To effectively manage sustainability risks, decision makers require trust-worthy information about current performance and potential impacts of interventions.
A data-driven approach provides timely and robust insights to guide sustainability decisions.
Sustainability is a broad, multi-dimensional and complex concept. It is comprised of numerous sub-topics, each of which needs to be understood in order for sustainability opportunities to be identified, decisions taken and performance improved.
This multi-dimensionality of sustainability present challenges to both internal decision-makers and external stakeholders alike, and requires solutions that can provide a clear and accurate view of performance across each dimension and sub-topic.
Sustainability data are powerful assets for enabling both internal and external stakeholders to better understand an organisation’s sustainability performance and make informed decisions about that organisation.
Given the diverse number of sub-topics under the ‘sustainability’ umbrella, sustainability data encompass a wide range of data and data sources that can illuminate the current or/and historic sustainability performance of an organisation, an asset, a facility or supply chain.
Sustainability data, for example, data about energy usage, corporate carbon emissions, raw material life cycle emissions, staff training, employee health and safety, board composition, etc.
To fully understand sustainability performance, the organisations must not only capture and collect the right data, but must ensure that the data is of good quality.
By ‘good quality’, we mean that the data must be complete, accurate, consistent, valid, unique and made available in a timely manner.
Decisions made on the basis of data that do not meet adequate quality standards are likely to result in same types of sub-optimal and ill-informed decisions that would have been made with no data at all!
The need for high-quality sustainability data cannot be overstated.
However, even high-quality data would be no value if left in their raw state. For high-quality data into valuable information, insights are not extracted from them through analyses.
To enable data-driven sustainability management, a wide range of analyses are likely to be required at different stages of an organisation’s sustainability journey.
These include Descriptive analyses to understand current trends and patterns from sustainability data; Diagnostic analyses to investigate and assess causal relationships between actions and sustainability outcomes; Predictive analytics to assess what the future might hold for sustainability performance under various scenarios; and Prescriptive analytics for formulating and appraising options for realising sustainability opportunities.
It is the combination of high-quality sustainability data and robust analyses that together produce valuable and high-quality sustainability information.
Such high-quality data, in turn, enable internal stakeholders to make better and more informed decisions for sustainability, and provide external stakeholders with credible information about the organisation’s sustainability performance.
At FuturoFirma, we are as much data experts as we are sustainability experts.
We can help you develop and enhance your data processes and approaches for sustainability. This includes helping you develop and embed robust data collection systems, set-up data management and data governance solutions for sustainability, and apply analytical techniques to derive meaningful insights from your data.