Workforce Persona & Automation Opportunities

Workforce Persona & Automation Opportunities helps organizations understand how users work across applications and identify recurring cross-application workflows that may be suitable for further automation analysis.

The analysis is divided into two connected areas:

• Workforce Personas groups users with similar application-usage patterns into meaningful work personas.
• Automation Opportunities identifies application pairs that are frequently used together and evaluates whether those relationships may represent repeatable workflows with automation potential.

Use Workforce Personas first to understand who is working in similar ways and what applications they use. Then use Automation Opportunities to investigate which application relationships may represent repetitive or manual workflows.

Important: These features identify patterns for investigation. They do not automatically determine that a process should be automated or that an existing technical integration between two applications exists.

---

Customer Workflow

Use the following workflow to move from workforce analysis to automation investigation:

1. Open Work Intelligence in the AppNavi Portal.
2. Review the Workforce Personas results.
3. Identify personas with recurring or highly manual work patterns.
4. Select a persona and review its detailed analytics.
5. Review the applications contributing to the persona.
6. Identify application combinations that appear repeatedly within the work pattern.
7. Open Automation Opportunities.
8. Review the application pairs identified from organizational usage data.
9. Use filters, search, and sorting to focus the analysis.
10. Compare Users, Active Days, Automation Potential, Usage Overlap, Workflow Confidence, Manual Work, Sensitivity, and Recurrence.
11. Select an application pair to review its detailed analytics.
12. Review the affected countries and departments.
13. Validate the observed workflow with the relevant business or application owner.
14. Prioritize the workflows that provide the strongest combination of business relevance, recurrence, manual work, and automation potential.

This workflow connects workforce analysis with automation investigation instead of treating the two features as separate dashboards.

---

1. Workforce Personas

What Are Workforce Personas?

Workforce Personas groups users with similar application-usage patterns into meaningful work personas.

The feature analyzes application usage across users and evaluates relationships between applications to identify common work patterns. Based on these patterns, AppNavi generates a business-oriented persona name and provides metrics that describe the identified pattern.

For example, personas may be identified as:

• Business Analyst
• Marketing Specialist
• Operations Manager
• Project Coordinator
• Customer Support Specialist
• Learning and Development Specialist
• Financial Controller

The generated name describes the observed usage pattern and does not necessarily represent the user's official organizational job title.

---

What Data Does Workforce Personas Analyze?

Workforce Personas analyzes application usage across users.

The resulting personas are based on indicators such as:

---

Workforce Personas Overview

The Workforce Personas table provides a high-level view of the identified work patterns.

How to Read the Overview

Do not evaluate a persona using one metric in isolation.

For example, a persona with:

• High Confidence
• High Recurrence
• High Manual Work
• A large number of Users

may represent a well-established work pattern that is worth investigating for process improvement or automation.

Review the applications associated with the persona before drawing conclusions about the type of work being performed.

---

Persona Analytics

Select a persona from the Workforce Personas table to open its detailed analytics.

The detailed view provides additional information about the selected work pattern.

Confidence

Confidence indicates how strongly the observed application usage supports the identified persona.

The score is displayed from 0 to 100.

Use Confidence to understand the strength of the evidence before drawing conclusions about the persona.

---

Risk

Risk indicates the potential risk associated with the applications and data usage observed for the persona.

Risk is represented as:

• Low
• Medium
• High

Risk may be influenced by observed sensitive-data activity and the types of applications used by the persona.

Use this indicator to identify personas that may require additional security, compliance, or data-governance review.

---

Users

The Users metric shows the total number of users associated with the selected persona.

For example:

Users: 937

means that 937 users are associated with the identified application-usage pattern.

A larger user population can indicate that the identified work pattern has broader organizational relevance.

---

Ø Activity Time

Ø Activity Time shows the average activity time associated with the persona.

The value can be displayed in minutes or hours depending on the calculated activity duration.

Review Activity Time together with Manual Work and Recurrence to understand the scale and consistency of the observed work pattern.

---

Active Days

Active Days shows the number of days on which activity associated with the persona was observed.

For example:

Active Days: 90

indicates that activity was observed across 90 days within the available data range.

A higher number of Active Days provides additional context when determining whether the pattern is recurring rather than occasional.

---

Manual Work

Manual Work indicates the level of manual activity associated with the identified work pattern.

