Personal InfoCloud

We Can't Find Anything

There is nothing more common that I hear from an organization about their intranet and internal information services than, "We can't find anything." (Some days I swear this is the mantra that must be intoned for an organization to become real.)

There are many reasons and potential solutions for improving the situation. Some of these involve improved search technologies, some improved search interfaces, or But, understanding the cost of this inefficiency is where I find it is valuable to start.

The first step after understanding you have this problem is to measure it, but most organizations don't want to pay for that they are just looking for solutions (we all know how this turns out). The best method I find is walking through the broad understandings of the cost of inefficiencies.

The Numbers...

At Interop 2009 I presented "Next Generation Search: Social Bookmarking and Tagging". This presentation started off with a look at the rough numbers behind the cost of search in the enterprise (see the first 16 slides). [I presented a similar presentation at the SharePoint Saturday DC event this past week, but evaluated SharePoint 2010's new social tagging as the analysis focus.]

Next Generation Search: Social Bookmarking and Tagging

View more presentations from Thomas Vander Wal.

Most of the numbers come from Google white papers on search, which gets some of their numbers from an IDC white paper. I also have a white paper that was never published and is not public that has slightly more optimistic numbers, based on the percentage of time knowledge workers search (16% rather than the Google stated ~25% of a knowledge workers time is spent searching). There are a few Google white papers, but the Return on Information: adding to your ROI with Google Enterprise Search from 2009 is good (I do not endorse the Google Search Appliance, but am just using the numbers used to state the problem).

I focus on being optimistic and have I yet to run into an organization that claims to live up to the optimistic numbers or total cost of inefficiency.

• Few organization claim they have 80 percent of or better success with employees finding what they need through search
• That is 80 percent success rate
• Or, 1 in 5 searches do not find what is they were seeking
• A sample organization with 500 searches per day has 100 failures
• An average knowledge worker spends 16% of their time searching
• 16% of a 40 hour work week is 1.25 hours spent searching
• 20% (spent with unsuccessful searches) of 1.25 hours a week is 15 minutes of inefficient productivity
• At an average salary of $60,000 per year that leads to $375 per person of inefficient productivity
• Now take that $375 per knowledge worker and multiply it by how many knowledge workers you have in an organization and the costs mount quickly
• An organization with 4,500 knowledge workers is looking at a inefficiency cost of $1,687,500 per year.
• Now keep in mind your knowledge workers are you most efficient at search
• Many organizations as a whole are running at 40% to 70% success rate for search

We Know We Have a Costly Problem

This usually is enough to illustrate there is a problem and gap with spending time resolving. The first step is to set a baseline inside your organization. Examine search patterns, look at existing taxonomies (you have them and use them to some degree, yes?) and work to identify gaps, look at solutions like tagging (folksonomy) to validate the taxonomy and identify gaps (which also gives you the terms that will likely close that gap). But get a good understanding of what you have before you take steps. Also understand the easy solutions are never easy without solid understanding.

Evaluating what, if any taxonomy you have is essential. Understand who is driving the taxonomy development and up keep. Look at how to get what people in the organization are seeking in the words (terms) they use intend to find things (this is often far broader than any taxonomy provides).

Overview/Intro

One of my areas of focus is around social tools in the workplace (enterprise 2.0) is social bookmarking. Sadly, is does not have the reach it should as it and wiki (most enterprise focused wikis have collective voice pages (blogs) included now & enterprise blog tools have collaborative document pages (wikis). I focus a lot of my attention these days on what happens inside the organization’s firewall, as that is where their is incredible untapped potential for these tools to make a huge difference.

One of the things I see on a regular basis is tagging interfaces on a wide variety of social tools, not just in social bookmarking. This is good, but also problematic as it leads to a need for a central tagging repository (more on this in a later piece). It is good as emergent and connective tag terms can be used to link items across tools and services, but that requires consistency and identity (identity is a must for tagging on any platform and it is left out of many tagging instances. This greatly decreases the value of tagging - this is also for another piece). There are differences across tools and services, which leads to problems of use and adoption within tools is tagging user interface (UI).

Multi-term Tag Intro

The multi-term tag is one of the more helpful elements in tagging as it provides the capability to use related terms. These multi-term tags provide depth to understanding when keeping the related tag terms together. But the interfaces for doing this are more complex and confusing than they should be for human, as well as machine consumption.

