Preparing for Negotiations with Regression Analysis
- ukrsedo
- Jan 8
- 3 min read
Updated: Jan 12

Introduction
In today's data-driven business environment, high-quality datasets are essential for practical analysis, enabling companies to optimize their expenses effectively.
This article explores the application of regression analysis by examining the relationship between UK electricity prices and AWS EC2 costs.
It underscores the significance of data quality and statistical insights in preparing for well-informed negotiations.
Data and Methodology
Dataset Overview
We utilized hypothetical data from 2018 to 2023, covering:
Electricity Prices: Monthly average prices in GBP/MWh.
AWS EC2 Costs: Hourly rates for virtual servers (USD/hour).
Regression Analysis
We conducted a linear regression analysis with electricity prices as the independent variable and AWS EC2 costs as the dependent variable.
Key Results
Model Equation: AWS Cost = 0.1236 - 0.0005 × Electricity_Price.
R² Value: 0.914 (91.4%) – indicating a strong correlation between the two variables.
Coefficient: -0.0005 – indicating that AWS costs decrease by $0.0005/hour for every 1 GBP/MWh increase in electricity prices.
P-Value: 0.00284 – statistically significant level.
Interpretation of Findings
Although we found a statistically significant relationship, the negative trend contradicts expectations that AWS costs should rise with higher electricity prices. Several factors may explain this paradox:
Efficiency Gains – AWS may offset rising energy costs through operational efficiencies and investments in renewable energy.
Global Pricing Strategies – AWS pricing reflects global markets, competition, and technological improvements rather than local electricity costs.
Scale Economies – Larger data centres achieve cost efficiencies that mitigate regional price fluctuations.
Negotiation Strategy
The regression analysis reveals that AWS EC2 costs exhibit a statistically significant yet counterintuitive negative relationship with UK electricity prices. While higher electricity costs were expected to drive AWS pricing upward, the analysis indicates a slight decline in AWS costs as electricity prices increase. This anomaly highlights the complexity of pricing strategies employed by cloud providers and the importance of integrating broader economic and operational insights into negotiations.
Data-Driven Insights: The substantial R² value (91.4%) reinforces the importance of leveraging high-quality datasets to understand cost drivers and validate assumptions during negotiations. Procurement teams should demand transparency regarding pricing structures and cost components from AWS or similar providers.
Operational Efficiencies: AWS's ability to offset rising energy prices through efficiency gains and renewable energy investments suggests an opportunity to negotiate based on long-term sustainability commitments and efficiency improvements.
Global Pricing Trends: Since AWS pricing reflects global rather than regional electricity costs, procurement teams must benchmark against international markets and consider multi-region deployment strategies to secure better rates.
Scale and Commitment Advantages: Cloud providers often offer volume discounts and preferential pricing based on usage commitments. Buyers should emphasize scalability requirements and future growth projections when negotiating favourable terms.
Scenario Planning: The findings highlight the need to model various pricing scenarios and conduct sensitivity analyses. This approach ensures preparedness for potential price fluctuations and strengthens the case for fixed-term contracts or price caps.
Better data means richer negotiation toolsets and well-informed decisions. This is pretty evident if you don't consider the dark data challenges and spaghetti bowl of integrations between corporate IT systems. Otherwise, it's easy.
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