The Importance of Data Management Part 2

• Start by analyzing existing energy data before purchasing new technology.
• Collecting and analyzing energy data has a cost but offers strong ROI through energy savings.
• Effective energy data management requires a multi-disciplinary team across the organization.
• Collected data must be actively used to drive accountability and continuous savings.
• Energy data management forms a feedback loop turning data into actionable insights.
• Managing energy data is crucial not only for energy savings but also for carbon reduction goals.
• A blended internal and external approach to data management is most effective.

• Meters Alone Do Not Save Energy: The Power Lies in Data Analysis
  Energy meters provide valuable raw data but do not inherently reduce consumption. Organizations must analyze the data and implement changes based on insights.
• Budgeting for Data Management Should Reflect Energy Spend and Potential Savings
  By understanding total energy spend, organizations can set a realistic budget for data management. For example, spending around 1% of energy costs to achieve 5% savings provides a strong payback and justifies investment in data collection and analysis.
• Multi-Disciplinary Involvement Ensures Comprehensive Energy Data Use
  Involving departments like accounting, operations, maintenance, and frontline employees fosters ownership and diverse perspectives.
• Data Management Enables a Continuous Improvement Cycle
  The transformation from raw data to actionable knowledge initiates a cycle where modifications in energy use generate new data, which is then analyzed to optimize further, enabling sustained efficiency gains over time.
• Visibility and Accountability Drive Behavior Change
  Simply making people aware that energy consumption is being monitored often results in immediate behavior adjustments and waste reduction, leading to an initial savings uplift that extends over the long term.
• Energy Data Is Foundational to Carbon Reduction and Sustainability Leadership
  Successful sustainability leaders use energy and carbon data as a “data engine” powering strategic decisions.
• Balanced Internal and External Efforts Maximize Effectiveness
  Fully outsourcing data collection risks losing internal expertise, while doing everything in-house may overwhelm resources.

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