Build Foundational Structures With Information Architecture

Structure the labels and taxonomies that will deliver long-lasting value to the organization.

EXECUTIVE BRIEF

Analyst Perspective

Information architecture results in assurance that the right information is in the right place to help you deliver your very best.

Information architecture can be the organization's compass in achieving long-lasting value. It can support the requirements for just about any solution.

Information architecture is a sub-component of enterprise architecture. It inherits the ability to realize the business goals and objectives in practical deliverables.

Putting appropriate effort into organizing and structuring the ecosystem that your business-critical data and information will reside in results in expected behavior.

Ibrahim Abdel-Kader
Research Analyst,
Data & Analytics Practice
Info-Tech Research Group

Executive Summary – Information architecture

Your Challenge

The structural state of organization-wide solutions lack consistency, standardization, and fortitude. This leads to the following challenges:

• The lack of structural reliability when operating immediately from solutions out of the box is making information inaccessible.
• Even when leveraged properly, finding the relevant information is inefficient.
• Navigation and search across repositories is a struggle.

Knowledge is either duplicated or lost as a result.

Common Obstacles

Major change is needed; however, the following will make the journey harder:

• Resources such as time and expertise are scarce.
• Technology is painful and confusing rather than enabling the business.
• Populating metadata is evidently challenging cultural behaviors.

The later this initiative is properly addressed, the worse the problems get and the harder the path to success becomes.

Info-Tech's Approach

Our approach to information architecture should contribute to laying the groundwork for organization-wide solutions:

• Assess the needs of key stakeholders and ensure that business context is top of mind.
• Build taxonomies and/or interdependent taxonomies as foundational structures for the organization.
• Apply standard naming conventions when labeling metadata.

Info-Tech Insight

Don't jump the gun and start using newly obtained technologies right away. Make sure there are tailored underlying frameworks in place that support organizational objectives and usage.

Glossary

• Element: Basic unit in the ArchiMate metamodel. Used to define and describe the constituent parts of enterprise architectures and their unique set of characteristics.
• Metadata: Data about data.
• Business capability: What a business does to enable value creation. Business capabilities are business terms defined using descriptive nouns such as "Marketing" or "Research and Development." They represent stable business functions, are mutually exclusive and comprehensively exhaustive, and typically will have a defined business outcome.
• Business process: A business process is the execution of a sequence of activities that are coordinated to produce a specific output for an internal or external outcome.
• Information architecture: Information architecture describes the discipline of the definition, categorization, and organization of metadata and semantics.
• Naming convention: A generally agreed scheme for naming things.
• Controlled vocabulary: An organized arrangement of words and phrases used to index content and/or to retrieve content through browsing or searching.
• Business data glossary: Glossary of the most-used and most-popular data terms within the organization, with their definitions and semantics. Used primarily to avoid ambiguity.
• Taxonomy: A structural and hierarchical representation of the same type of element.
• Interdependent taxonomy: A structural and dynamic representation of the relationship between elements in any given set of taxonomies.

Develop an Enterprise Content Management Strategy and Roadmap

Great information services means a big-picture strategic lens on the whole dynamic lifecycle of information

Information Architecture is part of the Enterprise Architecture framework

Enterprise to program/portfolio/domain

Info-Tech Insight

Decisions at the enterprise level apply across multiple programs/portfolios/solutions and represent the guardrails set for all to play within.

Data domain documentation

Select the correct granularity for your business need.

Sources:
Dataversity; Atlan; Analytics8

Taxonomy examples

Taxonomy: A structural and hierarchical representation of the same type of element. (One-to-many)

Famous examples and common ways organizations will build a taxonomy.

Famous taxonomy examples:

• Animal kingdom
• Dewy Decimal System
• Audio playlists in Spotify or iTunes

Common areas that can be enhanced with the use of a taxonomy in organizations:

• Site map
• Folder structure
• Metadata fields
• Organization chart

Find out more in our DIY section

Image source: MarTech

Interdependent taxonomy examples

Interdependent Taxonomy: A structural and dynamic representation of the relationship between elements in any given set of taxonomies. (Many-to-many).

