Twin Transformation: Why digitalization and sustainability only work together

Twin Transformation (also known as Twin Transition) refers to the simultaneous and integrated transformation of digitalization and sustainability. The term now appears in almost every strategy and ESG discussion. And with good reason, because companies are faced with the task of combining complex requirements (stakeholders, markets, regulation) with operational feasibility. This is precisely where it becomes clear that “green” without “digital” quickly ends up in a vacuum of intent, and ‘digital’ without “green” increasingly misses the strategic target.

What does twin transformation mean and what does it not mean?

In practice, twin transformation does not describe a parallel “double project,” but rather a common goal. Digital capabilities – such as data models, systems, automation, analytics, or AI – are specifically developed to contribute measurably to sustainability performance. At the same time, sustainability goals set the strategic direction for digitalization decisions.

The distinction is crucial:

• Twin transformation does not mean that an ESG team and a digital team work independently of each other.
• Rather, twin transformation refers to an integrated operating model in which data flows, responsibilities, controls, and management logic interact across departments – from finance and sustainability to IT, purchasing, and operations.

Research and policy debate also underscore this approach. They show that digital technologies enable significant synergies for sustainability goals, but at the same time can also entail trade-offs, for example through the increasing energy requirements of digital infrastructures. This is precisely why integrated control is needed instead of parallel structures.

An ESG study by Sustainable Services also shows that this view is no longer just theoretical: more than 80% of the companies surveyed in the DACH region rate twin transformation and ESG-related digitalization as important to very important. The integrated consideration of digitalization and sustainability has thus clearly become a strategic issue in corporate practice, regardless of industry or company size.

Why the topic is so hot right now

There are solid reasons why twin transformation is currently being discussed everywhere. Several developments are overlapping and increasing the pressure on companies to think about digitalization and sustainability together.

Reporting and verification pressure meets data reality

Many companies only realize how fragmented their data landscape is in the ESG context, especially when it comes to value chain and Scope 3 issues. A Bain survey (cited in the Wall Street Journal) shows that only 24% of companies believe they have the technology necessary to meet upcoming ESG reporting requirements; at the same time, over 88% say they need better technology.

This discrepancy between regulatory requirements and technological reality is also confirmed by an ESG study by Sustainable Services: More than 80% of the companies surveyed rate ESG data collection and twin transformation as important to very important, but often do not yet consider themselves sufficiently prepared to implement these requirements systematically and in an integrated manner.

Digitalization is becoming a lever for real emissions reduction (not just for reporting)

The World Economic Forum article summarizes research and practical examples as follows: If digital technologies are scaled up, they could enable up to 20% emissions reduction by 2050 (especially in energy-, material-, and mobility-intensive sectors). In the short term, emission reductions of 4–10% by 2030 are even described as achievable, provided that adoption and data availability increase. This shifts the focus from pure documentation to the question of how digital systems can be used specifically to control and reduce emissions.

AI further accelerates the discussion

AI is not automatically “green,” but it increases the speed and degree of automation in data collection, plausibility checks, and analysis, especially in reporting. The WEF describes AI as an enabler for greater transparency and more timely reporting, including earlier detection of deviations in supply chains. Especially in conjunction with structured data platforms, AI is thus reinforcing the trend toward not only reporting on sustainability retrospectively, but also monitoring it continuously and making it controllable.

Digitalization as an enabler of sustainability

Sustainability rarely fails because of the goal itself, but rather because of data, processes, and scaling. According to the ESG study by Sustainable Services, 77% of companies see high potential in digital technologies for ESG goals, but only around 30% currently use central platforms for the structured collection and control of ESG data. In practice, digitalization helps in four key areas:

1. Data availability and quality for reliable values

Many ESG metrics are still generated today through manual surveys, point solutions, and Excel. This leads to:

• Inconsistencies between locations/units
• High costs for data collection and cleansing
• Weak auditability (“Where does the number come from?”)

Studies and practical analyses show the enormous potential of structured data exchange processes: In a sustainability/cloud paper, McKinsey describes how a refined data exchange process can save up to 80% of the time typically spent on data collection, cleansing, and estimation, and how greater Scope 3 transparency can reveal emission levers on a relevant scale.

2. Automation and controls for auditable processes

As soon as ESG figures become relevant for auditing or reporting, the following are required:

• Versioning/history
• Roles & rights
• Approval workflows
• Audit trails and document logic

Digitalization is not a “nice to have” here, but rather the basis for making ESG routines repeatable, auditable, and scalable.