A higher Manual Work score can indicate a pattern that is suitable for further process investigation.

Manual Work should be evaluated together with:

• Application usage
• Activity Time
• Recurrence
• Confidence

Important: A high Manual Work score does not automatically mean that a process can or should be automated.

---

Recurrence

Recurrence indicates how consistently the identified application-usage pattern occurs.

A high Recurrence indicates that the same or similar application pattern is observed repeatedly.

Recurring patterns can be investigated for:

• Process optimization
• Workflow improvements
• Standardization
• Automation opportunities

---

Applications Used by Persona

The Apps Used By Persona section shows the applications contributing to the selected persona.

Cluster Usage

Cluster Usage represents the contribution of an application to the application-usage cluster associated with the persona.

For example:

Use these values to understand which applications contribute most strongly to the identified usage pattern.

Do not interpret the persona based on one application alone. The combination of applications provides the context for understanding the work pattern.

---

Application Explanation

The Explanation field provides a business-oriented description of the application's role within the identified persona.

For example, applications used for:

• Customer relationship management
• Contact research
• Scheduling
• Project management

may collectively provide evidence of a sales-oriented work pattern.

This helps move the analysis from:

"Which applications are being used?"

to:

"What type of work might this application combination support?"

---

Workforce Persona Example

Consider a persona with:

This combination suggests a well-established work pattern involving a significant user population and repeated manual activity.

The next step should be to review the applications associated with the persona and understand the underlying work pattern.

If the same applications repeatedly appear together, continue the investigation in Automation Opportunities.

---

Automation Opportunities

What Are Automation Opportunities?

Automation Opportunities identifies application pairs that are frequently used together and may represent opportunities for process automation.

It analyzes application usage across users and active days and provides indicators for:

• Automation Potential
• Usage Overlap
• Workflow Confidence
• Manual Work
• Sensitivity
• Recurrence

This helps organizations identify repetitive cross-application workflows and prioritize workflows that may benefit from further automation analysis.

---

Access Automation Opportunities

To access Automation Opportunities:

1. Open the AppNavi Portal.
2. Navigate to Work Intelligence.
3. Select the Automation Opportunities tab.
4. Review the application pairs displayed in the table.
5. Use the available filters, search, and sorting options to focus on specific opportunities.

---

Automation Opportunities Overview

Each row in the Automation Opportunities table represents an application pair identified from organizational usage data.

---

Understanding an Application Pair

Each Automation Opportunity represents two applications that demonstrate a measurable relationship in organizational usage.

For example:

Dynamics 365 Business Central → Microsoft Stream

The arrow represents an observed usage relationship.

It does not necessarily mean that:

• The applications have a technical integration.
• One application directly triggers the other.
• An API exists between the applications.
• Automation is already technically possible.

The application pair is derived from activity observed across users and time and represents a potential workflow pattern.

---

Users

The Users column shows the number of users associated with the application pair during the selected reporting period.

A higher number indicates that the observed application relationship occurs across a broader user population.

For example:

• 100 users → observed across a smaller user group.
• 1,000+ users → may represent a broader organizational opportunity.

Use Users to help estimate the potential organizational reach of an opportunity.

---

Active Days

Active Days represents the number of days on which activity associated with the application pair was observed.

A higher number indicates that the application relationship persists over a longer period rather than appearing as an isolated event.

For example:

90 Active Days

indicates that the application pair was observed during the reporting period represented by the data.

---

Automation Potential

Automation Potential indicates how suitable an application pair may be for automation based on the observed usage pattern.

The score considers signals such as repeated application usage, user coverage, and recurring activity.

Important: A High Automation Potential score is a prioritization signal. It does not confirm that automation can definitely be implemented.

---

Usage Overlap

Usage Overlap indicates how strongly the two applications are used by the same users and within related activity patterns.

A high overlap means that the applications frequently appear together in the observed usage data.

A lower overlap indicates that the applications have less consistent overlap.

Example

If many users who interact with Application A also interact with Application B within related activity patterns, the pair may have high Usage Overlap.

This provides evidence that the applications may be part of the same broader work pattern.

---

Workflow Confidence

Workflow Confidence measures how clearly the application relationship resembles a repeatable workflow.

