Do you assume people will adopt your new knowledge management initiative, or is adoption something you are actively investing in? Resistance can be the death knell for a KM project, and can lead to technology being left unused, processes being ignored, and knowledge being hoarded.

If you’re currently experiencing some of these challenges, a change management strategy can help. One of the key benefits of a change strategy is that it creates opportunities to have conversations with end users and stakeholders, and learn how to communicate in the user’s terms. As a result of these conversations, users and stakeholders will better understand the value and outcomes of the KM project. The more conversations, the better: for a change strategy to be most effective, it should be included in a KM project at all stages of the process, including the very beginning.

Here’s how we have applied change management techniques to KM projects at EK:

1. Technology Changes

Nearly all knowledge management projects involve some sort of technology, such as an intranet site, social media tool, or wiki collaboration platform. Resistance to these tools often looks like a sad, blank tool that is gathering dust.

In my experience, many of these change failures can be prevented by tailoring end user training to the value the technology actually adds to people’s daily work. For example, I’ve taught basic SharePoint classes on the benefits of version control, co-authoring, and storing files outside of an email platform. For groups that are less tech-savvy, these simple lessons are much more impactful than teaching them about why they should stop using navigation and start using search to find documents.

2. Process Changes

Knowledge management frameworks are often built around processes: content authors need to tag their content correctly, admins need to follow a records management schedule, or staff needs to follow a standard publishing process.

The change management principle of co-creation can help with process changes. A new process that’s designed without the input of the people actually using it will almost certainly fail, by leading to workarounds. For example, in terms of a publishing process, a low percentage of “emergency” publishing will be a good indicator of success. In addition, taking an agile approach to content development and gradually improving processes over time will help make change manageable.

3. Cultural Changes

Promoting knowledge sharing and growing communities of practice are cultural aspects of many knowledge management projects. These types of changes are often the most difficult to manage because they are difficult to “force” – they address behaviors and habits that are ingrained in an organization.

Applying change networks can help you surface issues and build excitement and trust in these cases. A change network is a group of people outside of the management team who is serving as “ambassadors” for the change. They are a motivated group that will help spread the value of KM and will bring issues to the group that people don’t feel comfortable saying publicly. In the past, I have also used a change network as an informal focus group to test project communications, new tools, and other KM ideas.

Taxonomy management typically follows a Library and Information Science paradigm. The taxonomist is a keeper of knowledge, who is responsible for updating and managing the “Source of Truth.” Each version of the taxonomy is published and subsequently distributed to separate systems to help perform specific functions.  Such change control processes are effective for ensuring stability and quality, but they can be a costly use of time and resources.  The costs are even more apparent when organizations analyze the opportunity costs associated with employing a slow process that may take months to implement.  Compare this to agile IT teams who are significantly cutting the length of time it takes to deploy system changes.  The fact is, taxonomists can reap many of the same benefits by adopting an agile approach:  properly scaled releases, quicker delivery, better engagement with user communities, more relevant search results, and reduced overhead.

Many agile practices that support continuous delivery in software development, like DevOps, are emerging as an approach to taxonomy maintenance. DevOps emphasizes the collaboration and communication of both software developers and other information-technology (IT) professionals while automating the process of software delivery and infrastructure changes. With the alignment between taxonomy maintenance and systems, there are emerging possibilities for employing Continuous Delivery and DevOps strategies to greatly enhance the effectiveness of taxonomies throughout their lifecycle.   

Benefits of DevOps for Taxonomies

Software companies that embrace the agile approach of Continuous Delivery readily respond to change as they significantly increase the speed of delivery of applications and services.  The gains in efficiency and effectiveness are shown in all areas where development and operations are merged in an environment known as DevOps.  DevOps methods promote continuous delivery by rapidly moving software development (to include features, configuration, changes, and bug fixes) into production.  A DevOps environment is characterized by:

• Small cross-disciplinary teams
• Short iterative releases throughout the entire software lifecycle 
• Adaptability and resilience to change

A natural outgrowth of this movement toward efficiency is its spread to many other areas of business and operations.  Naturally, leaders in the field of information science are asking how they can streamline the maintenance of taxonomies in order to keep in step with continuously evolving information architecture.

In order for a taxonomy to stay relevant and adaptable to change, it is critical to engage stakeholders and subject matter experts through each iteration of its maintenance.  However, it is often difficult to enlist the valuable time of experts.  In a DevOps environment this challenge is addressed by promoting short term involvement on ad-hoc teams that come together in a few brief meetings to suggest, design, and validate new concepts and terms.  A  large active pool of participants in DevOps will yield the added benefit of ownership among a broad base of stakeholders and SMEs without incurring significant overhead.    

