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DATA ANALYSIS

Insight from Raw Data

Data analysis uncover insights to identify results, trends, & recommendations based on current and past data. Asking the right questions to make the right decisions for your business or project. Think “What happened, why did it happen, and what can we learn?” Results can be presented in dashboards, reports or presentation format with recommendations and follow-up steps so well-informed, data-driven decisions can be made, costs can be saved and processes streamlined for all around optimization.

Capabilities

Specializing in data interpretation, requirement gathering, and strategic planning, I leverage industry insights to deliver actionable recommendations. Example of analysis capabilities: 

  • Data cleaning & transformation (Excel, Power Query, Python, SQL)

  • Descriptive & diagnostic analysis

  • Correlation and trend identification

  • Comparative analysis (e.g., TY vs LY, A/B test outcomes)

  • Data storytelling

Sample Use Cases

Discover how I have helped businesses enhance decision-making processes, streamline operations, and improve overall performance through my analytical expertise. Sample use cases include but not limited to: 

  • Sales performance by region and department

  • Profit margin analysis by category

  • Customer churn investigation

  • Underperforming store analysis

  • Product cannibalization discovery

Work Samples

Sales Performance by Region, Department, & Store in Tableau

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Tiered Subscriptions Based on Desired ROI

Need: Amazon implemented new reimbursment restrictions that would affect my client's bottom line. The client wanted to change pricing strategy from a pay-per-service to a subscription based model for their Amazon FBA business.

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Objective: Find a subscription price point that would meet the ROI needs of the client.​

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Methodology: Create a dynamic model that identifies the best subscription price point while allowing the client to understand how different business strategies can positively or negatively affect their ROI.​​​​

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Factors Considered

  • Costs

    • LY vs. CY ​Costs (CAC, VC, FC) 

      • CY Costs is a dynamic field alllowing the client to see how YoY% change of costs combined with other factors affects ROI​

  • Customer Tier Segmentation​​

    • Average Revenue / Average Reimbursment = Current Charge Rate

      • Reimbursment = $'s received by client's customers as a result of using the service​

      • Revenue = $'s received by the client as a commission (charge rate) of the reimbursement

    • The current charge rate for FY24 combined with the percentage hit of the new Amazon regulations was used to estimate the potential monthly reimbursement for customers and estimated revenue for my client for FY25.

  • Price Point​

    • The subscription price point as a % of reimbursment cannot be higher than the current charge rate.

    • A dynamic field that evaluates the cost:revenue ration of lower revenue generating tiers. 

      • I found the point at which each tier would no longer be profitable​

  • Churn​

    • I forecasted a churn rate per tier to implement in the calculation​

  • New Seller Aquisition Strategy​

    • This is a dynamic field that educates the sales team as to which customer tier needs to be targeted AND the necessary minimums and maximums of selelr acquisition needed per tier to achieve the desired ROI. For example, the sales team cannot onboard customers of the lowest tier without risking negative ROI.​

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Workforce + Revenue Optimization Analysis

OBJECTIVE:

The client is looking to optimize workforce planning to achieve 43% growth and be in line with the $1B revenue goal ($750M less salaries) for the next fiscal year.

ASSUMPTIONS: 

  • Growth Rate for Fiscal Year: 30%

  • Annual Raise: 5%

  • Net Revenue = Gross Revenue – Total Compensation

STRATEGIES TO ANALIZE:

  1. Growth in Business: Assume consistent compensation structure and no growth in headcount.  Optimize by assuming company grows its book of business (30%).

  2. Commission Structure & Quota: Modify the pay structure to boost incentives for employees & maximize net revenue.

  3. Headcount: Increase the headcount

  4. Combination: Combine the above 3 strategies (modifying quotas, growth, headcount, and commission structure to optimize forecasted revenue for the upcoming fiscal year.

Strategy 1: 

Organic Growth

 

Assumptions: 

  1. Annual growth ~30%

  2. Commission Structure, Quota, and Headcount remain unchanged.

 

Results:

We can automatically rule out Strategy 1 on its own knowing that we need at least 43% growth to achieve a $1B gross revenue goal.

Strategy 2: 

Change in Commission

Structure & Quotas

 

Assumptions: 

  1. Annual Raise of 5%

  2. Account executives will generate more revenue in direct proportion to the additional income they receive.


Results:

Only 9% increase in gross revenue compared to the 43% increase needed to achieve revenue goal.

Strategy 3: 

Headcount Increase

 

Assumptions: 

  1. Headcount increases from 1000 to 1200 employees (+200 employees)

  2. Additional Employees driving incremental revenue NOT Performance

  3. No change in commission structure


Results:

Only 20% increase in gross revenue compared to the 43% increase needed to achieve revenue goal.

Strategy 4: 

Combined Strategies

 

Assumptions:

  1. Headcount has increased

  2. Commission Structure has changed/increased with quotas modified respectively 

  3. The company experience a natural growth within the market


Result:

We exceed the $1B Gross Revenue goal by 16%

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Conclusion

When using a combined strategy method of modifying quotas, headcount, commission structure and organic growth, we surpass our $1B GR goal and reach 59% growth for the next fiscal year.

Recommendations

Headcount: Increase employee headcount by 200.
Commission Structure: Implement the following new structure.

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Overall Comparison

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