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Supplier quotes do not become comparable just because the totals use the same currency.
Before choosing the lowest price, I check five gaps:
Incoterm and freight boundary
Tax and duty assumptions
MOQ and price-break basis
Lead-time definition
Payment and warranty terms
If a field is missing, I mark it unknown instead of estimating it. That turns a price table into a decision record and gives each supplier a clear set of clarification questions.
I use this written-only method for 2-5 readable quotes. The comparison and negotiation service is available on my profile.
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Creatives on Contra have earned over $150M and we are just getting started
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Hidden costs are often not hidden in the quote. They are hidden in the boundary.
Before comparing supplier totals, mark these fields as stated or unknown:
freight scope and named Incoterm place;
duty, tax, brokerage, and local delivery;
tooling, packaging, inspection, and payment fees;
MOQ and price-break basis;
what event starts the promised lead time.
A lower visible total is not a lower decision cost when the missing fields are material. Ask for the boundary in writing before awarding the order.
Five written questions can remove more uncertainty than another discount request:
Which costs are excluded from the quoted total?
What exactly starts the stated lead time?
Is the Incoterm paired with a named place and current version?
Are tooling and packaging one-time or recurring charges?
How long are price and payment terms valid?
The goal is not to force a winner. It is to make the decision conditions visible before supplier award.
Superstore Sales & Profit Analysis
Developed a SQL-based sales and profit analysis project using MySQL to clean, validate, analyze, and extract meaningful business insights from the Superstore dataset.
The project involved data cleaning, duplicate detection, date conversion, KPI calculation, sales and profit analysis, product and customer analysis, regional performance analysis, shipping analysis, and discount impact analysis.
Advanced SQL techniques including CTEs, subqueries, JOINs, CASE statements, aggregate functions, and window functions such as RANK, DENSE_RANK, ROW_NUMBER, LAG, and LEAD were used to answer complex business questions and identify performance trends.
Tool: MySQL / MySQL Workbench
Skills: SQL, Data Cleaning, Data Analysis, KPI Analysis, Advanced SQL, Window Functions, CTEs, Joins, Business Insights