An Agile Approach to Maintaining Taxonomies

Traditional approaches to maintaining a taxonomy using a  governance plan are becoming outdated.  Taxonomies are a key element of software information architecture.  Like other areas of system architecture, taxonomies are barely noticed when they serve their purpose, but any lapse in quality compromises the integrity of the system and causes users to grow frustrated or lose confidence.  Therefore, taxonomies must be maintained with robust and frequent quality control monitoring.  To do so in the current dynamically changing environment, taxonomists must embrace new ways to optimize the design/development/release cycles for taxonomies to keep up with software’s rapid movement into production for feature releases, configuration, changes and bug fixes.   

A best practice for taxonomy maintenance is to employ simple guidelines for a build-measure-learn iterative process for governance.  A Taxonomy DevOps team is a small ad hoc group of subject matter experts with expertise relevant to the business use case for the taxonomy terms in question.  It is also a best practice to employ the use of tools that provide a common easy-to-use space for the team to make changes and test them prior to deployment.  Lastly, the review cycle should be truncated to meet the expectation of frequent releases.  In all cases stakeholders and technical members come together in the DevOps environment to assist with the rapid deployments.

5 Principles of Continuous Delivery for Taxonomy¹

Instead of prescribing procedures, taxonomy maintenance in a DevOps environment should apply the 5 Principles of Continuous Delivery in order for it to meet its goals.

1. Everyone is Responsible 

A taxonomy must be like the lexicon it captures: adaptable to change and reflective of the business. Stakeholders and Subject Matter Experts must be empowered to suggest, edit, and validate a subset of the concepts that are represented in the taxonomy. In instances where taxonomies serve the purpose of unifying an enterprise, these stakeholders and SMEs need to work across lines of business to make decisions about changes.  Whether the collaborative effort is coached using an agile framework or facilitated by the taxonomist, SMEs and stakeholders must understand their role as owners who can directly influence the taxonomy at all stages of DevOps.

2. Build in Quality 

Identify system quirks and build in a mechanism for addressing problems as soon as taxonomy changes are applied.  Build simple rules into the system to identify improper syntax, spelling errors, or duplicate terms, to name a few of the pesky problems that generally plague taxonomies in production.  Use a staging environment with workflows so that SMEs can use a common space to collaborate, review, and validate changes before they are deployed.

3. Work in Small Batches

Avoid the risks associated with adhering to a rigid cadence.  Make changes as they organically occur or, if necessary, schedule short intervals for changes to be made. This approach is less likely to cause major disruption for the end-users, easing the change management challenge.  By deploying changes in small batches, incrementally, end-users will grow accustomed to a dynamic taxonomy that is updated and in step with business changes.

4. Computers Perform Repetitive Tasks, People Solve Problems 

Implementing changes is a much easier task than it’s been in the past.  The key to greatly reducing the administrative tasks associated with the taxonomy publishing process, as well as the duplication of effort that often comes with importing them into separate systems, is to leverage technology that uses linked open data² to reference the terms and concepts represented in the taxonomy.  Today’s standard Web technologies significantly cut the time spent performing data entry and quality control. Additionally, these technologies can be used to dynamically incorporate changes without having to go through the much riskier re-indexing process.   

5. Relentlessly Pursue Continuous Improvement

Because a taxonomy is never really complete, the review of the terms and concepts must be an ongoing process: not to be ignored but instead made easy and quick.

Summary

Current and accurate taxonomies make information more findable. Making information more findable increases the time available for people to spend on innovation and meeting other mission focused goals. When it comes to Continuous Delivery, the benefits truly outweigh the costs.   

Taxonomy is not as daunting as it seems. In this blog series, one of EK’s taxonomy experts, Ben White, provides 4 practical steps to designing and validating a user-centric taxonomy.

Step #4: Measure the Findability of Your Content

Search, which is central to enterprise-wide knowledge transfer, is simple in theory; a user enters a set of key terms in a search engine and the search engine retrieves records that match the key terms. In reality, the architecture of a search engine is nothing more than:

Search Outputs: Search results the user sees after requesting information
Query Management:  The way a system formats and matches requests for information
Search Inputs: Content a system looks through to find the requested information

Yet while it’s true that search is a simple and well-understood progression, creating an effective enterprise-wide search is a multifaceted process that requires in-depth analysis. In my previous blogs, I’ve talked about some of those necessary steps, such as designing a user-centric taxonomy, making sure that facets are consistent, as well as testing the taxonomy. In my final blog of this taxonomy series, I’ll be discussing the metrics that can be used to measure the effectiveness of a taxonomy.