Famous examples and common ways organizations will leverage an interdependent taxonomy

Famous interdependent taxonomy examples:

• Amazon
• Yelp

Common areas that can be enhanced with the use of an interdependent taxonomy in organizations:

• Hub/Flat site maps for 'modern' websites
• Knowledge graph as part of an analytics solution

Find out more in our DIY section

Image source: MarTech

Information architecture outputs

Information architecture: Information architecture describes the discipline of the definition, categorization, and organization of metadata and semantics.

All these outputs directly leverage information architecture.

Success indicators

Here are some indicators that information architecture outputs have been successful:

• Findability: It takes a reasonable amount of time to find or locate information on a regular basis.
• Accuracy: The information is accurate due to adherence to standard operating procedures such as standard naming conventions and/or having a single source of truth.
• Structures are capable of handling high degrees of complexity without breaking logic.
• Structures are capable of handling high degrees of accumulation without breaking logic.
• Avoiding the need to rebuild structures frequently.
• Adherence to established information architecture principles.
• Stakeholder satisfaction.
• Storage optimization. Decisions at the enterprise level apply across multiple programs/portfolios/solutions and represent the guardrails set for all to play within.
• User adoption.

Info-Tech Insight

The ultimate success in information architecture is when there is only one final version of each unique structure. This suggests that fewer disruptions occur due to the foundational structure fulfilling its purpose.

Insight summary

Take a step back and carefully lay the foundations for a positive experience

Don't jump the gun and start using newly obtained technologies right away. Make sure there are tailored underlying frameworks in place that support organizational objectives and usage.

Architecture principles lead to success

The ultimate success in information architecture is when there is only one final version of each unique structure. This suggests that fewer disruptions occur due to the foundational structures fulfilling its purpose.

More chefs actually improve the broth

Willingness and availability of key stakeholders may help determine scope and prioritization.

Control accumulation first

When architecting a structure for a new solution, focus on the water flowing in first before dealing with the water (legacy information) just pooled there.

Definition and standardization facilitates the path to success

If the organization has completed its data glossary, data catalog, and data dictionary (database catalog), then the automation of taxonomy and interdependent taxonomy creation can more easily be achieved.

Information architecture relates to other architectural domain disciplines

Decisions at the enterprise level apply across multiple programs/portfolios/solutions and represent the guardrails set for all to play within.

Build Foundational Structures with Information Architecture – Project overview

Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit

“Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful.”

Guided Implementation

“Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track.”

Workshop

“We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place.”

Consulting

“Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project.”

Diagnostics and consistent frameworks used throughout all four options

SoftwareReviews

SoftwareReviews provides services to both software buyers and software providers.

Here are the relevant software categories that can provide benefits before, during, and/or after implementing information architecture:

• Analytical Data Store
• Business Intelligence & Analytics – Enterprise
• Content Collaboration
• Data Integration & iPaaS
• Data Preparation for Analytics
• Data Quality
• Desktop Search
• Desktop Publishing
• Digital Asset Management (DAM)
• Digital Experience - Enterprise (DXP)
• Document Management (DMS)
• eDiscovery
• Enterprise Content Management - Enterprise (ECM)
• Enterprise Architecture (EA)
• Enterprise Search
• Enterprise Service Bus (ESB)
• Machine Learning
• Master Data Management (MDM)
• Metadata Management
• Product Information Management (PIM)
• Retail Analytics
• Transaction Data Store
• Virtual Data Room (VDR)

How we help users select software:

• Understand the market with data driven reports
• measure the value of the vendor relationship
• Shortlist, compare and select your best software

Check out all the Software Categories

Start scoping with enabling capabilities

Pick a focus – something representative that delivers cross-enterprise impact and provides a model for scaling further, i.e., rinse and repeat

Enabling capabilities support the creation of strategic plans and facilitate business decision making as well as the functioning of the business (e.g. IT, Finance, HR)

We can provide structures for and label any components of the business, e.g. services, programs, physical assets, contracts, accounts, web pages. Examples of capabilities where we can apply common language and organizing structures are:

• IT Service Management
• Project Management
• Budget Management
• Document Management

For this blueprint, we are organizing and labelling Documents; Document Management will be leveraged as a focus in examples.

