cloud

While you have probably heard the saying that “the cloud has altered the economics of computing” (Jared Spataro), you might be wondering how to get there. How to go from where you are now to the so-called cloud. The answer for search is that SharePoint 2013 provides a hybrid approach that helps out in this transition. Hybrid search promises to be the bridge between on-premises and the cloud.

The search results from the cloud and those from on-premise can be shown on the same page with the use of the “result blocks”. The result block, new to SharePoint 2013, is a block of results that are individually ranked and are grouped according to a “query rule”. In short, a query rule defines a condition and an action to be fired when the condition is met. With the use of the result blocks, you can display the search results for content coming from the cloud when searching from an on-premises site and the other way around (depending whether you want the search to be one-way or bidirectional), and you can also conditionally enable these result blocks depending on the query (for example, queries matching specific words or regular expressions).


Screenshot from the post Hybrid search of the Microsoft SharePoint Team Blog showing how results from the cloud are integrated in the search results page when the user searches from an on-premises SharePoint 2013 site.

Before making the decision to move to the cloud, it is wise to check the current features availability for both online and on-premise solutions on TechNet.

Mobile devices

With SharePoint 2013, Microsoft has added native mobile apps for Windows, Windows Phone, iPhone, and iPad, and support across different mobile devices (TechNet), which provides access to information and people wherever the users are searching from.

Also important to mention when talking about mobile, is that the improved REST API widens the extensibility options and allows easy development of custom user experiences across different platforms and devices. The search REST API provides access to the keyword query language parameters, and combining this with a bit of JavaScript and HTML allows developers to quickly start building Apps with custom search experiences and making all information available across devices.

Social search

In the same keynote, Jared Spataro said that Microsoft has “integrated social very deeply into the product, creating new experiences that are really designed to help people collaborate more easily and help companies become more agile.” This was also conveyed by the presence of the two founders of the enterprise social network Yammer in the keynote presentation. The new social features integration means that the information about people following content, people following other people, tags, mentions, posts, discussions, are not only searchable but can be used in improving the relevance of the search results and improving the user experience overall. Also, many of the social features are driven by search, such as the recommendations for people or documents to follow.

Whether you are trying to find an answer to a problem to which the solution has already been posted by somebody else, or whether you are trying to find a person with the right expertise through the people search, SharePoint 2013 provides a more robust and richer social search experience than its previous versions. And the possibilities to extend the out-of-the-box capabilities must be very attractive to businesses that are for example looking to combine the social interactivity inside SharePoint with people data stored in other sources (CRM solutions, file shares, time tracking applications, etc).

Stay tuned!

It was indeed an awesome conference, well organized, but most of the times it was hard to decide which presentation to choose from the many good sessions running at the same time. Luckily (or wisely), we had more than one Findwizard on location!

This post is part of our series of reports from the SharePoint 2012 Conference. Keep an eye on the Findability blog for part two of our report from the biggest SharePoint conference of 2012!

Enterprise Search in Practice: A Presentation of Survey Results and Areas for Expert Guidance

Enterprise search in practice presentation has two main focuses. First, to present some interesting and sometimes rather contradicting findings from the Enterprise Search and Findability survey 2012. Second, to introduce an holistic approach to implementing search technology involving five different aspects that are all important to succeed and to reach findability rather than just the ability to search.

Presented at Gilbane Conference 2012 in Boston USA on the 28th of November by Mattias Ellison.

Presentation: Enterprise Search and Findability in 2013

This was presented 8 November at J. Boye 2012 Conference in Aarhus, Denmark, by Kristian Norling.

Presentation Summary

There is a lot of talk about social, big data, cloud, digital workplace and semantic web. But what about search, is there anything interesting happening within enterprise search and findability? Or is enterprise search dead?

In the spring of 2012,  we conducted a global survey on Enterprise Search and Findability. The resulting report based on the answers from survey tells us what the leading practitioners are doing and gives guidance for what you can do to make your organisation’s enterprise search and findability better in 2013.

This presentation will give you a sneak peak into the near future and trends of enterprise search, based on data form the survey and what the leaders that are satisfied with their search solutions do.

Topics on Enterprise Search

  •  Help me! Content overload!
  • The importance of context
  • Digging for gold with search analytics
  • What has trust to do with enterprise search?
  • Social search? Are you serious?
  • Oh, and that mobile thing

Tutorial: Optimising Your Content for Findability

This tutorial was done on the 6th of November at J. Boye 2012 conference in Aarhus Denmark. Tutorial was done by Kristian Norling.

Findability and Your Content

As the amount of content continues to increase, new approaches are required to provide good user experiences. Findability has been introduced as a new term among content strategists and information architects and is most easily explained as:

“A state where all information is findable and an approach to reaching that state.”

Search technology is readily used to make information findable, but as many have realized technology alone is unfortunately not enough. To achieve findability additional activities across several important dimensions such as business, user, information and organisation are needed.

Search engine optimisation is one aspect of findability and many of the principles from SEO works in a intranet or website search context. This is sometimes called Enterprise Search Engine Optimisation (ESEO). Getting findability to work well for your website or intranet is a difficult task, that needs continuos work. It requires stamina, persistence, endurance, patience and of course time and money (resources).

Tutorial Topics

In this tutorial you will take a deep dive into the many aspects of findability, with some good practices on how to improve findability:

  • Enterprise Search Engines vs Web Search
  • Governance
  • Organisation
  • User involvement
  • Optimise content for findability
  • Metadata
  • Search Analytics

Brief Outline

We will start some very brief theory and then use real examples and also talk about what organisations that are most satisfied with their findability do.

Experience level

Participants should have some intranet/website experience. A basic understanding of HTML, with some previous work with content management will make your tutorial experience even better. A bonus if you have done some Search Engine Optimisation (SEO) for public websites.