The addition of a taxonomy supports accurate search and guided navigation, which cannot be achieved with a search engine alone. However, implementing a taxonomy requires consistent maintenance and refinement of the search data in order to ensure its effectiveness. Objectively scrutinizing enterprise-wide search data allows us to tune search and update the underlying taxonomy to create a positive search experience. When examining search data, there are a number of metrics that can help us measure the effectiveness of a taxonomy:

Metrics, Definitions and Benefits:

Search Refinements:   The number of times a visitor searched and then performed another search. Provides information on the effectiveness of the terms used to search
Search Depth:   Average number of pages viewed after performing a search. Provides information on the effectiveness of the search results.
Bounce Rate:   Percentage of visitors who navigate away from the site after viewing only one page. Also shows us the effectiveness of search terms.
Time after Search:  How many searches made before reaching a desired page. Allows us to see if search terms retrieved adequate results.

These analytics can be used to better identify the most effective search terms and determine if they are reflected in a taxonomy.

To capture this information, we can simply ask users to search for specific content and analyze their search habits, making note of search depth, bounce rate, time after search, and any search refinements that occur. There are also a number of tools that can be used to help calculate these analytics. Google Analytics and PIWIK are two popular choices that can be used for both intranets and public facing websites.

Once you implement these metrics, the taxonomy should be updated periodically to reflect the search trends, which will result in a more efficient and accurate search system. The key to properly updating a taxonomy with effective search inputs is to understand user intent. This is no easy task, it involves a deep understanding of the keywords used by employees when searching. Therefore, in addition to the metrics provided above, it is also important to look at:

Where users searched and what they did next:  Did the user reach the desired page or attempt another search? Are users generally visiting the same pages when searching the same key words?

Measuring search quality:  By looking at search refinements, search depth, bounce rate, and time after search while paying close attention to the search terms used to reach the page, we can get a good idea of the quality of the search.

For example, if a high number of users searched the intranet using a specific keyword and 80% of users left the page the keyword led to immediately, correcting the underlying taxonomy is necessary.

In short, understanding the intent of the user allows us to get into the minds of the searcher. Therefore, a better understanding of the search terms used by users allows us to create a better taxonomy and a better search experience.

Although the concept of search is a relatively simple idea, there are many considerations that go into the implementation process. Despite the challenges that come with developing an effective enterprise search, the benefits to doing so are clear. Sue Feldman of IDC found that knowledge workers spend from 15% to 35% of their time searching for information and 40% of corporate users reported that they couldn’t find the information they need to do their jobs on their intranets. The subsequent costs are significant; in another recent survey conducted by IDC, the time spent searching for information averages 8.8 hours per week, at a cost of $14,209 per knowledge worker per year. In short, the time and costs associated with unstructured information are too significant to ignore.

We hope that through this blog series, you have a better understanding of how much thought and consideration goes into designing and evaluating a quality taxonomy and enterprise search. To learn more about how you can improve the findability of your content, connect with one of our knowledge management experts by contacting Enterprise Knowledge.

Taxonomy is not as daunting as it seems. In this blog series, one of EK’s taxonomy experts, Ben White, provides 4 practical steps to designing and validating a user-centric taxonomy.

Step #3: Validate Your Taxonomy

Previously, I’ve talked about how to design a user-centric taxonomy, as well as how to ensure that your facets are consistent. Today’s blog will address the next key task: testing the taxonomy. In order to continue to provide you all with practical and applicable advice, I’ll address some of the most common and efficient forms of testing that can be executed on a taxonomy prior to deployment.

Taxonomy Testing

Faceted search is one of the most significant search innovations to date.  It allows users to combine searching and browsing with a simple keyword search. We must treat faceted search the same as any other component in an information environment. This means testing the underlying taxonomy the same way other elements of an information architecture are tested. These are the the most common and efficient forms of testing that can be executed on a taxonomy prior to deployment.

Card Sorting

Card sorting is the most common form of user experience testing for taxonomy. It’s a technique where users group related terms using index cards or online programs, such as Optimal Workshop or Usability Tools. There are two forms of card sorting, open and closed.

Open Card Storing

Open card sorts require participants to group potential taxonomy values together and assign a broader category of their own. For example, users could group index cards labeled 401(k), Healthcare, Holidays, etc. under an index card labeled Benefits. Open card sorting is done earlier in the taxonomy design process, when taxonomic categories are not clear. This test helps uncover how users believe the taxonomy should be classified.  

Closed Card Sorting

In closed card sorts the categories have already been designated, allowing only prelabeled cards and categories. Closed card sorts are used to validate the taxonomic structure already developed. In closed card sorting tests, users are presented with a series of prearranged categories. Users then assign taxonomy values to each category using index cards or an online program. When the card sorting exercise is finished you will likely notice that the participants chose slightly different categorization schemes.  This is typical and should be formally documented. The most effective way to document participant responses is through a standardization grid:

A standardization grid captures the number of participants that chose a specific categorization scheme.  This allows the taxonomist to choose the most appropriate classification scheme within the taxonomy.