Scenario Example: Document Management Initiative

Professional Services organization kickstarts document management initiative for the organization

The organization of focus for the examples in this blueprint is looking to drastically improve information findability and accuracy. It has the following main functions:

• Sales
• IT
• HR
• Finance
• Research & Advisory
• Production & Design

Since the Research & Advisory function has the most in-house expertise when it comes to document management best practices, it was decided that they will lead this initiative and pilot it.

Info-Tech Insight

Deciding to start out with yourselves (project developers) can be the best way to learn and test out what can be scaled across the rest of the organization.

Find an input to create an initial structure

Decide how big and/or how many structures are needed.

There are various enterprise assets that can be used as inputs to leverage, such as:

• Business Capability Map (most recommended for an enterprise-wide scope)
• If you do not have an existing business capability map, start from Phase 1: Business context – Map Your Business Architecture to Define Your Strategy.
• to initiate the formulation of a map (value streams and related business capabilities).
• If you have an existing business capability map, meet with the relevant business owners/stakeholders to confirm that the content is accurate and up-to-date. Confirm that the value streams (how your organization creates and captures value) and their business capabilities are reflective of the organization's current business environment. (start from 3.3 Heatmap capability map – Map Your Business Architecture to Define Your Strategy)
• Business Data Catalog
• Defined Use Cases
• Entity Classifications (Security, Data, Records, or Digital Assets)
• Content Audit
• Application/System Portfolio
• Organizational Chart

If you find that the scope is too big to handle within your organization, consider leveraging one of Info-Tech's services to help ease the workload.

Info-Tech Insight

Willingness and availability of key stakeholders may help determine scope and prioritization.

For more information refer to Info-Tech's Map Your Business Architecture to Define Your Strategy

For more information refer to Info-Tech's Data Use Case Framework Template.

For more information refer to Info-Tech's Data Classification Inventory Tool.

For more information refer to Info-Tech's ECM Content Audit Tool.

Information architecture principles

Express purpose through principles.

Before creating an initial information skeleton structure, think about some architectural principles that can be used to guide the building process.

Review or establish architecture principles as a guidance mechanism when assessing or building structures. Think of the criteria that might be used to evaluate structures being built.
If there are strategic principles that exist, try to translate them into an architectural perspective. Here are some examples of guiding principles when building structures:

• No more than three levels deep – minimize clicks
• One agreed-upon designated location and owner – avoid duplication
• No more than 10 parent elements across the horizontal logic of the structure
• No more than 15 child elements associated to a parent in the same level
• No more than five hub/interdependent taxonomy nodes
• Term labels should aim to be one or two words
• Naming conventions should be recognizable but also distinguishable

Info-Tech Insight

Leveraging architectural principles results in a more accurate structure that is fit-for-purpose, just like someone would use a ruler as a guide to draw an accurate straight line.

1.0 Create an initial information skeleton structure

Attempt to create an initial high-level structure within your working group

1. Leverage any existing enterprise assets to help identify use cases relevant to your architecture focus.
1. If no enterprise assets exist, try to decompose the initial scope into key business processes.
2. Once use cases are identified, try to categorize and organize them into foundational functional groupings that are logical. Leverage architectural principals to support this step. A taxonomy template is provided on the following slide.
1. If there are challenges in finding logic at first glance, then some contextual definition is needed to improve clarity (activity 2.0 - Structure a section with metadata discovery).
2. Adopt a proactive-progressive mindset when defining additional context, what will this structure be used for?
3. Based on the structural purpose, what information would be useful to identify at this stage to gain additional clarity?
4. Continuously define layers of informational context until you feel comfortable in categorizing and organizing identified use cases into a function-based taxonomy.

In our Document Management Example, useful informational context would be to identify the roles within our scope and the documents they generate:

Leadership Roles: Research Agenda Planning Documents; Operational Team Documents; Event Related Documents

Non-Leadership Roles: Research Project Documents; Operational Team Documents; Member/External-Facing Documents

This informational context enables us to build an initial information skeleton structure that be leveraged as a site map.

Initial Site Map Taxonomy

Document Management Example

Info-Tech Insight

Even though the primary structure purpose is for a site map, it can also be repurposed into a governance operating model down the line.

