Split Incentives and Information Gaps Hinder Data Center Energy Efficiency Investments

Why It Matters

Understanding these non-technical barriers is crucial for designers and engineers developing new energy-saving technologies. Solutions need to address not only technical feasibility but also the complex stakeholder relationships and information asymmetries within organizations to ensure successful adoption.

Key Finding

Data center managers face challenges investing in energy efficiency due to internal conflicts of interest (split incentives), a lack of trust or clear data on new technology effectiveness, and a prioritization of system uptime over energy savings.

Key Findings

• Split incentives between different departments or between colocation providers and tenants impede investment.
• Uncertainty and imperfect information about the performance of new energy-saving technologies are significant deterrents.
• Concerns about data center uptime and reliability often outweigh potential energy savings.

Research Evidence

Aim: What are the primary barriers preventing data center managers from investing in energy-efficiency technologies?

Method: Qualitative research using focus groups and interviews, followed by content analysis.

Procedure: Researchers conducted focus groups and interviews with data center managers to gather insights into their decision-making processes regarding energy-efficiency investments. The collected data was then analyzed using content analysis to identify recurring themes and barriers.

Context: Data center industry, focusing on investment decisions for energy efficiency.

Design Principle

Technology adoption is influenced by organizational and informational factors as much as by technical merit.

How to Apply

Before launching a new energy-efficient product for data centers, conduct stakeholder analysis to identify potential split incentives and develop robust, easily accessible performance data to address information uncertainty.

Limitations

The study is qualitative and relies on self-reported data from managers, which may be subject to bias. The findings may not be generalizable to all data center types or sizes.

Student Guide (IB Design Technology)

Simple Explanation: It's hard for data centers to invest in saving energy because different parts of the company might not benefit equally, and it's often unclear if new energy-saving gadgets actually work as well as advertised or if they might cause problems.

Why This Matters: This research highlights that even the best technical solutions can fail if they don't account for the human and organizational factors that influence decision-making.

Critical Thinking: How might a designer proactively address 'split incentives' within a client organization during the design process?

IA-Ready Paragraph: This study by Klemick et al. (2017) identified significant barriers to energy efficiency investments in data centers, including split incentives between organizational units and uncertainty regarding new technology performance. These findings underscore the importance of considering organizational dynamics and information asymmetry when designing and proposing new solutions.

Project Tips

• When researching a product, look beyond just its technical specs to understand who benefits from its use and who pays for it.
• Consider how you will prove your design's effectiveness to potential users, especially if they are risk-averse.

How to Use in IA

• Use this research to justify the need for user research that explores organizational barriers, not just user needs.
• Cite this study when discussing challenges in adopting new technologies in your design project.

Examiner Tips

• Demonstrate an understanding of the non-technical factors that influence design adoption.
• Show how your design process accounts for potential organizational barriers.

Independent Variable: ["Organizational structure (split incentives)","Information availability and quality (uncertainty/imperfect information)"]

Dependent Variable: ["Investment in energy-efficiency technologies"]

Controlled Variables: ["Data center uptime requirements","Perceived cost savings"]

Strengths

• Provides rich qualitative data on complex decision-making processes.
• Identifies specific, actionable barriers faced by industry professionals.

Critical Questions

• To what extent do these barriers represent market failures versus solvable organizational challenges?
• How do these barriers vary across different types and sizes of data centers?

Extended Essay Application

• Investigate how organizational structures and information flows impact the adoption of sustainable technologies in other industries.
• Develop frameworks for assessing and mitigating organizational barriers to innovation.

Source

Data Center Energy Efficiency Investments: Qualitative Evidence from Focus Groups and Interviews · AgEcon Search (University of Minnesota, USA) · 2017 · 10.22004/ag.econ.280941