In the instance illustrated to the tag is comprised or two related terms: social and network. When the tool references the tag, it is looking at both parts as a tag set, which has a distinct meaning. The individual terms can be easily used for searches seeking either of those terms, but knowing the composition of the set, it is relatively easy for the service to offer up "social network" when a person seeks just social or network in a search query.

One common hindrance with social bookmarking adoption is those familiar with it and fans of it for enterprise use point to Delicious, which has a couple huge drawbacks. The compound multi-term tag or disconnected multi-term tags is a deep drawback for most regular potential users (the second is lack of privacy for shared group items). Delicious breaks a basic construct in user focussed design: Tools should embrace human methods of interaction and not humans embracing tech constraints. Delicious is quite popular with those of us malleable in our approach to adopt a technology where we adapt our approach, but that percentage of potential people using the tools is quite thin as a percentage of the population.. Testing this concept takes very little time to prove.

So, what are the options? Glad you asked. But, first a quick additional excursion into why this matters.

Conceptual Models Missing in Social Tool Adoption

One common hinderance for social tool adoption is most people intended to use the tools are missing the conceptual model for what these tools do, the value they offer, and how to personally benefit from these values. There are even change costs involved in moving from a tool that may not work for someone to something that has potential for drastically improved value. The "what it does", "what value it has", and "what situations" are high enough hurdles to cross, but they can be done with some ease by people who have deep knowledge of how to bridge these conceptual model gaps.

What the tools must not do is increase hurdles for adoption by introducing foreign conceptual models into the understanding process. The Delicious model of multi-term tagging adds a very large conceptual barrier for many & it become problematic for even considering adoption. Optimally, Delicious should not be used alone as a means to introduce social bookmarking or tagging.

We must remove the barriers to entry to these powerful offerings as much as we can as designers and developers. We know the value, we know the future, but we need to extend this. It must be done now, as later is too late and these tools will be written off as just as complex and cumbersome as their predecessors.

If you are a buyer of these tools and services, this is you guideline for the minimum of what you should accept. There is much you should not accept. On this front, you need to push back. It is your money you are spending on the products, implementation, and people helping encourage adoption. Not pushing back on what is not acceptable will greatly hinder adoption and increase the costs for more people to ease the change and adoption processes. Both of these costs should not be acceptable to you.

Multi-term Tag UI Options

Compound Terms

I am starting with what we know to be problematic for broad adoption for input. But, compound terms also create problems for search as well as click retrieval. There are two UI interaction patterns that happen with compound multi-term tags. The first is the terms are mashed together as a compound single word, as shown in this example from Delicious.

The problem here is the mashing the string of terms "architecture is politics" into one compound term "architectureispolitics". Outside of Germanic languages this is problematic and the compound term makes a quick scan of the terms by a person far more difficult. But it also complicates search as the terms need to be broken down to even have LIKE SQL search options work optimally. The biggest problem is for humans, as this is not natural in most language contexts. A look at misunderstood URLs makes the point easier to understand (Top Ten Worst URLs)

The second is an emergent model for compound multi-term tags is using a term delimiter. These delimiters are often underlines ( _ ), dots ( . ), or hyphens ( - ). A multi-term tag such as "enterprise search" becomes "enterprise.search", "enterprise_search" and "enterprise-search".

While these help visually they are less than optimal for reading. But, algorithmically this initially looks to be a simple solution, but it becomes more problematic. Some tools and services try to normalize the terms to identify similar and relevant items, which requires a little bit of work. The terms can be separated at their delimiters and used as properly separated terms, but since the systems are compound term centric more often than not the terms are compressed and have similar problems to the other approach.

Another reason this is problematic is term delimiters can often have semantic relevance for tribal differentiation. This first surface terms when talking to social computing researchers using Delicious a few years ago. They pointed out that social.network, social_network, and social-network had quite different communities using the tags and often did not agree on underlying foundations for what the term meant. The people in the various communities self identified and stuck to their tribes use of the term differentiated by delimiter.

The discovery that these variations were not fungible was an eye opener and quickly had me looking at other similar situations. I found this was not a one-off situation, but one with a fair amount of occurrence. When removing the delimiters between the terms the technologies removed the capability of understanding human variance and tribes. This method also breaks recommendation systems badly as well as hindering the capability of augmenting serendipity.

So how do these tribes identify without these markers? Often they use additional tags to identity. The social computing researchers add "social computing", marketing types add "marketing", etc. The tools then use their filtering by co-occurrence of tags to surface relevant information (yes, the ability to use co-occurrence is another tool essential). This additional tag addition help improve the service on the whole with disambiguation.

