It’s no secret that a move to sustainability is at the top of the to-do list across all industries. From ESG and net-zero initiatives to a low carbon economy shift, it is evident that the integration of sustainable practices into everyday business practices is now a necessity.
This period of great transition is fueled by great innovation and creativity, but the starting flags have been waved, the race has begun, and pressure is on. Taking steps towards sustainability is as much a subject of vision and commitment to that vision as it is one of change management and implementation.
In fact, these things should be intricately intertwined. Many organizations struggle to merge these two things, leaving a grey area of disconnection. The vision can be there, usually embodied by committed teams of experts, but the capacity to translate this vision into company-wide actions and revisit all underlying processes remains the real frontier. This execution can be significantly accelerated with a data-driven approach — the data is the real ignitor behind innovation.
The Same Race for All Industries? Different Value Chains, Shared Challenges
With the push to ESG in investments which has happened in the past two decades, the level of awareness tends to be more established in financial institutions. Many are past the questioning stage and are on track, with strong commitments being taken. Now comes the time to turn their stance into systematic changes which, by nature, is no simple task. Namely, this stems from a lack of methodologies and norms to benchmark against.
We could claim that the challenge to get going at full speed towards sustainability initiatives is even more complex for other verticals such as retail, manufacturing, telco, and others. As in FSI, the level of awareness is there. But these organizations are by nature somewhat less data native, and their underlying processes are often even more varied and decentralized in end-to-end ownership, notably when it comes to supply chain management, so the task ahead is significant. And here again, the absence of mature, harmonized norms and data structures can make things arduous.
Does it mean organizations should wait for these norms to emerge? There isn’t time for that. Some, such as myself, would claim that we simply can’t afford it. Being more cynical, let’s also say that their market valuations really can’t afford it. Nor can their profitability as a growing number of customers move to a seamless integration of sustainability factors in their consumption decisions.
Racing Toward a Moving Target: What We Can Learn From Banks
Let’s take a “net zero emissions” commitment in the context of a bank. The ambition is noble and fully aligned with global warming reduction needs. However, for this bank to make progress, it is now confronted with significant challenges:
- Defining its baseline
- Building its policy and action plan
- Monitoring its implementation
As mentioned, there is no universal market standard that establishes how a bank is supposed to calculate its current emissions and what the underlying data points should be. And even if this norm existed, its actual implementation throughout all banking processes — loans, cards, investment, stress testing, and more — will require an unprecedented data blending and modeling effort.
The consequence of this absence of norm is that players are confronted with a plethora of initiatives and data providers on the road ahead. While these initiatives and providers all offer added value, it is important to note that they all slightly differ, sometimes overlap, and, most importantly, are often only partial in their approach. Meaning, a provider fully focused on CO2 emissions will be instrumental on net-zero topics but less on other critical dimensions such as waste and biodiversity management.
As banks and other financial institutions assess their data partners and build their methodologies, they will have to tackle multiple questions, including:
- Will this data provider have the capacity to cover all issuers? All counterparts?
- If I don’t have data, should I take a proxy? Wait, which proxy?
- How universal is this data provider? Can it cover processes as varied as investment and trade finance?
A bank will have to make tough methodological choices and, beyond this, build its own approach so as to realistically embrace the complexity of its operations. The same challenge exists for players aiming to improve their ESG initiatives.
Ultimately, each bank will need to put different types of data (mainstream and sustainability-focused) in the hands of a broad variety of process owners, supported by sustainability experts, to build these much-needed data-driven approaches. This makes data-driven approaches the key accelerators for companies aiming to tackle rapidly evolving sustainability targets.
Shifting Into Gear
To be a frontrunner in the race for a better future, action must be taken today. It is time for all organizations across all industries to recognize that if they want to emerge successfully from this unprecedented era of transformation, they need to embrace it, not only by stating a vision but by shifting into gear and organizing a systemized process that will have real impact.
There is no one magic solution, but what we can see is that having the capacity to leverage data and to develop company-wide agile analytics initiatives will be instrumental for the times ahead. All organizations will have to review their present processes, inject new sustainability-specific data into them, and embed these new objectives into their decision-making.
Internal Mechanisms Driving the Transformation
To properly power new sustainability objectives, an organization must prepare and fine-tune its internal mechanisms, evolving each facet of their business processes in a collective manner. For example:
- Procurement teams have to position their purchasing decisions with sustainability at the forefront— which comes from a variety of signals: mainstream, alternative data, etc. — so as to measure the impact of their purchasing decisions on their company exposure.
- Supply chain managers have to develop ESG-adjusted cost assessments of their supply chains.
- Logistics experts have to revisit their approaches based on switching to renewables and resulting constraints.
- Marketing experts have to embed sustainability dimensions in their approach to customers to preserve their brand positioning.
- CSR teams will have to be in a position to monitor and orchestrate these efforts, building analytics watchtowers to monitor progress, gaps, and successes.
A requirement to orchestrate these changes: An organization must make sure to have the right technology enabler and empower teams throughout this journey. Teams should focus on finding balance between building a common framework and supporting the development of highly tailored models and use cases which is where Dataiku can step in. Dataiku can act as a powerful catalyst by putting data and agile analytics power in the hands of all these teams, enabling them to turn vision into action through a data-driven approach.
Pit Stops & Quick Reaction
With the capacity to ingest all types of data — internal, external, structured, alternative, etc. — and to model these into proper analytics or develop tailored machine learning models, Dataiku can support a step acceleration in establishing these baselines, in quickly modeling impacts of decisions, and fostering capitalization on referential analytics. With market changes and the emergence of new standards, organizations need to have the ability to take a pit stop, evaluate, and react efficiently. This is of the utmost importance for success.
While this may not be a “boom, problem-solved” situation, this empowerment of teams through agile analytics in a governed environment plays a key role in embracing and successfully tackling the sustainability challenge.