Guy Gniotczynski

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Excel and Sheets

Project: The Institutional Strategic Audit (2020–2025)
A Multi-Stakeholder Analysis of Operational Health & 5-Year Strategic Vision
[Status: Active Investigation — Strategic Dashboards & Solutions Pending]
Project Overview I am currently finalizing a comprehensive strategic audit that examines five years of longitudinal data (2020–2025) to identify the hidden drivers of organizational success. This project was born from a need to bridge the gap between siloed divisional data and high-level executive decision-making. By synthesizing half a decade of records, I am developing a multi-stakeholder reporting suite and a comprehensive 5-year strategic plan designed to align the goals of three distinct leadership perspectives:
The Operational Leader: Correlating historical performance trends with personnel stability and recruitment efficiency.
The Stakeholder Advocate: Mapping the user lifecycle and utilizing retention metrics as a proxy for engagement and satisfaction
The Fiscal Executive: Auditing 5 years of fiscal data to ensure long-term revenue sustainability and equitable resource allocation
The Technical Architecture: Data Modeling & Standardization
To transform thousands of lines of non-uniform data into a roadmap, I utilized a sophisticated "Multi-Tool" workflow:
Advanced Data Modeling: Using Excel Data Models and Pivot Tables to unify disparate datasets into a single source of truth.
Normalized Benchmarking: All metrics have been scaled to a 100-point benchmark and adjusted for Full-Time Equivalent (FTE) staffing to ensure fair comparison across business units of all sizes
Data Privacy by Design: All sensitive records are protected via custom anonymization formulas to ensure 100% privacy for the institution and its stakeholders
The Deliverable: Data-Driven Solutions The final release will feature a suite of interactive charts and visualizations, paired with a 5-year strategic roadmap. This plan provides actionable solutions for resource optimization and financial health, tailored for diverse stakeholders with varying interests in the organization’s long-term success.

Training Analysis Project OverviewThis project is the culmination of a longitudinal study drawing from my 27 years of high-performance coaching experience. To identify the universal drivers of peak performance, I developed a custom ETL (Extract, Transform, Load) pipeline to aggregate and unify data from multiple teams and historical sources.The project was designed to solve a recurring technical bottleneck: the lack of integration between training software and wellness tracking platforms. By synthesizing thousands of data points into a single "Performance Intelligence" dashboard, I moved beyond siloed reporting to create a unified view of how physical workload and mental recovery overlap.Note on Data Privacy: To ensure 100% confidentiality, this analysis utilizes a multi-source dataset that has been fully anonymized. All individuals and organizations have been assigned unique, non-sequential IDs to allow for deep-dive analysis without revealing Personal Identifiable Information (PII).Technical Workflow & Data Integrity
I developed a rigorous three-stage workflow to bypass software silos and ensure maximum data accuracy:Automated Extraction (Python): Utilizing a custom Python script, I extracted, cleaned, and combined over 4,400 rows of raw data from disparate platforms. This script automated the heavy lifting of data cleaning that would typically take over 10 hours of manual labor.The Integrity Check (Excel): To ensure 100% accuracy before deployment, the unified data was exported to Excel for a final manual audit and validation. This "Human-in-the-loop" step ensured that all edge cases were accounted for and the data remained clean and consistent.Platform Integration (Google Sheets): Validated data was then moved into Google Sheets to serve as the backend for the visualization layer, allowing for real-time collaboration and accessibility for the coaching staff.Custom Visualization Layer: I designed a dashboard to "overlay" the two disparate datasets. Using IFERROR(VSTACK(...)) and VLOOKUP, I created a unified view that lets coaches see how wellness dips (such as sleep or stress) directly correlate with training performance.Impact & Key Findings
Member 25: Validating Training Shifts
The Insight: By comparing training blocks from 2024 to 2025, the data highlighted a significant shift in the November training cycle.The Result: The individual achieved Lifetime Bests in 2025. By centralizing this data, we can now mathematically replicate the training percentages that led to that success for future cycles.Member 19: Holistic Coaching Adjustments
The Insight: With consistent wellness data, we identified specific high-stress periods in the organization’s calendar.The Result: We moved beyond "volume-only" metrics and adjusted performance expectations and communication based on the individual's recovery state.Conclusion
This project demonstrates my ability to identify a technical bottleneck and build a custom, secure solution. By bridging incompatible software programs through a Python-driven ETL process, I saved the division significant manual labor and provided the staff with a "Custom Visual" that neither original platform could provide.Note: The video walkthrough is currently being updated to reflect the latest dashboard improvements and UI enhancements. Check back soon for the new narrated demonstration.

