Content Health Flashcards
How value is captured in the interaction process
- capturing all the KCS article information during the interaction process
- respecting the contributions of all the people who interact with the knowledge
- structuring the articles so for reuse
- structuring information for findability and readability
- collective ownership
- evolve-loop articles
common element/fields of an article
- issue (symptom, problem/question)
- issue described in customer’s words/phrases from their perspective and context
- what is the customer trying to do?
- what is not working?
- environment
- products, categories, business process
- changes (upgrade, deletions, additions)
- resolution
- answer or steps to resolve the issue
- cause
- underlying cause of the issue
metadata
metadata is the collection if attributes of the KCS article, the metadata can be automatically added by the KCS system. (date created, date modified, reuse counts, creator, modifier) or added manually (visibility, quality (AQI), governance)
examples of metadata
article state author/modifier date created last modify date last modify by reuse counter audience and visibility references and hyperlinks identification number version article governance title summary knowledge state sub article confidence and visibility
three metadata fields that comprise the KCS article state attributes
article governance
article confidence
article visibility
article governance
two governance attributes
- experience - the most open level of governance. control is a function of being a member of the community and having an identity where sign in (identify) is required. articles will be based on the collective experience of those who use the articles. the number of people with this level of rights and privileges will typically be large.
compliance - everyone should be able to comment on all types of articles; however not everyone can create or modify articles. compliance controls sensitive, regulated, or critical information for an organization. this attribute is restrictive -only designated individuals or specific groups of individuals can create and modify articles.
article confidence
article confidence is the attribute that defines the quality of an article and tells the level of certainty in the article’s structure and content. article confidence is used in determining article visibility.
four article confidence attributes
work in progress - the article has no resolution. the problem and some environmental is captured, but the resolution is unknown. this is sometimes referred to as a framed article.
not validated - the article is complete and a resolution has been captured; however, confidence is lacking in structure or content, due to the lack of feedback or article noncompliance with the content standard.
validated - the article us complete and reusable; it as been used bu a licensed KCS user. articles are validated when there is confidence in the resolution and compliance with the content standard.
archived - articles are moved to archived when the article is defined as having no value.
article visibility
article visibility adds an additional layer of control that allows business rules to be created allowing different access to different audiences.
the individual’s KCS license level defines their rights and privileges in setting the visibility attribute (internal, partner, external) and the confidence attribute (not validated or validated)
article visibility attributes
internal - articles are only visible internally to an organization (anything with wider visibility than internal is referred to external)
within a domain - articles are visible to a group associated with a particular product domain, topic, job function, department.
partners - articles are visible to third parties (who are not employees) who act as a trusted extension of the organization.
customers - articles are visible to customer/clients or users of the products/services provided bi the organization. the articles are typically accessible via the web-based self service portal for users (registered)
public - the article is intended for anyone unidentified in the public domain. a common practice is to have this article optimized and indexed for a publicly available search appliance like Google.
The purpose of a content standard
the purpose of the content standard is to formally document or use a template that describes the decision that need to be made about KCS article structure and content that promote consistency.
common components of a content standard
- KCS article structure (field definitions)
- quick (one-page_ reference guide
- examples of good and poor articles
- templates
- metadata definitions
- knowledge article states
- style guide
- supporting material
- vocabulary
- multi-language considerations
- multimedia considerations
Two types of KCS articles
Solve loop - articles are developed just-in-time based on customer demand. these articles must adhere to the content standards so that the articles have a consistent structure and are findable and usable by the intended audience.
- evolve loop - article are high-value articles which are usually created knowledge domain experts, based on patterns and trends in article reuse or the analysis of self-service activity. this content generally represents a very small percentage of the total knowledge base.
considerations for archiving
- do so in a way that improves the findability of what is collectively known, not by reducing what is collectively known
- assess whether the archiving will compromise the completeness of the knowledge base. (the greatest value from the knowledge base comes from it being a complete collection of the organizations’s experience and the ability to quickly find what is needed what it is needed.)
- archiving old articles treats the symptoms of findability, not the cause.
- there is often higher value in seldom used articles, since this knowledge does not typically exist in most of the knowledge worker’s heads/memory.
- age and size of articles should not be considerations.
considerations when migrating and integrating legacy data.
- creating a demand-based process that will help identify the legacy content that has value.
- keeping the legacy content in a separate repository and making it available to knowledge workers to search
- letting demand focus the attention on the legacy content that has value.
- creating KCS articles in the new knowledge base for the content that is being used (found) from the old knowledge base.
