Monitoring frameworks include high level indicators, which offer a “cockpit” for monitoring the overall progress of roadmap implementation, and a set of more detailed indicators.
High level indicators (the “cockpit”)
What: critical data for decision-making and showing overall progress on roadmap commitments. If these indicators are not met, it means that the implementation of the organisation’s roadmap is going off track. High level indicators typically include impact, outcome and output indicators.
Target audience: senior leadership, sustainability managers.
Impact indicators measure progress against the overall climate roadmap commitment, that is halving GHG emissions by 2030 (measuring volumes of emissions avoided).
Other high-level indicators can provide important information on the overall progress of the organisation in terms of emissions reduction, including monitoring emissions per dollar amount (intensity). Such indicators are a complement but do not replace the main impact indicator that consists in monitoring emissions reduction in absolute terms.
Progress indicators
For each category of solution (procurement, air freight, business travel, etc.), a set of input, activity, output, outcomes and impact indicators needs to be defined.
- Use a mix of qualitative and quantitative indicators.
- Focus on priority projects to be initiated on the first couple of years of the roadmap implementation.
- Combine the measurement of progress on key action/activities planned, with process, policies, and data availability/generation tracking tools.
Data collection, availability and quality are key for the capacity of an organisation to develop its climate roadmap and for the monitoring framework. However, organisations are often faced with initial challenges which will be addressed over time:
- Improve the physical data collection process, starting with initial mapping of available data.
- Contribute to develop emissions factors for key items, for instance identifying proxies and/or investing into research projects to estimate life cycle analysis (LCAs).
- Be selective in the number and complexity of additional requested indicators, using existing data in priority; make sure field is not overburdened with data collection.