Tree Testing

Tree testing, or reverse card sorting, is used after the open card sort is validated through closed card sorting. The hierarchy developed through closed card sorting is presented to the user and the user is asked to complete a series of tasks. Depending on how the taxonomy will be used, the tasks will vary.  Example tasks could include:

• Where in the taxonomy would you find a specific document?
• What value would you use to tag a specific document?

These tasks are written on index cards, and users are asked to place the task cards in the taxonomy. A standardization grid is used to collect the number of participant that chose:

Test Tagging

Once the structure of the taxonomy is in place, one final test is necessary. The taxonomy needs to be tested by tagging actual documents or other information products. It is important that the test administrator encourages users to talk through the searching process and note any problems that occur. Ideally this test involves having users tag and search for content within a content management system.    If it is not possible to perform this test in a content management system, a taxonomy testing tool can be developed in a spreadsheet:

Users can tag content using drop down menus populated by taxonomy values. This method does not allow users to search for content but does allow us to see if the taxonomy is exhaustive and flexible enough to support a large number of content from across the organization. As with any variation of user testing, the test administrator needs to note any gaps, ambiguity, or other issues found when using the testing tool.  

Now you are well on your way to designing and validating your taxonomy. The question still remains, has the taxonomy you’ve created improved the findability of your information? In the final blog of this series, I’ll share some critical metrics for determining whether your taxonomy is delivering the results you expect.

Taxonomy is not as daunting as it seems. In this blog series, one of EK’s taxonomy experts, Ben White, provides 4 practical steps to designing and validating a user-centric taxonomy.

Step #2: Make Sure Your Facets Are Consistent

In the first blog of my series, “The 4 Steps to Designing an Effective Taxonomy,” I spoke about the importance of designing a user-centric taxonomy. Indeed, developing an understanding of how people think about the content in question allows a taxonomist to design a clear and consistent taxonomy, enabling site visitors to find what they need. Though this may be the first step, it’s hardly the last. Once you have completed an initial taxonomy design, it’s essential to remain consistent with faceted classification when tagging your content, which is the subject of today’s blog.

For intranets and websites, the cost of an ill-considered taxonomy is efficiency. Creating a truly successful taxonomy design involves breaking down the content by its attributes and organizing those attributes in an easily understandable classification scheme. During this process, the taxonomist will develop multiple taxonomies related to several different categories, or facets. This method is known as faceted classification.

The end result of a faceted classification system is a faceted search capability. Faceted search is a technique that allows users to explore a collection of information by applying multiple filters. This enables users to practice a hybrid of search and browse to find content. Because users expect navigation systems to behave rationally, the terms found in the faceted classification system should describe the body of content using common and naturally occurring descriptors.

Although there is no universal set of facets that can be used across information environments, we have found there are several common facets:

• Topic/Subject
• Document/Product Type
• Format
• Audience
• Geography

Of course this list is not exhaustive, but it’s an excellent place to start when designing a faceted classification system. A few additional tips:

• Ensure that the terms that fall beneath each of these facets are mutually exclusive and clearly communicate the universe of content it is describing.
• Choose a list of preferred terms that reduces confusion.
• Identify terms that speak the same language as the information environment’s users while accurately describing the content.

So, if we know that inconsistent terms can create ambiguity and decrease efficiency, what can we do to address these challenges? In Information Architecture for the World Wide Web, Peter Morville outlines several guidelines for designing effective labels. These are applicable to taxonomy design as well. As Morville discusses, in order to ensure consistency it is important to pay close attention to:

• Syntax– Verb-based terms (e.g. run) and noun-based terms (e.g. health & wellness) are often mixed together in a single faceted taxonomy. Choosing a single syntactic approach can improve consistency within the faceted search system.  
• Granularity– Within a faceted classification system choosing terms that are approximately equal in specificity can reduce confusion and improve consistency. For example, “Stool”, “Table”, “Bergere”, and “Caquetoire” at the same level in the classification system will cause confusion among users when searching and browsing.  
• Audience– When choosing preferred terms within a faceted classification system it is imperative that you choose the terminology most commonly used by the audience. For instance, using “Cute Puppies” and “Felis Catus” in the same classification system can confuse users when searching and browsing for information.

By being aware of syntax, granularity, and audience, the taxonomist can take steps to create a meaningful and consistent taxonomy that reduces confusion and increases efficiency. This benefits all users by increasing usability and findability.

Once you’ve established a taxonomy that is both user-centric and consistent with faceted classification, you’ll be ready for my next blog, which describes how to validate your taxonomy. Stay tuned!