Exploring scenario modelling to help users map actions to financial impact
INDEPENDENT UX STUDY, 2025
Simplifying ESOP Management for Employees, Part 2
Picking up from earlier
Part 1 addressed gaps in user understanding of ESOP timelines. This case study builds on it to explore forecasting solutions.
Problem recap: Users struggle to extract actionable insights from ESOP tools
There’s a gap between how data is presented and the takeaways users need to plan their ESOPs.
Tools show isolated statistics like a report
Users can’t compare figures or analyze decisions
Users are left to manually interpret and contextualize data
People said they find it hard to understand possible outcomes when making decisions
Here’s where I could sense their frustration:
I keep using multiple spreadsheets to figure out which approach works best for me
Users are are manually managing complex calculations to compare different ESOP strategies and scenarios.
The taxes on my ESOP confuse me, and I’m worried I might mess something up and lose money
Exercising options triggers tax liabilities and tax treatments can be difficult to understand.
Employees have trouble estimating the impact of different decisions, and are scared of making mistakes.
Are current products doing anything to make this experience easier?
Platforms provide forecast tools. But they don’t address the real-world complexity of ESOPs
Present tools answer “How much could I make?” but not “What would happen if I acted on it?”
Platforms reduce employee tools to simple valuation sliders, giving surface-level visibility but no real-world complexity.
Most platforms only provide single-variable calculators, while equity outcomes depend on multiple interrelated factors
Users don’t make decisions in silos. Changing 1 factor (e.g., timing of exercise) directly alters others (such as tax treatment, etc.).
Scenario modeling features are prioritized for companies but are considered simple ‘add-ons’ in the employee view
Employee-facing tools are treated as extras for engagement rather than a core feature (as business are SAAS customers).
My Realization: Employees lack decision-support tools that help them evaluate hypothetical actions and strategies
The gap? Users want to compare trade-offs of different decisions before acting on them
If I vest now, how much do I pay to exercise, versus later? What are my tax liabilities if I sell today, versus next year?
How can we enable employees to explore the impacts of possible scenarios?
Idea: Integrated action-to-impact modelling tool
By unifying scattered forecast tools into one view, the need for multiple calculators and analyses can be eliminated
Approach 1: Multi-view workspace for scenario comparisons
Uses a spreadsheet pattern so that users can contrast possibilities
PROS
Comparative decision-making across multiple scenarios
Provides high analytical depth by exposing raw KPIs side by side, which reflect impact instantly.
CONS
Can feel data-dense, number-heavy and complex
May benefit power-users but could alienate employees who lack financial experience.
Approach 2: Forecasting layer within vesting chart
Can forecasting be incorporated into existing tools visualizing ownership?
PROS
Provides contextual insights when viewed with charts
Leverages a familiar chart that users already understand, and makes the forecast feel time-anchored and real.
CONS
Too much going here- visually and cognitively
A lot of overlays make this simple tool complex to interpret, and causes risk of information overload.
Limits forecasting as user cannot play with values here
These charts are generated on data sets provided the company, remote scope for user to customize figures.
Approach 3: ‘Build your own dashboard’ configuration
Allowing users to customize the output figures they want to see
PROS
Users can focus on only what is relevant to them
Customization reduces data clutter, avoiding overwhelming first time users.
Supports extra KPIs without overloading default view
More detailed figures can be included, as they will be added according to user requirement.
CONS
Requires initial set-up effort by user
Needs extra decision making by the user to choose what they want, or not. Might be tough for those without clarity.
Which approach aligns best with the user’s needs?
I reconnected with my interviewees, to get their input on the iterations
These were two valuable comments that stood out:
When it asked me ‘What if I exercise today?’, it felt easier to follow… else I didn’t really know where to start
Inexperienced users felt more comfortable when forecasting was introduced as a first-person question.
Experienced users valued customization + comparison features; newer users found navigating them slightly complex
While these features gave experienced users more control and flexibility, the complexity was also intimidating for newer users
Aha Moment: New users are more comfortable starting with open-ended questions, than directly engaging with tools
How do we bridge the gap between experienced and new employees?