Disconnected Multi-term Tags

The use of distinct and disconnected term tags is often the intent for space delimited sites like Delicious, but the emergent approach of mashing terms together out of need surfaced. Delicious did not intend to create mashed terms or delimited terms, Joshua Schachter created a great tool and the community adapted it to their needs. Tagging services are not new, as they have been around for more than two decades already, but how they are built, used, and platforms are quite different now. The common web interface for tagging has been single terms as tags with many tags applied to an object. What made folksonomy different from previous tagging was the inclusion of identity and a collective (not collaborative) voice that intelligent semantics can be applied to.

The downside of disconnected terms in tagging is certainty of relevance between the terms, which leads to ambiguity. This discussion has been going on for more than a decade and builds upon semantic understanding in natural language processing. Did the tagger intend for a relationship between social & network or not. Tags out of the context of natural language constructs provide difficulties without some other construct for sense making around them. Additionally, the computational power needed to parse and pair potential relevant pairings is somethings that becomes prohibitive at scale.

Quoted Multi-term Tags

One of the methods that surfaced early in tagging interfaces was the quoted multi-term tags. This takes becomes #&039;research "social network" blog' so that the terms social network are bound together in the tool as one tag. The biggest problem is still on the human input side of things as this is yet again not a natural language construct. Systematically the downside is these break along single terms with quotes in many of the systems that have employed this method.

What begins with a simple helpful prompt...:

Still often can end up breaking as follows (from SlideShare):

Comma Delimited Tags

Non-space delimiters between tags allows for multi-term tags to exist and with relative ease. Well, that is relative ease for those writing Western European languages that commonly use commas as a string separator. This method allows the system to grasp there are multi-term tags and the humans can input the information in a format that may be natural for them. Using natural language constructs helps provide the ability ease of adoption. It also helps provide a solid base for building a synonym repository in and/or around the tagging tools.

While this is not optimal for all people because of variance in language constructs globally, it is a method that works well for a quasi-homogeneous population of people tagging. This also takes out much of the ambiguity computationally for information retrieval, which lowers computational resources needed for discernment.

Text Box Per Tag

Lastly, the option for input is the text box per tag. This allows for multi-term tags in one text box. Using the tab button on the keyboard after entering a tag the person using this interface will jump down to the next empty text box and have the ability to input a term. I first started seeing this a few years ago in tagging interfaces tools developed in Central Europe and Asia. The Yahoo! Bookmarks 2 UI adopted this in a slightly different implementation than I had seen before, but works much the same (it is shown here).

There are many variations of this type of interface surfacing and are having rather good adoption rates with people unfamiliar to tagging. This approach tied to facets has been deployed in Knowledge Plaza by Whatever s/a and works wonderfully.

All of the benefits of comma delimited multi-term tag interfaces apply, but with the added benefit of having this interface work internationally. International usage not only helps build synonym resources but eases language translation as well, which is particularly helpful for capturing international variance on business or emergent terms.

Summary

This content has come from more than four years of research and discussions with people using tools, both inside enterprise and using consumer web tools. As enterprise moves more quickly toward more cost effective tools for capturing and connecting information, they are aware of not only the value of social tools, but tools that get out the way and allow humans to capture, share, and interact in a manner that is as natural as possible with the tools getting smart, not humans having to adopt technology patterns.

Tale of 2 Tunnels

One comment I made yesterday is, "the difference between Web 2.0 and Enterprise 2.0 is like the difference building a tunnel through rock and tunnel under water".

That this is getting at is Web 2.0 takes work to build to get through the earth, but once built it can suffer from imperfections and still work well. The tunnel can crack and crumble a little, but still get used with diminished capacity. We can look at Facebook, which has a rather poor interface and still gets used. Twitter is another example of a Web 2.0 solution that has its structural deficiencies and outages, but it still used as well as still loved (their Fail Whale is on a t-shirt now and a badge of pride worn by loyal users).

The Enterprise 2.0 tunnel is built under water. This takes more engineering understanding, but it also requires more fault testing and assurances. A crack or crumbling of a tool inside an organization is not seen kindly and raises doubts around the viability of the tool. The shear volume of users inside an organization using these tools is orders of magnitude less than in the open consumer web world, but faults are more deadly.