Taxonomy template

Structure use:

Related to Activity 1.0

Skeleton Taxonomy example

Structure usage: ITRG research department intranet site map

Related to Activity 2.3.1

Structural Evolution

As sections of the information skeleton structure are defined, some shuffling and refinement is inevitable

Naming convention approach

Avoid ambiguity with a standard way of labeling controlled vocabulary.

Naming convention: A generally agreed-upon scheme for naming things.

Consider the following questions when establishing standard naming conventions:

• Are there any organizational or industry standards you can rely on? If so, do they satisfy the main purpose?
• What is the purpose?
• What makes it recognizable?
• What makes it distinguishable?
• Are there multiple elements involved? If so, what are they?
• Is there an all-encompassing term or short phrase to represent the multiple elements?
• Is there any risk of a key stakeholder assuming that the term label belongs to a different purpose than intended?

When trying to decide between two labels, repeat the following: Are all Xs Ys? (example: all taxonomies are structures but not all structures are taxonomies).

Download the Information Standards Guide

Translate information into knowledge with intuitive metadata

Metadata is how you give your organization's information context. Without context, not only will information be hard to find, but it will not be used to its full potential. Metadata is key to strategically enabling your information assets to support current operations and future developments.

Benefits of Effective Metadata Management

1. Improved decision making due to improved information asset discovery.
2. Better trustworthiness from accessing the correct information.
3. Improved speed to findability of information assets.
4. Reduce duplication efforts in developing and storing similar or the same digital assets.
5. Standardization and increased efficiency.
6. Better sharing of information in the organization.
7. Better preservation of information.
8. Easily demonstrate compliance with standards.

2.0 Structure a section with metadata discovery

Use metadata to confirm that the high-level structure created is accurate.

1. Identify metadata fields for the high-level categories that were identified in Activity 1.0 – Create an initial information skeleton structure, that you feel would help fulfil your structure's purpose. Attempt to do this within your project working group first.
2. See if you can streamline metadata fields that are common to each category. An example of this is on the right-hand side and a Metadata matrix template is provided on the following slide.
3. Gather additional context from relevant key stakeholders by getting some metadata value suggestions and probe to see if there are any key metadata fields missing.
1. An internal stakeholder survey can be created and distributed to support this step; this is also a good way to promote the initiative and potentially identify operational governance roles once the initiative is deemed complete.
2. In our Document Management Example, the metadata matrix can be used to influence the survey questions that will be answered by the relevant stakeholders with contextual knowledge. In this instance, the following questions can be included in the stakeholder survey:
1. What are the document sets you interact with most (top 3 – 5)?
2. How do you sort and filter these document sets to differentiate between them?
3. What processes do these document sets relate to?
4. In these processes, what is the workflow lifecycle stages? (e.g. in-progress, returned for correction, complete)

Refer to this appendix slide for more sample survey questions

Initial High-Level Metadata Discovery

Document Management Example

Metadata Matrix Template

Use the following template to conduct metadata discovery on information categories.

Best Practices:

• Whenever additional context is available/defined (e.g. from a stakeholder survey), replace cells populated with "yes" with metadata values that align to the corresponding metadata field.
• This template can also be repurposed for sub-categories for more detailed metadata.
• Standardize metadata values and naming conventions as much as possible.

Metadata Taxonomy example

Structure use: Event logistics document metadata requirements.

Related to Activity 1.0 & 2.0

Mine your Metadata in a Data Catalog

Metadata is the bridge between structured and unstructured data

Data Catalog: An organized inventory of data assets in the organization. It uses metadata to help organizations manage their data. It also helps data professionals collect, organize, access, and enrich metadata to support data discovery and governance.

In order to reduce the amount of complexity when building taxonomies and interdependent taxonomies, defining the relevant elements will provide a lot of clarity to unorganized sets of elements.

By mining metadata defined through initiatives, you are adopting a proactive progressive mindset that will make solution design and execution a lot easier.

Leverage the resources in the following slides as guidance of what aspects to document as part of the organization's data catalog. There are data glossary, catalog, and dictionary examples in the following slides that can be referenced during this exercise.

Info-Tech Insight

If the organization has completed its data glossary, data catalog, and data dictionary (database catalog), then the automation of taxonomy and interdependent taxonomy creation can be achieved.