Final Approach: Integrating an AI-powered question bar
Instead of adjusting inputs manually, users can ask questions. The AI updates and configures the dashboard on it’s own
Users can interact with the dashboard in natural language, reducing the barrier of entry to interact with the tool
Removes the need to first learn which variables to adjust or where to start; the question bar provides a clear, intuitive entry point.
This solution still maintains usability for users needing advanced functions
Advanced users who know what they want to simulate will prefer interacting directly with controls.
Manual input fields are disabled when the AI support is active
Users should not confuse AI calculations with values they edited themselves, when AI support is enabled
The dashboard is accessed only through the AI chat, clearly separating AI-driven and manual modes.
Guardrails are critical with AI support: Computation must not be interpreted as advice
Without guardrails, the product risks being seen as giving regulated financial advice, which has compliance risks.
Employees are enabled to analyze without external guidance
Users can map their actions to financial impact through this solution, to analyze hypothetical ESOP decisions and trade-offs.
Users can now independently explore decision-related ‘what if’ questions like:
How much will it cost if I exercise my shares in June 2026?
What will my gains be if I sell 50% of my shares at today’s valuation?
If I delay exercising by a year, how does it change my costs and taxes?
While largely qualitative, the impact can also be reflected in KPIs like:
Decrease in HR support tickets
Fewer tickets means users are resolving doubts independently, with less dependency on HR.
Increase in CSAT scores
Tracking improvement in customer satisfaction scores through in-platform surveys after key actions.
To wrap up, here are a few reflections
I iterated on solutions without tech constraints, to focus on user needs & imagine the ideal experience
This let me design freely, while knowing many details may change later based on technical feasibility.
A key realization was seeing how the same feature can overwhelm one user and empower another
It was important to return to users after iterating, to see which directions resonated with them and which did not.
INDEPENDENT UX STUDY, 2025
Exploring scenario modelling to help users map actions to financial impact
Simplifying ESOP Management for Employees, Part 2
Picking up from earlier
Part 1 addressed gaps in user understanding of ESOP timelines. This case study builds on it to explore forecasting solutions.
Problem recap: Users struggle to extract actionable insights from ESOP tools
There’s a gap between how data is presented and the takeaways users need to plan their ESOPs.
Tools show isolated statistics like a report
Users can’t compare figures or analyze decisions
Users are left to manually interpret & contextualize data
People also said they find it hard to understand possible outcomes when making decisions
Here’s where I could sense their frustration:
I keep using multiple spreadsheets to figure out which approach works best for me
Users are are manually managing complex calculations to compare different ESOP strategies and scenarios.
The taxes on my ESOP confuse me, and I’m worried I might mess something up and lose money
Exercising options triggers tax liabilities and tax treatments can be difficult to understand.
Employees have trouble estimating the impact of different decisions, and are scared of making mistakes.
Are current products doing anything to make this experience easier?
Platforms provide forecast tools. But they don’t address the real-world complexity of ESOPs
Present tools answer “How much could I make?” but not “What would happen if I acted on it?”
Platforms reduce employee tools to simple valuation sliders, giving surface-level visibility but no real-world complexity.
Most platforms only provide single-variable calculators, while equity outcomes depend on multiple interrelated factors
Users don’t make decisions in silos. Changing 1 factor (e.g., timing of exercise) directly alters others (such as tax treatment, etc.).
Scenario modeling features are prioritized for companies but are considered simple ‘add-ons’ in the employee view
Employee-facing tools are treated as extras for engagement rather than a core feature (as business are SAAS customers).
My Realization: Employees lack decision-support tools that help them evaluate hypothetical actions and strategies
The gap? Users want to compare trade-offs of different decisions before acting on them
If I vest now, how much do I pay to exercise, versus later? What are my tax liabilities if I sell today, versus next year?
How can we enable employees to explore the impacts of possible scenarios?