The other important factor is perceived fear of the environment. Fewer people (by pure numbers - as the percentages are likely the same, more on this later) are fearful of tunnels through land, they may not have full faith in them, but they know that they will likely make it safely on all of their journeys. The tunnels under water have greater fears as one little crack can cause flooding and drowning quickly. Fears of use of social tools inside an organization is often quite similar, there may be many that are not fearful, but if you spend time talking to people in organizations not using tools (it is the majority at this point) they are fearful of open sharing as that could lead to trouble. People are not comfortable with the concept as they are foreign to it as they are lacking the conceptual models to let them think through it.

Enterprise 2.0 is not Web 2.0

Another statement yesterday that garnered a lot of feedback was, "Web 2.0 does not work well in enterprise, but the approaches and understandings of Web 2.0 modified for enterprise work really well." The web is not enterprise or smaller organizations for that matter. The open consumer web has different scale and needs than inside organizations and through their firewalls. A small percentage of people using the web can get an account on a tool have have appear to be wildly successful correctly claiming 70 million or 100 million people are or have used their tool. But, even 100 million people is a small percentage of people using the web. Looking at real usage and needs for those tools the numbers are really smaller. Most darlings of the Web 2.0 phase have fewer than 10 million users, which is about 5% of the open consumer web users in the United States. On the web a start-up is seen as successful with 500,000 users after a year or two and is likely to have the capability to be self sufficient at that level too. Granted there are many players in the same market niches on the web and the overall usage for link sharing and recommending for Digg, Mixx, or Reddit is much higher across the sum of these tools than in just one of these tools (obviously).

These percentages of adoption and use inside organizations can make executives nervous that their money is not reaching as many employees as they wish. The percentages that can be similar to the web's percentages of high single digit adoption rates to the teens is seen as something that really needs more thinking and consideration.

Enterprise 2.0 is more than just tools (see my Enterprise Social Tools: Components for Success for better understanding) as it also includes interface/interaction design for ease of use, sociality, and encouragement of use. The two biggest factors that are needed inside an organization that can receive less attention on the web are the sociality and encouragement of use.

Understanding sociality is incredibly important inside an organization as people are used to working in groups (often vertical in their hierarchy) that have been dictated to them for use. When the walls are broken down and people are self-finding others with similar interests and working horizontally and diagonally connecting and sharing with others and consuming the collective flows of information their comfortable walls of understanding are gone. A presentation in Copenhagen at Reboot on Freely Seeping Through the Walls of the Garden focussed just on this issue. This fear inside the enterprise is real. Much of the fear is driven by lacking conceptual models and understanding the value they will derive from using the tools and services. People need to know who the other people are that they are sharing with and what their motivations are (to some degree) before they have comfort in sharing themselves.

Encouraging use is also central to increased adoption inside organizations. Many organizations initial believe that Web 2.0 tools will take off and have great adoption inside an organization. But, this is not a "build it and they will come" scenario, even for the younger workers who are believed to love these tools and services and will not stay in a company that does not have them. The reality is the tools need selling their use, value derived from them, the conceptual models around what they do, and easing fears. Adoption rates grow far beyond the teen percentages in organizations that take time guiding people about the use of the tools and services. Those organizations that take the opportunity to continually sell the value and use for these tools they have in place get much higher adoption and continued engagement with the tools than those who do nothing and see what happens.

Gaps in Enterprise Tools

The last related statement was around the gaps in current and traditional enterprise tools. At the fantastic Jive Enterprise UI Summit in Aspen a few weeks ago there was a lot of discussion about enterprise tools, their UI, and ease of use for employees by the incredible collection of people at the event. One of the things that was shown was a killer path of use through a wide encompassing enterprise toolset that was well designed and presented by SAP's Dan Rosenberg who has done an incredible job of putting user experience and thinking through the needed workflows and uses of enterprise tools at the forefront of enterprise software planning. Given the excellent design and incredible amount of user experience thought that went into the tools behind the SAP toolset in the scenario (one of the best I have seen - functioning or blue sky demoed) there are still gaps. Part of this is identifying of gaps comes from traditional business thinking around formal processes and the tools ensure process adherence. But, the reality is the tools are quite often inflexible (I am not talking about SAP tools, but traditional enterprise tools in general), the cost of time and effort is beyond the gain for individuals to document and annotate all decisions and steps along the way. The hurdles to capture information and share it are often too large for capturing one to 10 quick sentences of information that can be retained for one's own benefit or shared with other where it is relevant.