Data domain documentation

Select the correct granularity for your business need

Sources:
Dataversity; Atlan; Analytics8

Data domain documentation examples

Data Catalog Best Practices

Core metadata subjects

1. Datasets: Files and tables accessed by organization personnel. They may reside in a data lake, warehouse, master data repository or other shared resource.
2. People metadata: Describes the people who work with data, e.g. consumers, curators, stewards, and subject matter experts.
3. Search metadata: Supports tagging and keywords to help people find data.
4. Processing metadata: Elaborates on the various transformations and derivations applied as data is managed throughout its lifecycle.
5. Supplier metadata: Data acquired from external sources. Informs resources and subscription or licensing constraints associated with the data.

Data catalog key steps

1. Capture data: Which metadata to capture and how to capture it?
2. Assign points of contact: Who are the important people for each data asset, including business context and technical attributes of the data asset?
3. Document interactions: Add data documentation over time to achieve a certain coverage percentage, e.g. 90% or less within a few months. This could occur whenever you learn about it, when code change occurs, or by setting aside time for team members.
4. Ensure data catalog is up to date: Checking quality and staleness of information is essential.
5. Optimize according to needs: Set standards for how you want the organization to use the data catalog.

Best practices

• Add everything to the inventory – text files, spreadsheets.
• Manage data flow: A good data catalog will identify flows between disparate datasets.
• Prioritize sensitive data: Manage sensitive and redundant data to minimize the vulnerability to breaches.
• Include unstructured data: Documents, web pages, email, social media content images, and videos do not lend themselves to relational databases, but the data catalog can help to add structure to unstructured data.
• Add clear names and descriptions to make the assets more discoverable.
• Data lakes are different: Data catalogs can help make data lakes more discoverable (they gather lots of data into individual files).
• Transparent user ratings: Listen to users about how well the data catalog is helping them and meeting standards.
• Have rules to validate that data matches data catalog definitions.
• Apply machine learning: ML can identify data types and relationships to build the catalog. And, it generates data tags faster than a manual catalog.

Metadata Management - SoftwareReviews Category

3.0 Refine skeleton structure after each section is structured

Structures, metadata, and naming conventions are all subject to refinement

1. After each section of the original information skeleton structure is defined and built out, add on to that taxonomy. Over time, it is important to maintain the integrity of the structures and refer to original architectural principles.
2. Ensure that logic of the structure makes sense. After gathering context from stakeholders, or further defining metadata of a focused aspect, it might make sense to relocate a taxonomy node or add a new section to the taxonomy structure all together.

In our Document Management Example, after feedback from stakeholder surveys and interviews, it was determined that the Research Project document lifecycle would be managed in one place (as opposed to being split in two areas). There was also a need to add a section to support the intake of a collection of new research products. →

It is also important to pay attention to see if any metadata and/or naming conventions need to be refined to maintain integrity. An example of this refinement evolution is on the following slide.

Initial Structure	Evolved Structure	Net New Taxonomy Node
	Research Process is a more logical container for Projects-in-Progress & Projects-in-Publishing

Refinement evolution

Just like with structures, metadata and naming conventions also evolve.

Initial Research Project Status Metadata Values

• Working
• Submitted
• Published

Ambiguity and missing key status possibilities triggered the need to refine metadata values and naming conventions.

Current Research Project Status Metadata Values

• In-Progress
• Completed
• Published
• Analyst Attention Required

Upcoming optimization to the research development process will trigger a need to review current structure, metadata, and naming conventions aligned to any potential changes.

4.0 Identify and connect other potential skeleton structures into an interdependent taxonomy

Think about the big picture whenever it is appropriate

1. Once the focused taxonomy design is considered complete, ensure the enterprise purpose is met. Think about functions throughout the enterprise and other business capabilities. What aspects of the focused taxonomy can be considered an entry-point to other potential skeleton structures?
2. Ensure that the logic of the interdependent taxonomy structure makes sense. After gathering context from stakeholders, or further defining metadata of a focused aspect, it might make sense to relocate a taxonomy or add a new section to the taxonomy structure. Always keep architectural principles in mind; one of key ones is to achieve synergies when possible and avoid unnecessary duplication and ambiguity.