Idea: Integrated action-to-impact modelling tool
By unifying scattered forecast tools into one view, the need for multiple calculators and analyses can be eliminated
Approach 1: Multi-view workspace for scenario comparisons
Uses a spreadsheet pattern so that users can contrast possibilities
Input variables
Output Figures
PROS
Comparative decision-making across multiple scenarios
Provides high analytical depth by exposing raw KPIs side by side, which reflect impact instantly.
CONS
Can feel data-dense, number-heavy and complex
May benefit power-users but could alienate employees who lack financial experience.
Approach 2: Forecasting layer within vesting chart
Can forecasting be incorporated into existing tools visualizing ownership?
‘What-If’ Layer Toggle
PROS
Provides contextual insights when viewed with charts
Leverages a familiar chart that users already understand, and makes the forecast feel time-anchored and real.
CONS
Too much going here- visually and cognitively
A lot of overlays make this simple tool complex to interpret, and causes risk of information overload.
Limits forecasting as user cannot play with values here
These charts are generated on data sets provided the company, remote scope for user to customize figures.
Approach 3: ‘Build your own dashboard’ configuration
Allowing users to customize the output figures they want to see
User can choose from a list of planned output figures
PROS
Users can focus on only what is relevant to them
Customization reduces data clutter, avoiding overwhelming first time users.
Supports extra KPIs without overloading default view
More detailed figures can be included, as they will be added according to user requirement.
CONS
Requires initial set-up effort by user
Needs extra decision making by the user to choose what they want, or not. Might be tough for those without clarity.
Which approach aligns best with the user’s needs?
I reconnected with my interviewees, to get their input on the iterations
These were two valuable comments that stood out:
When it asked me ‘What if I exercise today?’, it felt easier to follow… I didn’t really know where to start otherwise
Inexperienced users felt more comfortable when forecasting was introduced as a first-person question.
Experienced users valued customization + comparison features; newer users found navigating them slightly complex
While these features gave experienced users more control and flexibility, the complexity was also intimidating for newer users
Aha Moment: New users are more comfortable starting with open-ended questions, than directly engaging with tools
How do we bridge the gap between experienced and new employees?
Final Approach: Integrating an AI-powered question bar
Instead of adjusting inputs manually, users can ask questions. The AI updates and configures the dashboard on it’s own
Users can interact with the dashboard in natural language, reducing the barrier of entry to interact with the tool
Removes the need to first learn which variables to adjust or where to start; the question bar provides a clear, intuitive entry point.
This solution still maintains usability for users needing advanced functions
Advanced users who know what they want to simulate will prefer interacting directly with controls.
Manual input fields are disabled when the AI support is active
Users should not confuse AI calculations with values they edited themselves, when AI support is enabled
The dashboard is accessed only through the AI chat, clearly separating AI-driven and manual modes.
Guardrails are critical with AI support: Computation must not be interpreted as advice
Without guardrails, the product risks being seen as giving regulated financial advice, which has compliance risks.
Employees are enabled to analyze without external guidance
Users can map their actions to financial impact through this solution, to analyze hypothetical ESOP decisions and trade-offs.
Users can now independently explore decision-related ‘what if’ questions like:
How much will it cost if I exercise my shares in June 2026?
What will my gains be if I sell 50% of my shares at today’s valuation?
If I delay exercising by a year, how does it change my costs and taxes?
While largely qualitative, the impact can also be reflected in KPIs like:
Decrease in HR support tickets
Fewer tickets means users are resolving doubts independently, with less dependency on HR.
Increase in CSAT scores
Tracking improvement in customer satisfaction scores through in-platform surveys after key actions.
To wrap up, here's a few reflections
I iterated on solutions without tech constraints, to focus on user needs and to imagine the ideal experience
This let me design freely, while knowing many details may change later based on technical feasibility.
A key realization was seeing how the same feature can overwhelm one user and empower another
It was important to return to users after iterating, to see which directions resonated with them and which did not.
© 2025 by Vishruth. All rights reserved
© 2025 by Vishruth
