Strategic Analysis of Options

Executive Summary

This report addresses the discrepancies and issues found within the STAR reporting system at Cox Communications, which have significantly impacted my sales performance and compensation. The key findings include underreported revenues, missing sales data, and technical issues affecting productivity. Recommendations for resolving these issues are provided to ensure accurate reporting and fair compensation.

Introduction

Since my employment at Cox Communications, I have encountered multiple issues related to the STAR reporting system that have adversely affected my sales performance and compensation. This report aims to highlight these discrepancies, provide a detailed analysis of the impact, and offer recommendations for resolution.

Detailed Analysis

Transfer Negative Posting Error

Instances where negative revenue of the "MOVEFROM" address was posted to the STAR report against the salesperson, without corresponding positive revenue from the "MOVETO" address.

Incorrect and Underreported Sale Revenue

Sales recorded in STAR at significantly lower amounts compared to ICE orders, customer biller, and ICOMS.

Sales Not Included in Monthly Revenue

Sales made and billed correctly but not reflected in the month's sales revenue, impacting my efforts significantly. For instance, in May alone, 46 sales worth $6,227.02 were not included in the STAR report.

Data Discrepancies

Google Lighthouse Audit

This is a popular, open-source tool used for auditing web page performance, SEO, accessibility, and more. Google Lighthouse generates reports that are commonly used by developers and businesses to improve website quality. It’s highly recognized in the industry and integrates well with tools like Google Sheets for data tracking.

Moz Site Audit

Moz is a well-known SEO tool that provides a comprehensive audit of a website's SEO performance. Moz’s audit reports cover technical SEO issues like broken links, missing metadata, and crawl errors, making it widely used by companies seeking to optimize search rankings.

Ahrefs Site Audit

Ahrefs is another highly recognized tool for SEO auditing. It provides detailed insights into backlink profiles, site health, keyword analysis, and competitor comparisons. Ahrefs is widely adopted by large organizations looking to monitor online performance and competitor benchmarking

Schema Validation with SQLLint or Schema Validator

This method involves running the SQL table through a schema validation tool like SQLLint or an online schema validator. It checks for compliance with SQL syntax, table structure accuracy, and adherence to best practices. You can extract the table data and submit it through these tools, which often accept uploads in HTML or CSV format

Basic Data Type and Consistency Check via Google Sheets or Excel

Convert the SQL table to CSV format and import it into Google Sheets or Excel. Use built-in data validation features to ensure consistency in data types (e.g., integer, date, text). You can create conditional formatting rules or scripts to highlight any anomalies like missing values, incorrect data formats, or mismatched column

HTML Table Validator (W3C Validator or TableCheck)

SQL Query Test on a Local Database Environment

Before submitting the table for further auditing, run it through a local database (e.g., MySQL, PostgreSQL) using a basic SQL query that tests table integrity. For example, perform simple SELECT queries to check for null values in required fields, validate foreign key constraints, and confirm that primary keys are unique and correctly indexed.

CSV Lint

is a web-based tool for validating CSV data against a defined schema. It checks for consistency in data types, missing values, and other structural issues in CSV files.

https://csvlint.io/

Schema Validation with SQLLint or Schema Validator

This method involves running the SQL table through a schema validation tool like SQLLint or an online schema validator. It checks for compliance with SQL syntax, table structure accuracy, and adherence to best practices. You can extract the table data and submit it through these tools, which often accept uploads in HTML or CSV format.

Datawrapper

Datawrapper can be used to upload your dataset (including CSV or Excel files) and provides data validation tools before creating charts or visualizations. It helps identify inconsistencies and errors in the data format.

https://www.datawrapper.de/

CSV Validator (Validator.nu)

Validator.nu offers a simple tool to validate CSV and other types of data formats, checking for missing fields, invalid entries, and general syntax errors.

https://validator.nu/

SQL Fiddle

SQL Fiddle allows you to submit SQL tables and test queries directly in the browser. It’s useful for ensuring that your SQL queries and tables are correctly structured and can run without errors in real environments.

http://sqlfiddle.com/

Online XML Validator (for HTML Tables)

If your SQL table is presented in HTML, you can use the W3C Markup Validation Service to check the validity of the HTML structure. It highlights errors in table tags and overall markup.

https://validator.w3.org/.