In our Document Management Example, the pilot taxonomy structure for Research & Advisory will be purposed as hub for other functional hubs to connect. The Research Products area will be leveraged by both Research & Advisory and Sales, so there should be an entry point to that area.

The link between Research Products & Sales Products is that harvested research product documentation can be leveraged for client-facing sales purposes

Interdependent taxonomy example

Related to Activity 4.0

Structure use:

Point in Time ECM interdependent taxonomy – IT Research & Advisory Department

Check out The Open Group ArchiMate Specification for language reference.

• 7.1 - Strategy Elements Metamodel
• 9.1 - Application Layer Metamodel

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Research Contributors and Experts

Ibrahim Abdel-Kader
Research Analyst | Data & Analytics
Info-Tech Research Group

Andy Neill
Associate Vice President | Enterprise Research; Technical Counselor
Info-Tech Research Group

Chris Dyck
Research Lead | Data & Analytics
Info-Tech Research Group

Ben Abrishami-Shirazi
Technical Counselor
Info-Tech Research Group

Peter Putros
Senior Service Desk Technician | IT Operations
Info-Tech Research Group

Andrea Malick
Research Director | Data & Analytics
Info-Tech Research Group

Milena Litoiu
Principal Research Director | Enterprise Architecture
Info-Tech Research Group

Anuradha Ganesh
Principal Research Director | Enterprise Architecture
Info-Tech Research Group

Ilana Schwartz
UX Director
Info-Tech Research Group

Sanchia Benedict
Senior Product Manager | Executive Services
Info-Tech Research Group

Bibliography

ArchiMate® 3.1 Specification. "2 Definitions," The Open Group, Accessed 15 Nov. 2022.
Babich, Nick. "The Beginner's Guide to Information Architecture in UX." Adobe XD, 24 Nov. 2020.
Cagle, Kurt. "Taxonomies vs. interdependent taxonomies." Forbes, 24 March 2019.
Chin, Cedric. "Putting Mental Models to Practice Part 3: Better Trial and Error." Commoncog, Accessed 28 Nov. 2022.
"Classification of Animals: The Complete Guide." AZ Animals, 14 Nov. 2022.
Ericson, Jonathan D. "Reimagining the Role of Friction in Experience Design." Journal of User Experience, 4 August 2022.
"Glossary of Statistical Terms," OECD, Accessed 15 Nov. 2022.
Indeed Editorial Team. "6 Types of Information (With Examples)." Indeed, 1 Nov. 2022.
Indeed Editorial Team. "A Guide To Procedural Knowledge in the Workplace." Indeed, 13 July 2021.
Khan, Sarah. "An Introduction to Taxonomies." UX Booth, 9 May. 2017.
Knight, Michelle. "What Is a Data Dictionary?" Dataversity, 23 Dec. 2017.
Knight, Michelle. "What Is a Data Catalog?" Dataversity, 9 Dec. 2021.
Kononow, Piotr. "Business Glossary vs Data Glossary vs Data Dictionary." Dataedo, 10 July. 2019.
Knight, Michelle. "Taxonomy vs Interdependent Taxonomy: Machine Learning Breakthroughs." Dataversity, 17 Oct. 2017.
"Interdependent Taxonomy" Dublin Core, Accessed 15 Nov. 2022.
Peck, Bob. "Dewey Decimal Classification System." Accessed 15 Nov. 2022. Web.
Peck, Bob. "Designing a Naming Convention."Accessed 15 Nov. 2022.
"Product Information Management: 4 Key Principles of Good Product Data" Earley Information Science, Accessed 15 Nov. 2022.
Thurow, Shari. "Website Taxonomy Guidelines And Tips: How Best To Organize Your Site." MarTech, 08 May 2015.
"Taxonomies and Controlled Vocabularies" University of Pittsburgh, 20 Oct. 2022.
"The Powerfully Simple Modern Data Catalog." Atlan, 2021. Web.
"The search-inference framework of thinking" Bernhard Wenzel, 19 Sept. 2020.
"What is the Difference Between A Business Glossary, A Data Dictionary, and A Data Catalog, and How Do They Play A Role In Modern Data Management?" Analytics8, 23 June 2021. Web.
Verma, Aman. "Business Glossary, Data Dictionary, and Data Catalog?" Medium, 28 Aug. 2020.

