Short answer

When designing energy-efficient solutions for data centers, prioritize clear, demonstrable ROI and reliability, and consider how to navigate internal organizational structures and information silos that might prevent adoption.

Field: Innovation & Design
Source: AgEcon Search (University of Minnesota, USA) (2017)
Method: Qualitative research using focus groups and interviews, followed by content analysis.
Evidence: Moderate effect

Internal organizational structures and a lack of clear, reliable data on new technology performance are significant barriers to adopting energy-efficient solutions in data centers. This innovation & design research insight is drawn from a 2017 study published in AgEcon Search (University of Minnesota, USA). Using Qualitative research using focus groups and interviews, followed by content analysis., researchers explored how this design variable affects real-world outcomes. The key design takeaway: When designing energy-efficient solutions for data centers, prioritize clear, demonstrable ROI and reliability, and consider how to navigate internal organizational structures and information silos that might prevent adoption.

Study

Innovation & DesignHigh ImpactModerate effect

Split Incentives and Information Gaps Hinder Data Center Energy Efficiency Investments

Internal organizational structures and a lack of clear, reliable data on new technology performance are significant barriers to adopting energy-efficient solutions in data centers.

AgEcon Search (University of Minnesota, USA) · 2017

Key Findings

01Split incentives between different departments or between colocation providers and tenants impede investment.
02Uncertainty and imperfect information about the performance of new energy-saving technologies are significant deterrents.
03Concerns about data center uptime and reliability often outweigh potential energy savings.

Application

Design takeaway

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.

Project actions

01When researching a product, look beyond just its technical specs to understand who benefits from its use and who pays for it.
02Consider how you will prove your design's effectiveness to potential users, especially if they are risk-averse.

Method & Evidence

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

MethodQualitative research using focus groups and interviews, followed by content analysis.

ProcedureResearchers 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.

ContextData center industry, focusing on investment decisions for energy efficiency.

Variables

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

DV["Investment in energy-efficiency technologies"]

CV["Data center uptime requirements","Perceived cost savings"]

Strengths & Limitations

Strengths

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

Limitations

Qualitative data can be subjective. The findings might not apply to smaller data centers or those with different management structures.

Reliability & validity

Reliability could be improved through triangulation of data sources (e.g., comparing interview data with actual investment records). Validity is strengthened by using multiple focus groups and interviews to capture diverse perspectives.

Think critically

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

Design Principles

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

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.

What This Means for Your Design

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.

How to use in your project

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

Add to My Project

Quick Cite

Paragraph starter

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.

Source

AgEcon Search (University of Minnesota, USA)

Data Center Energy Efficiency Investments: Qualitative Evidence from Focus Groups and Interviews

journal · 2017

View source

Questions About This Research

What does the research say about split incentives and information gaps hinder data center energy efficiency investments?: When designing energy-efficient solutions for data centers, prioritize clear, demonstrable ROI and reliability, and consider how to navigate internal organizational structures and information silos that might prevent adoption. Evidence: AgEcon Search (University of Minnesota, USA) (2017).
Why does "Split Incentives and Information Gaps Hinder Data Center Energy Efficiency Investments" matter for design?: 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.
How can designers apply this research?: When designing energy-efficient solutions for data centers, prioritize clear, demonstrable ROI and reliability, and consider how to navigate internal organizational structures and information silos that might prevent adoption.
What were the main 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.
What research method was used?: Qualitative research using focus groups and interviews, followed by content analysis..
How strong is the evidence?: Evidence strength is rated Moderate effect, based on a 2017 journal from AgEcon Search (University of Minnesota, USA).
What should I do differently in my next project?: 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.
What are the 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.