Data Discrepancies

STAR Report Discrepancy (Summary)

Order Discrepancy: STAR reported 178 orders, while you documented 197. This represents a 9.6% difference (19 orders / 197 orders).

Negative Revenue Omission: STAR's total revenue excludes documented negative revenue of -$1,931.40 from 23 orders.

Missing Accounts: There are potentially 52 accounts with missing revenue information in STAR, totaling an estimated $6,227.02.

Underreported Revenue: Combining negative revenue and missing accounts, the potential underreporting in STAR is $8,158.42 (-$1,931.40 + $6,227.02).

Conversion Rate Discrepancy: If all 744 calls were yours, STAR's reported orders suggest a 23.9% conversion rate (178 orders / 744 calls). Including your documented orders raises the conversion rate to 26.5% (197 orders / 744 calls).

Missing Revenue Impact: The potential underreporting of $8,158.42 represents a 44.7% difference from the reported STAR revenue of $18,272.99.

Agent Performance Inaccuracy: The discrepancy could lead to an underestimation of your individual performance based solely on STAR data.

Commission Impact: If commissions are based on reported revenue, the underreporting could negatively affect your compensation.

Data Quality Concerns: The discrepancies raise concerns about the accuracy and completeness of STAR data for reporting purposes.

Missed Opportunities: Missing revenue data could hinder identifying areas for improvement and optimizing sales strategies.

Network Issues

Timeline of Events

Case Management and Follow-Up

The following list contains current open requests in the HR system, demonstrating the ongoing issues that have yet to be resolved:

• General Inquiry case for Thomas Coates - 00812404 (HRC1147319), Ready, Created 36 days ago
• General Inquiry case for Thomas Coates (HRC1149551), Ready, Created 25 days ago
• Performance: Compensation for Thomas Coates - 00812404 (HRC1149024), Ready, Created 29 days ago
• Leave Of Absence case for Thomas Coates - 00812404 (HRC1152131), Work in Progress, Updated 23 hours ago
• General Inquiry case for Thomas Coates (HRC1148762), Ready, Created 11 days ago
• General Inquiry case for Thomas Coates (HRC1148753), Ready, Created 30 days ago

Conclusion

In summary, the issues with the STAR reporting system, coupled with ongoing network problems and the lack of timely responses from HR, have significantly impacted my performance and compensation. It is crucial that these matters are addressed promptly to ensure accurate reporting, fair compensation, and a supportive work environment.

Appendices

Supporting data, documents, charts, system logs and graphs

Appendix A: Supporting Data

• Time-Stamped Communication Logs: Submitted emails and chat logs with precise timestamps showing the sequence of key interactions and decisions.

•  Documented Approvals: Submitted workflow records from systems like Workday, showing approvals and the progression of key requests.

•  Attachment and File Metadata: Submitted attached files and documents, along with metadata on when they were uploaded and by whom, to verify authenticity.

•  Employee and Resource Data: Submitted tracking data showing employee movements, role changes, and resource allocations over time to support management claims.

•  Audit Trails and Change Logs: Submitted audit trails showing exactly when and by whom key changes were made to HR and case records, supporting transparency.

•  User Activity Logs: Submitted user action logs from HR and resource systems showing who accessed, updated, or logged into key records and when.

Appendices

Supporting documents, charts, graphs, and references can be found in the attached appendices.

Appendix B: Supporting Documents

• Document 1: Detailed STAR Report April 2024
• Document 2: Detailed STAR Report May 2024
• Document 3: Correspondence with HR
• Document 4: Physician Accommodation Request Form

Appendix C: Charts and Graphs

Appendix C: References

• Enforcement Guidance on Reasonable Accommodation and Undue Hardship under the ADA
• Wage and Hour Division (WHD)
• Office of Federal Contract Compliance Programs (OFCCP)
• Equal Employment Opportunity Commission (EEOC)
• Americans with Disabilities Act (ADA)
• Virginia Employment Commission