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Tableau

https://public.tableau.com/app/profile/guy.gniotczynski/viz/SalesData_17655531124740/Dashboard1Project Overview
The goal of this analysis was to optimize lead distribution for an outside sales consultant. By analyzing historical sales data by city, I aimed to identify the consultant’s "high-conversion zones" to ensure their time was spent where they were most likely to close deals.Technical Workflow
Geospatial Data Cleaning: I used Excel to aggregate sales performance data, ensuring city names and regional markers were standardized for accurate mapping.Performance Mapping: I built a visualization in Tableau to map sales success rates across various territories, allowing for a clear comparison of revenue generated per location.Key Findings & Actionable Insights
Identifying Top Markets: The analysis clearly identified Crystal Lake, IL as the consultant’s most successful territory, closely followed by Waukegan, IL.Strategic Lead Reallocation: Rather than a "one-size-fits-all" approach to leads, I recommended reallocating future leads specifically within these high-performing zip codes. This ensured the consultant was working in environments where they had an established track record and market familiarity.The Impact
By shifting the focus to these high-success areas, the company was able to maximize the consultant’s efficiency.This strategic reallocation led to:
Revenue Growth: An overall increase in corporate revenue by [XX%].Operational Efficiency A significant reduction in travel time and cost by narrowing the geographic focus to high-conversion regions.

Project: Data for Good — Bridging the Tech Gap for Non-Profits
Reclaiming Engagement Through Strategic Insight and EmpathyProject Overview
Technology should be a bridge, not a barrier. However, many non-profits—the organizations doing the most vital work in our communities—often struggle with outdated systems that make their mission harder to achieve. Recognizing this, I launched a proactive initiative to provide pro-bono data consulting for organizations across the country. My goal was simple: to help these teams stop guessing and start using their data to build deeper, more meaningful connections with their stakeholders.The Human Challenge: Working Beyond Legacy Systems
For this specific organization, the hurdle was a 15-year-old CRM. While it could track basic "Open Rates," it left the staff completely in the dark regarding actual conversations. They were sending out messages without knowing if anyone was truly listening or responding. I stepped in to build a custom data pipeline where no native reporting existed, giving them a voice and a clear view of their impact.Technical Workflow: Integrity, Privacy, and Precision
To ensure the results were driven by truth rather than intuition, I developed a workflow that prioritized both scientific rigor and data security:A Commitment to Privacy: Because I was handling sensitive community data, I built a randomized ID system within Excel. While the organization held the "Master Key" to names and identities, I worked strictly with anonymized, non-repeating IDs. This allowed me to conduct a high-level audit without ever compromising the privacy of the individuals they serve.Manual Care Meets Automated Speed: I utilized a custom Python script to extract a decade’s worth of data from the legacy CRM. To capture the "human" side of the data—the actual replies—I performed a targeted manual extraction from the organization's inbox, unifying these disparate sources to see the "full picture" of their engagement for the first time.Syntactic Pattern Analysis: Once I identified the top-performing messages, I analyzed the structural patterns that led to success. I wasn't just looking for "words that sell," but for the specific themes and structures that fostered genuine interaction and trust.Impact & The Path Forward
Empowering the Staff: The analysis revealed a clear disconnect between passive opens and active replies. I provided the team with a "Structural Roadmap," helping them shift away from generic outreach toward messaging that invites real conversation and community action.Advocating for Growth: By providing a "Shadow Invoice"—detailing the technical labor and manual hours required to keep these old systems running—I am helping the organization build a financial case for the modern tools they deserve. This isn't just about a better CRM; it’s about ensuring they have the resources to sustain their mission for the next 15 years.Conclusion
This project is a testament to my belief that data should serve people. It demonstrates my ability to navigate technical bottlenecks with a proactive, problem-solving mindset, translating complex technical labor into a human-centered strategy that drives both organizational growth and community impact.https://public.tableau.com/app/profile/guy.gniotczynski/viz/MarketingAnalysis_17660733851120/Dashboard1#1

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PowerBI

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