There is another gap in business around the collective intelligence that is needed, which can lead to collaboration. Most businesses and their tools focus on collaboration and set groups, but at the same time wonder why they do not know what their company knows and knowledge is not all being captured. First there is a difference between collective and collaborative activities and the tools and design around and for those different activities is more than a nuance of semantics it is a huge barrier to capturing, sharing, and learning from information that leads to knowledge if it is not understood well. Enterprise has gone through its phases of knowledge management tools, from forms for capturing information, forums for sharing, and up to enterprise content management systems (ECM) that encompass document management, content management, knowledge management, and information harvesting. But, the gaps still exist.

These existing gaps are around conversations not being captured (the walls of the halls have no memory (well today they do not)) and increasingly the ubiquitous communication channel in organizations, e-mail, is being worked around. Quick decisions are not being documented as it is not enough for a document or worth completing a form. As the iterative processes of development, design, and solution engineering are happening at quicker and smaller increments the intelligence behind the decisions is not being captured or shared. This is largely because of the tools.

As has always been the case large enterprise systems are worked around through the use of smaller and more nimble solutions that augment the existing tools. Even in Dan's incredible demo I saw gaps for these tools. The quick tools that can fill these gaps are blogs, wikis, social bookmarking, tagging, Twitter type sharing, Veodia type video sharing, instant messaging, etc. There are many avenues to quickly capture information and understanding and share it. These tools get out of the way and allow what is in someone's head to get digitized and later structured by the individual themselves or other people whom have had the information shared with them in a community space. This turns into flows through streams that can be put into many contexts and needs as well as reused as needed.

Another point Dan stated at the Enterprise UI Summit that is dead on, is organizations are moving out of the vertical structures and moving to the horizontal. This is having a profound effect on the next generation of business tools and processes. This is also an area for Enterprise 2.0 tools as they easily open up the horizontal and diagonal prospects and tie into it the capability for easily understanding who these newly found people are in an organization through looking at their profiles, which eases their fears around sharing and unfamiliar environments as well as their related tasks.

Is 70% New Terms from Folksonomy Tagging Normal?

In my discussion with enterprise organizations and other clients that are looking to evaluate their existing tagging services, have been finding 30 percent to nearly 70 percent of the terms used in tagging are not in their taxonomy. One chat with a firm who had just completed updating their taxonomy (second round) for their intranet found the social bookmarking tool on their intranet turned up nearly 45 percent new or unaccounted for terms. This firm knew they were not capturing all possibilities with their taxonomy update, but did not realize their was that large of a gap. In building their taxonomy they had harvested the search terms and had used tools that analyzed all the content on their intranet and offered the terms up. What they found in the folksonomy were common synonyms that were not used in search nor were in their content. They found vernacular, terms that were not official for their organization (sometimes competitors trademarked brand names), emergent terms, and some misunderstandings of what documents were.

In other informal talks these stories are not uncommon. It is not that the taxonomies are poorly done, but vast resources are needed to capture all the variants in traditional ways. A line needs to be drawn somewhere.

Comfort in Not Finding Information

The difference in the taxonomy or other formal categorization structure and what people actually call things (as expressed in bookmarking the item to make it easy to refind the item) is normally above 30 percent. But, what organization is comfortable with that level of inefficiency at the low end? What about 70 percent of an organizations information, documents, and media not being easily found by how people think of it?

I have yet to find any organization, be it enterprise or non-profit that is comfortable with that type of inefficiency on their intranet or internet. The good part is the cost is relatively low for capturing what people actually call things by using a social bookmarking tool or other folksonomy related tool. The analysis and making use of what is found in a folksonomy is the same cost of as building a taxonomy, but a large part of the resource intensive work is done in the folksonomy through data capture. The skills needed to build understanding from a folksonomy will lean a little more on the analytical and quantitative skills side than the traditional taxonomy development. This is due to the volume of information supplied can be orders of magnitude higher than the volume of research using traditional methods.

Personal Planets

Why a personal planet? We have an incredible amount of information that passes before out eyes and that is generated by our simple actions.  Emily did a great job showing the breadth of feeds generated.  This seems a simple thin thread.  What if we could quickly scan that thread and annotate it to make it easier to refind.

Planets are relatively easy to build and it should be easy to share for others to build upon. Personally, I am really surprised there are not thousands of these out there already.  Now to start tinkering a wee bit this week.