It considers factors such as:

• Repeated application pairing
• Consistency of usage
• Directionality between applications
• Activity across users
• Recurrence over time

A High Workflow Confidence indicates that the applications repeatedly appear together in a recognizable sequence or usage pattern.

It does not necessarily mean that one application directly triggers the other.

---

Manual Work

The Manual Work indicator represents the amount of manual interaction associated with the observed workflow.

It is particularly useful for identifying workflows where users repeatedly move or handle information between applications.

Observed signals may include:

• Copying information
• Pasting information
• Repeated transfer of content between applications

A High Manual Work score combined with High Recurrence can represent an especially interesting automation candidate.

---

Sensitivity

Sensitivity indicates the potential sensitivity of information involved in the observed workflow.

The analysis can identify categories such as:

• Email addresses
• Phone numbers
• IBANs

The sensitivity level is based on the presence and volume of detected sensitive-data activity.

Consider Sensitivity together with Automation Potential when prioritizing opportunities.

---

Sensitivity Summary

The Sensitivity Summary provides additional information about sensitive-data categories detected for an application pair.

For example:

These values represent detected activity counts and not the actual sensitive information.

The feature provides visibility into potential data exposure without storing or displaying the underlying sensitive content.

---

Recurrence

Recurrence indicates how repeatedly the application pair appears in the observed usage data.

A combination of High Recurrence + High Manual Work can be particularly useful when prioritizing automation candidates.

---

Automation Opportunity Details

Select an application pair to open its detailed Automation Opportunity view.

The detailed view provides:

• Applications involved
• User information
• Activity information
• Automation Potential
• Workflow Confidence
• Manual Work
• Data Sensitivity
• Affected countries
• Affected departments

Use this information to understand where the workflow occurs, which business areas are involved, and whether the opportunity warrants further investigation.

---

Filters, Search, and Sorting

Automation Opportunities supports filters, search, and sorting for analyzing specific opportunities.

Use these controls to narrow the application-pair list and focus on opportunities relevant to your investigation.

For example, when reviewing potential automation candidates, prioritize combinations such as:

• High Automation Potential
• High Workflow Confidence
• High Manual Work
• High Recurrence
• High Users
• High Active Days

Use the resulting list as a starting point for detailed investigation rather than treating the filtered results as confirmed automation recommendations.

---

From Workforce Persona to Automation Opportunity

The two features work best when used together.

Step 1: Identify the work pattern

Start with Workforce Personas.

Look for personas with:

• High Manual Work
• High Recurrence
• High Confidence
• Significant User population

Step 2: Understand the applications

Open the persona and review Apps Used By Persona.

Look for applications that repeatedly appear together.

Step 3: Investigate the application relationship

Open Automation Opportunities and locate the relevant application pair.

Step 4: Assess the workflow

Review:

• Users
• Active Days
• Automation Potential
• Usage Overlap
• Workflow Confidence
• Manual Work
• Sensitivity
• Recurrence

Step 5: Understand the business scope

Open the detailed opportunity and review the affected:

• Countries
• Departments

Step 6: Validate the process

Confirm with the relevant business or application owner that the observed application relationship represents a genuine business workflow.

Step 7: Prioritize

Prioritize opportunities where the evidence indicates:

High Automation Potential + High Workflow Confidence + High Manual Work + High Recurrence

Consider Users, Active Days, and Sensitivity as additional context when deciding which opportunities deserve further investigation.

---

Governance Actions

The purpose of these features is to provide evidence for business and technology decisions.

Use the following approach when evaluating an opportunity.

These are investigation and prioritization actions. The features do not automatically implement or approve automation.

---

Concrete Example: Identifying an Automation Candidate

Consider a Workforce Persona with:

The persona also shows repeated use of several applications.

Investigation

1. Open the persona.
2. Review the applications used by the persona.
3. Identify applications that repeatedly appear together.
4. Open Automation Opportunities.
5. Locate the corresponding application pair.
6. Review Users and Active Days.
7. Review Automation Potential.
8. Review Usage Overlap and Workflow Confidence.
9. Review Manual Work and Recurrence.
10. Check Sensitivity and Sensitivity Summary.
11. Review the affected countries and departments.
12. Validate the workflow with the process owner.

Possible Outcome

The analysis may reveal a recurring workflow where users repeatedly transfer information between two applications.

