How can you adapt your sustainability data collection and analysis to new market conditions?

Assessing your data needs in adapting sustainability data collection to new market conditions involves identifying relevant metrics aligned with evolving industry trends. Understand the specific information required to gauge environmental, social, and governance (ESG) performance in the changing landscape. This proactive approach ensures that your data collection remains strategic, supporting informed decision-making and effective sustainability initiatives.

'Sustainability' is an overarching subject. The sustainability data is the same data that you collect, interrogate and use for managing energy, pollution prevention, procurement, travel etc ... Data management covers all of these aspects and data management is a core function of any organisation.

Assessing your sustainability data needs should ultimately results to a good understanding in your sustainability reporting requirements as the market switched to a voluntary reporting to a mandatory reporting (SEC, CSRD among other) and sustainability performance type of data (designing sustainable product, sustainable and resilience supply chain, understanding customer sustainable habits and so forth)

Your method should match the expected roi due to automation and at the same these new automation will bring roi beyond sustainability business use cases. Moreover sustainability data challenge go beyond data method and usually also affect your business processes this will require broader transformation

In choosing data methods for adapting sustainability data collection to new market conditions, prioritize methods that align with emerging ESG priorities and market expectations. Opt for data collection approaches that are agile, allowing quick adjustments to evolving sustainability standards. Utilize technology-driven solutions and industry benchmarks to enhance the accuracy and relevance of your sustainability data in response to dynamic market conditions.

Listing down KPI with respect to the targeted sustainability goals is a primary step and the data set then collected should be aligned to those KPI's. These indicators not only help us in giving a direction but also helps us in visualizing our analysis and and deciding further course of measurable actions. The team working on data collection should be trained on sustainability disclosures and the related tools.

To engage data stakeholders in adapting sustainability data collection to new market conditions, establish clear communication channels to convey the importance of aligning data practices with emerging trends. Collaborate with key stakeholders to identify their specific data needs and preferences, ensuring a tailored approach to data collection. Foster a culture of continuous feedback and improvement, encouraging stakeholders to actively participate in refining sustainability data practices in response to evolving market dynamics.

Communicate the necessity of adapting data collection and analysis strategies to stakeholders. Involve key internal and external stakeholders in discussions regarding data requirements and seek their input in refining the approach. Collaborating with stakeholders ensures the data collected is comprehensive and addresses varied perspectives.

Explore innovative data solutions to cater to the modified market landscape. This might involve investing in predictive analytics, artificial intelligence, or machine learning tools to forecast market trends more accurately. Embrace newer data analysis techniques that offer agility and adaptability in responding to rapid market changes.

I usually look at ‘sustainability data sets’ in the following categories: - Designed data (for administrative purposes) - Historical data (to understand the context and issues at hand) - Synthesised data (be it projected, predicted or foreseeable computation based on proxies and other factual attributes for short, mid or long terms perspectives) - “Almost instantaneous” IoT, near real-time on the fly collected and calculated telemetry data! *** *** this is the area that I am currently learning and studying, an area I am very passionate about at present moment, especially in flood and land slides monitoring, mitigation, and recovery strategies

It is essential in today's time for strategy to account for the high level of uncertainty associated with upcoming mid to long-term fundamental shifts such as the push for decarbonization, renewable energy, economic transformations, geopolitical crises, and supply chain disruptions based on the collected data.