Data & Reporting

Stop guessing. Start seeing what's actually happening in your business.

You're probably sitting on more data than you realize. The problem isn't the data. It's that no one has turned it into something useful.

I help you build reporting systems that give you clarity, not just numbers.

What this can look like

Dashboards & scorecards: real-time visibility into the metrics that matter
Forecasting models: plan ahead with confidence, not gut feelings
KPI & metrics frameworks: define what "good" looks like for your team
Data cleanup & integration: connect your tools so information flows, not fragments
Executive reporting: the right information, at the right level, at the right time

Signs you might need this

You make decisions based on instinct because you don't have reliable data
Reports take hours to pull together and are outdated by the time they're done
Different teams are tracking the same things in different ways
You know something's off but can't pinpoint where

Some of the Technologies I've Used

Redshift

MySQL

Data Studio

Google Sheets

Google Apps Scripts

JavaScript

Mailchimp

Sample: Document Processing Dashboard

Built in Looker Studio pulling from Redshift, this dashboard tracked time-to-close trends week over week alongside processing time percentiles. The p90 and p95 figures gave leadership an early signal on capacity pressure before it reached SLA thresholds.

Document Processing Dashboard

2.4h

Avg Time
to Close

14.3m

p90 Process
Time

95%

SLA
Compliance

247

Cases
Closed

Time to Close (hours) — 8-week trend

W1W2W3W4 W5W6W7W8

Processing Time by Percentile (minutes)

p50

4.2 min

p75

7.8 min

p90

14.3 min

p95

22.1 min

p99

31.5 min

Sample: Capacity Model — Task Breakdown

Modeled two seasons (low and high volume) across five work types and two employee skill levels. Volume and time-per-task figures came from three sources: Redshift for phone and document data, Asana for project work hours, and Google Calendar for meeting time.

Operations Capacity Model (28-week period)

Task Type	Level	Vol / Low	Vol / High	Hrs / Low	Hrs / High
Phone Calls	Senior	108	130	32.4	39.0
Phone Calls	Junior	542	802	108.4	160.4
Support Tickets	Senior	777	719	543.9	503.3
Support Tickets	Junior	1,730	4,273	519.0	1,281.9
Project Work	Senior	250	200	250.0	200.0
Meetings	Junior	50	65	50.0	65.0
Document Processing	Junior	—	5,673	—	94.6
Total hours needed				1,603.7	2,454.2

Staffing & Cost Summary

Total hours rolled up to an FTE headcount estimate, with a contractor rate comparison to give leadership concrete numbers for staffing decisions.

FTE Estimate

Hours needed (low season) 1,603.7 hrs

Hours needed (high season) 2,454.2 hrs

FTEs required (high season) 4.83

Contractor rate comparison (28 wks)

$25 / hr $18,149

$23 / hr $16,055 save $2,094

$20 / hr $13,961 save $4,188

Agent Performance Classification

Phone data from Redshift was used to classify agents as senior or junior based on two p75 thresholds: call volume and average handle time. The split fed directly into the capacity model.

Phone Data (Redshift)

Agent	Calls	Min/Call
A. Torres	195	7.6	High
J. Kim	205	8.1	Low
M. Okafor	228	8.3	Low
D. Chen	135	11.3	Low
S. Rivera	113	6.5	Low

High: >150 calls AND <7.7 min/call (p75 thresholds, Redshift)

Examples of My Work

Document Processing Capacity Report

Created a capacity report using Redshift data, SQL, Google Sheets, and Apps Scripts to show predictive incoming document counts and the headcount needed for processing. The team handled over 25,000 documents per year with an average of just two workers per day. The report gave leadership clear visibility into staffing needs and helped drive systems improvements that reduced processing time per document by 70% in a single quarter.

Support Case Routing Analysis

Conducted a data analysis on historical support cases, examining post-hoc categorizations and the frequency of subject-line keywords. Used those findings to rebuild a JavaScript case-assignment algorithm, enabling true skills-based routing for the first time.

Mailchimp API Custom Report

Built a custom report using Mailchimp's API for a nonprofit client to track click-throughs on important document links. The report surfaced engagement data that wasn't available in Mailchimp's standard dashboard, giving the team actionable insight into how constituents were interacting with key materials.

Historical Document Organization Scripts

Wrote scripts to sort and rename hundreds of historical documents, automatically placing them into an organized folder structure. Eliminated a significant manual backlog and established a consistent naming and filing convention going forward.