If the opportunity also has:

• High Automation Potential
• High Workflow Confidence
• High Manual Work
• High Recurrence

the workflow becomes a strong candidate for further automation assessment.

The next step is to validate the actual business process and determine whether automation is technically and operationally appropriate.

---

Concrete Example: High Usage but Low Automation Potential

A frequently used application pair may involve:

• Many users
• High Active Days
• High Usage Overlap

but still have Low Automation Potential.

This means the applications are frequently used together, but the observed relationship provides limited evidence that the pattern represents a suitable automation opportunity.

Do not prioritize an application pair solely because many users interact with both applications.

Review Automation Potential, Workflow Confidence, Manual Work, and Recurrence together.

---

Concrete Example: High Sensitivity

An application pair may show:

• High Automation Potential
• High Workflow Confidence
• High Manual Work
• High Sensitivity

This may look attractive from an automation perspective, but the sensitive-data context should be reviewed before proceeding.

Recommended action

1. Review the Sensitivity Summary.
2. Identify the categories of sensitive-data activity detected.
3. Review the affected countries and departments.
4. Involve the appropriate security, privacy, or compliance stakeholders.
5. Determine whether the proposed automation would maintain appropriate data-handling controls.

The objective is to balance automation opportunity with data sensitivity and governance requirements.

---

How to Prioritize Opportunities

Use the following indicators together when deciding which opportunities deserve further investigation:

Strong candidate

• High Automation Potential
• High Workflow Confidence
• High Manual Work
• High Recurrence
• Significant Users
• Significant Active Days

Requires further investigation

• Medium Automation Potential
• Medium Workflow Confidence
• Medium Manual Work
• Medium Recurrence

Lower priority

• Low Automation Potential
• Low Workflow Confidence
• Low Manual Work
• Low Recurrence

These levels are not an automatic approval or rejection mechanism. They provide evidence that can help teams prioritize their investigation.

---

Important Interpretation Guidelines

Keep the following points in mind:

• A Workforce Persona represents an observed application-usage pattern.
• A persona name does not necessarily represent an official job title.
• Review the combination of applications rather than relying on one application.
• High Manual Work does not automatically mean that automation is appropriate.
• Recurrence helps identify repeated work patterns.
• An Automation Opportunity represents an observed relationship between applications.
• An application pair does not necessarily mean that the applications have a technical integration.
• High Automation Potential is a prioritization signal, not confirmation that automation can be implemented.
• Workflow Confidence describes how clearly the application relationship resembles a repeatable workflow.
• High Manual Work combined with High Recurrence can be an especially useful automation signal.
• Sensitivity should be considered before prioritizing workflows involving potentially sensitive data.
• Validate important findings with the relevant business, application, security, or compliance owners.

App Redundancy

App Redundancy helps you see where applications may do similar work, which application is the main one in each group, and what should be checked before any change is made.

App redundancy occurs when multiple applications are being used for similar purposes, and one application may potentially replace or reduce the need for another.

Primary and Redundant Applications

App Redundancy compares applications to identify potential overlap and determine whether applications may be performing similar business functions.

Primary Application

The Primary Application is the application selected as the main application for comparison within an app group. It is used as the reference point when evaluating user overlap, capabilities, usage, and other comparison metrics.

Redundant Application

A Redundant Application is an application that has significant overlap with the primary application and may provide similar functionality or serve similar business needs.

Being identified as a redundant application does not automatically mean that it should be removed. The application should be validated against business requirements, users, unique capabilities, integrations, security requirements, cost, and other organizational needs before any decision is made.

Example

Suppose an organization uses:

• Microsoft Teams for communication and collaboration
• Slack for communication and collaboration

If the same users are using both applications for similar activities, there is an application overlap. App Redundancy can identify one application as the Primary Application and the other as a potential Redundant Application for further evaluation.

How Does App Redundancy Work?

AppNavi's App Redundancy analysis can identify this overlap by looking at things such as:

• User Overlap : How many users use both applications?
• Capability Overlap : How much functionality do the applications have in common?
• Usage : How frequently are the applications being used?
• Unique Capabilities : What functionality exists only in the candidate application?
• Usage Trends : Is usage of one application increasing or decreasing?

Based on these factors, App Redundancy highlights applications that may have a high level of overlap.

