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Sustainability is data heavy. To succeed in the field, leaders must manage a wide array of data points for external reporting and internal business use. Creating data solutions ad hoc to address the latest critical needs can introduce unnecessary risks. To avoid them, enterprises need a strategic approach. Here we present our Sustainability Data Leverage Matrix, a tool we developed to help clients form strategies to maximize their existing sustainability data and systematically identify data gaps to be addressed in due time.
The Big Picture: Enterprise Sustainability Increasingly Relies on Data
In today’s world, enterprises face sustainability challenges and opportunities arising on multiple fronts, from new and evolving regulations through shifting consumer expectations to investor pressure to go green. While there are many aspects of sustainability and many approaches to advancing it, all successful initiatives share one thing in common — they require data.
For example, to prepare sustainability reports, a multinational enterprise might need to track hundreds of data points across multiple standards and frameworks. To qualify for green financing, the enterprise will need relevant sustainability data. Green products? Consumers expect claims to be backed up by robust sustainability data. The list goes on; data is at the heart of any sustainable activity.
The Imperative: Efficiently Fulfilling Data Needs Requires a Data Strategy
To achieve success, sustainability leaders must ensure they have the right data at the right time and right where it is needed — with everything done within budget. The key to doing so is a data strategy that goes hand in hand with the enterprise’s overall sustainability strategy.
Without such a strategy, enterprises inevitably resort to scrambling for ad hoc solutions to satisfy immediate data needs. Based on our experience, this approach is not only inefficient but also risky, often resulting in common setbacks like:
- Embarrassing adjustments to public net-zero commitments. If commitments are made without a detailed carbon inventory, they must be backtracked when the true scale of emissions is eventually uncovered.
- Missed opportunities for decarbonization or capturing new green markets. Without the right data, products cannot be designed for sustainability and green claims cannot be backed up.
- Cost overruns when deploying last-minute solutions to satisfy immediate needs without time for proper deliberation. Such scenarios often lead to data being siloed and unutilized for business analytics.
The Strategy Development Tool: Our Sustainability Data Leverage Matrix
When it comes to forming a data strategy for sustainability, we have found that the main challenge is linking thousands of sustainability data points to hundreds of use cases. Identifying what is needed where involves navigating a maze of connections. Our Sustainability Data Leverage Matrix was born to tackle this problem by mapping data types to use cases at just the right granularity.
This matrix makes it easy to identify sustainability data needs, synergies, and gaps. Note that the template version of the matrix presented here is simplified — categories and dimensions can be further tailored according to the specific needs of an enterprise. The matrix reveals a number of important insights, including that:
- Social and governance data are needed as much as environmental data for many use cases. The environmental aspects of Environmental, Social, and Governance (ESG) initiatives are often prioritized, but social and governance data should be gathered in tandem to avoid duplicated efforts and solutions.
- Environmental data is often needed at the product level. Such data — for example, on electricity consumption or water usage — is commonly gathered at the site level based on invoices and used at the company level for regulatory compliance. This data should, however, be disaggregated and correctly attributed to production lines to utilize its full potential.
The Tool’s Design: Drilling Down on Sustainability Use Cases and Data Types
The purpose of our Sustainability Data Leverage Matrix is to help enterprises answer two broad questions: where data is needed and what that data is. The matrix helps by breaking down these broad questions into smaller, more manageable ones, i.e., by defining the spectrum of both sustainability data use cases as well as data types.
Use cases
All enterprises have unique use cases for sustainability data, but their needs will typically fall into three broad functional categories encountered across all industries: sustainability strategy, regulatory compliance, and communications with external stakeholders. Examples of the most common use cases falling into these categories are outlined in the following table.
Data types
Given the vast amount of types of data used in the field of sustainability, it is essential to efficiently highlight and analyze key differences between large groups of data points. Therefore, we recommend grouping sustainability data by three broad dimensions that will commonly differentiate most data points: entity, value chain, and ESG. See examples of data types falling within each dimension below. Note that dimensions may be modified or introduced depending on specific enterprise needs. For example, in some instances, we have observed that it is helpful to add a “Frequency” dimension to address how often data needs to be updated.
The Tool in Action: Powering the Matrix Like an Electric Grid Engineer
Once our Sustainability Data Leverage Matrix has shown what data is needed and where, the next step is to take action and meet these needs.
We recommend thinking like an electric grid engineer looking at a map of homes while planning a grid. Electric grids consist of a few large power plants and a far greater number of households consuming electricity; the point is to connect producers and consumers of electricity to ensure it is delivered where needed.
Treat our matrix as a map that helps determine where specific types of data originate and to which sustainability use case they are connected currently or should be connected soon. Data strategy is all about building the “data grid” of solutions necessary to support all these connections.
Note that a dedicated data solution to address a single sustainability use case is like an off-grid, solar-powered house that cannot draw power from the grid during peak consumption or supply surplus power to it. Building such a solution is clearly a poor choice when there are multiple sustainability objectives to address.
The Way Forward: Sustainable Success through Better Data
With sustainability only growing in importance and scope, so must organizations’ maturity when it comes to sustainability data management. A sound sustainability data strategy — like one our matrix was designed to enable — will help them not only minimize risks but also seize opportunities that may not have otherwise been visible.
In other words, do not let requests for sustainability data put entire departments into crisis mode! We look forward to helping you avoid this unpleasant scenario and achieve more with better leveraged data.