Optional: Representative user experiences

Understand a user's experience with the search inference framework.

When addressing user experiences, the challenge arises in anticipating a user's thoughts and decisions. In Thinking and Deciding, Jonathan Baron offers up the search inference framework which states that all of thinking can be modelled as a search for possibilities, goals, and evidence. The framework has been adapted to the exercise below:
Walk through and document a representative user experience workflow in the following slide. The workflow may contain a significant pain point, and/or a critical business process.

1. As you walk through the workflow, document all the typical events that tend to occur.
2. What questions does the user think about pre-, during, and post-workflow?
3. Determine what criteria will be used to evaluate the success of each workflow event.
4. Heatmap the typical workflow events using the recently developed evaluation criteria. Green = Aligned. Yellow = Somewhat aligned. Red = Not aligned.
5. Now document the alternative events (for anything red or yellow) that can occur in that workflow. It could contain exceptions, other trigger points, and other possibilities not considered at all.
6. Heatmap those alternatives using the recently developed evaluation criteria.

Input

• User Experience Workflow(s)

Output

• User Experience Discovery and Assessment
• Strategic Principles via Evaluation Criteria

ITRG Engagement Options

• DIY
• Guided Implementation
• Technical Counselor Services
• Consulting Services

Participants

• Information Architect / Corporate Librarian
• Business Architect and other domain architects
• Business Leads

User experience discovery template

Leverage the template below when discovering representative user experiences.

Related to Activity 1.1

Potential stakeholder survey questions

Use these questions when gathering context for Document Management

1. What are the document sets you interact with most? (top 3 – 5)
2. How do/would you sort and filter these document sets to differentiate between them?
3. What processes do these document sets relate to?
4. In these processes, what is the workflow lifecycle stages? (e.g. in-progress, returned for correction, complete)
5. Are any of the document sets mentioned in paper/physical format? If so, which?
1. Where are these paper/physical documents stored?
2. Do all these paper/physical documents serve the same purpose?
3. What is/are the purpose(s) of these paper/physical documents?
4. How many of these paper/physical documents exist in total? (approximately)
6. Are there documents you can't access or find that you hope to in the future?
7. Why do you want more visibility of these documents?
1. What is the purpose?
2. What processes do they relate to?
8. What documents are you responsible for generating?
9. Do you need to collaborate with others to build these documents before they are used/delivered? If so, who?
10. Where do you capture/store the documents that you generate? (If different location for different document sets, then please list each location and context.)
11. How do you share documents?
12. Who else do you collaborate with regarding document sets? For what purpose? Are there any relevant processes?
13. What are some current pain points you experience when managing documents?
14. Are there any documents that involve external collaboration? If so, which documents and who are the external stakeholders?
15. Wish list: What are the top 3-5 outcomes you hope to come out of this initiative? (Disclaimer: Nothing can be promised but everything will be considered)

Note: Not all these questions will be relevant for all scenarios; only ask what is necessary to avoid survey fatigue and refine the questions to person/role you are asking for input. For example, if your audience are process owners, then some useful context to know would be what process(es) do they own?

Optional: Define the pilot scope for implementation

Here are some next steps to consider:

1. Find out the correlation of the candidates for implementation in the Implementation Assessment template on the next slide. Are there potential opportunities to find a pilot scope that has a big impact yet can be implemented in an ideal time frame?
1. List all the sections being assessed for pilot implementation.
2. Describe the section purpose and use.
3. Define the action plan of what is needed in order to consider an implementation milestone complete
4. Based on the previous documentation, evaluate each section's effort and impact levels from low to high.

Input

• Information architecture output(s)

Output

• Implementation pilot scope for solution defined

ITRG Engagement Options

• DIY
• Guided Implementation
• Technical Counselor Services
• Consulting Services

Participants

• Information Management Stakeholders
• Business Leads

Implementation assessment template

Related to Activity 2.4

Leverage the template below when assessing the scope for implementation.

Appendix

ArchiMate Relationships & Metamodels

Appendix

ArchiMate Relationships & Metamodels