What Is Application Overlap?

Application overlap means that two applications provide similar functionality or are used for similar business activities.

For example, an organization may use two different applications for managing customer relationships. If many of the same users use both applications and they provide similar capabilities, these applications may have a high level of overlap.

This does not automatically mean that one application should be removed. It simply highlights an area that may need further evaluation.

Understanding the Results

App Redundancy groups applications based on the level of overlap.

Strong Candidate

Applications in this category have a high level of overlap.

They have significant similarities in their capabilities and are often used by the same users.

These applications may be good candidates for further evaluation to determine whether both applications are needed.

Weak Candidate

Applications in this category have some level of overlap, but the overlap is not strong enough to indicate clear redundancy.

The applications may share some capabilities or users while still serving different needs.

These applications may require further investigation.

Likely Complementary

Applications in this category have limited overlap.

They may be used by some of the same users, but they generally provide different capabilities or support different business needs.

These applications are more likely to complement each other rather than duplicate each other.

App Redundancy Decision Workflow

Use the following workflow before making changes based on App Redundancy results.

1. Validate the Finding

Review the primary and potential redundant applications and validate the overlap using:

• User overlap
• Capability overlap
• Usage
• Unique capabilities
• Usage trends
• Geography and department information
• Identified risks and deviations

Confirm that the identified overlap reflects an actual business scenario and is not caused by incomplete or misleading usage data.

2. Evaluate Business Requirements

Before assigning an application for remediation, review:

• Business requirements
• User needs
• Application integrations
• Security and compliance requirements
• Application costs
• Unique capabilities
• Department or regional requirements

A high overlap score alone should not be treated as a removal decision.

3. Assign an Action

After validation, assign an appropriate action for the application.

Possible actions include:

• Retain both applications when they serve different business needs.
• Investigate further when the available evidence is not sufficient.
• Consolidate applications when the organization confirms that both applications are not required.
• Remediate the redundant application when a business decision has been made to reduce or remove its usage.

4. Remediate

Carry out the agreed action based on the business decision.

For example:

• Reduce duplicate application usage.
• Migrate users to the primary application.
• Replace or retire the redundant application.
• Update application ownership or assignment.
• Communicate the change to affected users and departments.

5. Review the Result

   After remediation, review application usage and overlap again to confirm that the expected change has occurred.

   Continue monitoring the applications where required to ensure that duplicate usage does not return.

Key Metrics

App Redundancy uses several metrics to help understand the relationship between applications.

User Overlap

Shows how many users are using both applications.

A higher user overlap means that more users are working with both applications.

Capability Overlap

Shows how many capabilities are shared between the applications.

A higher capability overlap means that the applications provide more similar functionality.

Higher Usage Than Primary

Shows whether the candidate application is being used more than the primary application.

This can help identify applications that may have a significant role in users' daily work.

Unique Capabilities

Shows capabilities that are available in one application but not the other.

These unique capabilities are important when evaluating whether applications can actually replace one another.

Usage Trend

Shows how application usage changes over time.

This can help you understand whether an application is becoming more or less important to users.

Primary and Candidate Applications

App Redundancy compares applications using two terms:

Primary Application

The application selected as the main application for comparison.

Candidate Application

The application being compared with the primary application to determine how much their usage and capabilities overlap.

For example:

Primary: Microsoft Teams
Candidate: Slack

The analysis then evaluates how much Teams and Slack overlap in terms of users, capabilities, and usage.

Dashboard summary cards

Confidence labels

Geography and department values

Risks and deviations

These items tell you what deserves attention before replacing or consolidating an app. They are not automatic decisions.

Important Note

Business requirements, user needs, costs, integrations, security, and unique application capabilities should also be considered before making a final decision.

Example

Imagine an organization uses two applications for project collaboration.

Application A

• Used by 800 users
• Provides project management and collaboration features

Application B

• Used by 600 users
• Provides similar project management and collaboration features
• 500 users use both applications

Because many users use both applications and the applications provide similar capabilities, App Redundancy may identify Application B as a potential redundancy candidate.

The organization can then investigate whether both applications are required or whether they serve different business needs.

Summary

App Redundancy gives you a simple way to identify applications that may overlap in users, functionality, or usage.

It helps you understand where potential duplication exists and provides useful information for making better application portfolio decisions.