- legacy data/content is typically not in the KCS structure, nor is it expressed in the context of the customer. Most who have done a mass migration of legacy (data/content) have ended up removing the legacy content because it disrupts findability.
- the investment of time and money to clean, write scripts, and move legacy knowledge is typically not worth the cost to migrate it, and often turns out to be counter-productive.
- experience shows that 90-95% of what is in the old knowledge base will never be referenced.
strategies for a successful demand-based migration strategy
- making the old knowledge repositories read-only
- the concept of searching the new knowledge base first
- if a KCS article is not found in the KCS knowledge base, search the old knowledge repositories
- re-purposing the old content that is useful (based on demand) by creating articles in the customer’s context and in the KCS structure.
describe the considerations when priming the knowledge base with new information
content should only be added when there is demand - don’t add unless someone asks.
examples: alpha and beta testers will experience the issue. if the issue is worth resolving. it’s worth capturing
- new products and processes deem it necessary
- ensure that the context is how customers will use it
- capture experiences (context) of alpha and beta testers
- capture context of user acceptance testing
- create content in the context of beta testers experience
- identify the article state as a draft or validated (internal)
- create content from training and pilot phase experiences
- expect articles to improve as customer context is added
describe KCS challenges in a global organization
- English is often the default language for global, multi-lingual, multi-cultural organizations
- KCS does not specifically address cultural issues
- the KCS article content structure and style of “complete thoughts, not complete sentences”
- complete thoughts are easier to comprehend for those where ESL
- KCS article structure provides meaning,and context, making translations easier
list examples of translation strategies
- just do it - machine translation (all articles)
- demand driven - only translate articles that have been reused
- hybrid - machine translation with manual edit and posting for reused articles
- side by side - the original article is available along-side the translated article
describe the purpose of knowledge domain analysis
knowledge domain analysis focuses on the health of the knowledge base with an emphasis on:
- quality of the articles
- the effectiveness of the workflow that produces and improves the articles
- the use of the articles
knowledge domain analysis is most effective with cross-organizational participation
identify the output of knowledge domain analysis techniques
knowledge domain analysis outputs includes the identification of:
- improvements to the content standard and process integration (workflow)
- recommendations on findability issues
- content gaps - knowledge people are looking for that does not exist
- content overlaps - consolidating duplicate articles, identifying the best or preferred resolution among many proposed resolutions.
- improvements in how known issues are leveraged, eliminating re-work, improving access and findability.
- improvements in how new issues are solved, suggestions for problem-solving and collaboration to solve new issues quickly
- pervasive issues - facilitating root cause analysis and working process, product, and business owners on high impact improvements.
- value of knowledge base: article reuse rates, self-service success, contributions in improving time to resolve, contribution to reducing downtime, contribution to increasing service availability
- archiving strategy for the knowledge base
describe the role of the knowledge domain expert
the knowledge domain expert (KDE) seeks to:
- optimize the creation, improvement , and use of articles
- identify patterns and trends of reuse to identify potential product, process, or policy changes that could eliminate the root cause of the frequent issues.
- work with coaches and KCS council to improve the content standard
- KDE’s are typically subject matter experts (SME) who continue to have other functional responsibilities
- KDE’s are individuals who are naturally attracted to using data analytics to figure out what can be learned from the collection of knowledge
- KDE’s must establish a relationship wit the business functions that need to take corrective actions:
- depending on the domain, may be the owners of business policy or processes and/or the owners of the product or services functionality and road maps
- provides the functional/product owner with quantifiable , actionable, information that is based on the user’s experience.
- success of the knowledge domain analysis function is measure through:
- improvements in findability
- self-service use
- incident volume reduction that is a result of corrective actions taken to pervasive issues
describe a knowledge domain
knowledge domains are virtual collections of KCS articles that are related to common topic, function, process, technology, or product family
knowledge domains are not precise or absolute in the boundaries, and they often overlap
a knowledge domain is the collection of content that makes sense to include for pattern recognition and cluster analysis. therefore, the purpose or intent of the analysis defines the collection of articles that are relevant
provide examples of evolve loop articles
- procedural articles, diagnostic articles, or step-by-step procedures
- resolution paths - a collection of linked procedural articles that defines a complex process (procedural or diagnostic) - created by KDE to address generic or high level symptoms. often created by KDE to address in a large/unweidy number of solve loop KCS articles.
high impact issues - issues that are pervasive, cause outages, or articles about new or strategic processes, policies, products or services. - KCS articles created to fill knowledge gaps - articles on topics or issues users are looking for that do not exist (typically identified through self-service and search analytics)
