Selected work
Case Studies
Three examples of investment analysis, forecasting, and executive reporting. Company details and supporting data are generalized or anonymized to protect confidential information.
Case Study 01
Broadband Expansion Investment Modeling
- Business problem
- Different markets and cost assumptions made broadband investment opportunities difficult to compare.
- My contribution
- Built a common framework for evaluating project returns.
- Project scope
- $1.2B+ in potential projects; more than one million underserved locations analyzed.
Expansion Screening Model
Illustrative data · generalized example
Representative cluster · $M
Take-rate scenario
IRR
15.2%
Hurdle 12.0% · 35% take rate
NPV
$9.4M
9% discount rate, 10 yrs
Cost / Passing
$3.9K
Rural aerial & underground mix
Payback
6.8 yrs
Discounted basis
Build cluster ranking
Ranked by IRR
Screening decision: Advance Clusters 01 and 02 — both clear the 12% hurdle with payback inside eight years at a 35% base take rate. Cluster 03 returns for funding and take-rate review; Cluster 04 is deferred pending cost-per-passing reduction.
| Cluster | Passings | Capex | IRR | Payback | Screen |
|---|---|---|---|---|---|
| Cluster 01 | 14,200 | $55M | 15.2% | 6.8 yrs | Fund |
| Cluster 02 | 9,800 | $43M | 12.6% | 7.9 yrs | Fund |
| Cluster 03 | 7,300 | $38M | 9.8% | 9.4 yrs | Review |
| Cluster 04 | 5,100 | $34M | 6.4% | 12.1 yrs | Defer |
Swipe or use the arrow keys to see all columns.
Cumulative discounted cash flow — Cluster 01
$M · Y0–Y9
- Base case · NPV $9.4M
Prioritization output
Advance Clusters 01 and 02 — both clear the 12% hurdle with payback inside eight years at a 35% base take rate. Cluster 03 returns for funding and take-rate review; Cluster 04 is deferred pending cost-per-passing reduction.
Representative view based on actual work; figures generalized to protect confidential information.
Business Challenge
Market conditions, build costs, and operating assumptions varied across a large infrastructure pipeline. Each opportunity needed to be evaluated on the same basis without losing the differences that affected its economics.
Analytical Approach
I combined operating forecasts with ROI, IRR, NPV, and payback calculations, then tested how changes in key assumptions affected returns. Scenario comparisons made the financial trade-offs between opportunities visible.
Tools and Methods
- Advanced Excel
- Financial modeling
- Power Query
- Scenario analysis
- Dashboard reporting
Outcome
The analysis gave decision-makers a consistent basis for prioritizing potential projects and weighing financial returns against investment requirements.
Case Study 02
Audit Income Forecasting and Budgeting
- Business problem
- Recovery volume and account complexity made monthly audit income difficult to forecast.
- My contribution
- Linked recovery assumptions to staffing costs and expected margin.
- Project scope
- An audit program covering more than $100M in unclaimed and reportable assets.
Audit Income & Budget Model
Illustrative data · generalized example
Monthly · $M
Recovery scenario
Forecast income
$1.54M
Base case, monthly
Budget margin
34%
After staffing cost
Break-even recovery
$33.9M
Monthly recovered value covering 9-FTE cost
Forecast accuracy
±3.2%
Avg. abs. variance, Mar–May
Audit income vs. budget
$M per month · Jan–May actuals · Jun–Aug Base forecast
- Budget
- Actual at/above
- Actual below
- Forecast (lighter)
Key assumptions
- Forecast horizon
- 12 months
- Base recovery rate
- 6.2% of reviewed value
- Accounts per FTE / mo
- 180
- Billing rate
- 3.0% of recovered value
- Base staffing
- 9 FTE
Driver sensitivity — monthly margin
Margin, pts
- Recovery rate-3.4 / +3.1 pts
- Account complexity-2.6 / +1.2 pts
- Staffing (FTE)-2.1 / +2.4 pts
- Billing rate-1.5 / +1.8 pts
- Turnaround time-1.3 / +1.1 pts
Downside impact shown left of centre, upside right; recovery rate and account complexity dominate outcomes.
Recovery scenarios
Income · margin
| Scenario | Income | Margin | Assessment |
|---|---|---|---|
| Upside | $1.82M | 44% | Above target |
| Base | $1.54M | 34% | At target |
| Downside | $1.21M | 16% | Below target |
Swipe or use the arrow keys to see all columns.
Budgeting output
Hold 9 FTE in base case — at 6.2% recovery the program clears the break-even recovery volume with 34% margin. Upside recovery supports a 10th FTE; the downside case flags staffing reduction if complex accounts push throughput below 150 accounts per FTE.
Representative view based on actual work; figures generalized to protect confidential information.
Business Challenge
Banking and brokerage audits differed in account mix, workload, and turnaround time. Staffing decisions needed to reflect those differences and the range of possible recoveries before the next quarter.
Analytical Approach
I used historical recovery rates, account mix, and team productivity to estimate monthly income. I then compared base, upside, and downside cases with staffing tiers and per-account processing costs to identify break-even recovery volumes and pressure on margins.
Tools and Methods
- Excel
- Forecasting
- Budgeting
- Variance analysis
- Scenario modeling
- Dashboard reporting
Outcome
Leadership could compare recovery scenarios with operating costs and adjust staffing plans before the quarter, informing audit strategy and resource allocation.
Case Study 03
Monthly Executive Audit Status Report
- Business problem
- Scattered audit updates made it hard to track progress and financial status.
- My contribution
- Created a monthly report with consistent KPI definitions.
- Project scope
- $100M+ in identified assets; reporting across 30+ states and clients with billions in assets under management.
Monthly Executive Audit Status
Illustrative data · generalized example
Report period · May
Report view
Accounts reviewed YTD
12,400
On plan through May
Assets identified YTD
$84.6M
Sum of four segments below
Recovery rate
6.4%
Recovered ÷ reviewed value · target 6.0%
Accounts at risk
38
Awaiting client response
Recovered vs. reportable value
$M per month · Jan–May · subset of identified value
- Reportable
- Recovered
Month-end summary
Recovery rate holds above target at 6.4% with $84.6M identified YTD across four segments. Brokerage — West is flagged at risk pending client response on open accounts, and Brokerage — Metro is on watch in reconciliation; both Banking segments are on track through field review and reporting.
Representative view based on actual work; figures generalized to protect confidential information.
Business Challenge
Audit work crossed multiple clients, account types, and teams. Executives needed to see which accounts required attention alongside asset totals and budget performance, without piecing together separate working files.
Analytical Approach
I brought status data into one report covering accounts reviewed, assets identified, recovered versus reportable value, budget-to-actual spend, forecast accuracy, and accounts at risk. Each monthly update used the same definitions and layout.
Tools and Methods
- Excel
- Power Query
- Dashboard reporting
- Variance analysis
- KPI development
Outcome
The report reduced manual preparation and made month-to-month comparisons more reliable, giving leadership a repeatable view of progress, financial status, and accounts at risk.