3. Control: from reporting to performance

The decisive leap in maturity occurs when ESG is not only documented but also controlled:

• Target values and action logic
• Scenarios and forecasts
• Deviation analyses (where, why, how big?)
• Linking actions to key performance indicators

This is precisely where the business case arises: Transparent data creates the basis for prioritizing actions where impact and economic efficiency come together.

4. Value chains: no Scope 3 maturity without digital cooperation

With Scope 3 in particular, the problem is rarely a “lack of will,” but rather a lack of connectivity to partner data. The WEF therefore emphasizes the importance of data networks and standardized exchange mechanisms to make emissions data shareable with suppliers and industry partners.

Sustainability as a strategic framework for digitalization

The second half of the twin transformation is often underestimated: Sustainability not only changes which digital projects are prioritized, but also how success is measured. While digital transformation has long been primarily focused on efficiency metrics such as cost, speed, or customer experience, the twin transformation expands this logic to include an impact perspective.

The focus is increasingly on questions such as:

• Which digital decisions reduce emissions permanently?
• Which data architecture creates transparency along complex supply chains?
• And which forms of automation help to measurably reduce resource consumption – such as materials, energy, or waste?

Sustainability thus becomes not an additional evaluation criterion, but a strategic framework for portfolio decisions in digitalization.

At the same time, this approach requires a conscious handling of conflicting goals. EU research by the Joint Research Centre (JRC) explicitly points out that digital technologies can have enabling effects such as efficiency gains, optimization, and transparency, but also negative effects, such as increased energy and resource consumption or rebound effects. Integrated management that jointly controls digital and sustainability-related goals, systematically leverages synergies, and limits risks at an early stage is therefore crucial.

Twin transformation in practice: from buzzword to operating model

The difference between “we talk about it” and “we can do it” in twin transformation usually lies not in the objectives, but in the operational anchoring. In practice, three building blocks have proven to be crucial for bringing digitalization and sustainability together on a lasting basis.

1. A common data foundation (single source of truth)

• Uniform data models and clear definitions across all organizational units
• Clear data responsibilities (data owners)
• Integrations into source systems (ERP, HR, purchasing, energy management, etc.)

2. End-to-end processes for ESG – from collection to reporting

• Standardized collection processes
• Plausibility checks and data validation
• Defined approval and control logic
• Clearly structured reporting output formats
• Continuous improvement (lessons learned per reporting cycle)

3. Organization and skills

Twin transformation is not just a question of systems or processes, but also a task of change and competence. EU analyses on the “work in the twin transition” perspective show that the impact of digital technologies depends heavily on how they are embedded in the organization. Qualification, clear role models, and a suitable organizational design are crucial in determining whether digital sustainability solutions are actually used and further developed.

What does this mean specifically for Envoria and the customer perspective?

For Envoria, twin transformation is primarily a very practical question: How can ESG be turned into a reliable, scalable, and controllable process – instead of an annual feat of strength? This is precisely where it becomes clear that digitalization and sustainability cannot be considered separately.

Software becomes an enabler of twin transformation when it supports companies in systematically integrating ESG into existing control logic, especially at the interface between sustainability, finance, and operational areas. The goal is not to establish another reporting tool, but to create a robust basis for management decisions.

In practice, this means that with Envoria, companies can:

• consolidate ESG, risk, financial, and corporate data in a structured manner instead of managing it in separate systems or Excel landscapes
• map integrated data flows, including standardized interfaces to upstream systems, instead of manual copy-paste processes
• build verifiable, traceable documentation that ensures transparency, historization, and clear responsibilities
• make the transition from pure reporting to active control, for example through dashboards, workflows, and a clear logic of measures

In this way, the Envoria platform supports the very core of twin transformation: not only collecting data, but also making it usable. For the first time, reliable, consistent information enables companies to prioritize sustainability measures in a targeted manner, make progress measurable, and combine regulatory requirements with corporate management. The goal is therefore no longer reporting, but better management, because sustainability only becomes effective when it is operationally anchored, digitally supported, and strategically controlled.

Final summary of Twin Transformation

Twin Transformation is more than just a buzzword. It describes a new corporate reality: sustainability is becoming data-, process-, and control-intensive. And digitalization is taking on a new objective, namely measurable impact. Companies are thus not faced with two separate transformation tasks, but with an integrated management issue.

Studies paint a clear picture: on the one hand, there is a significant gap in technological and organizational readiness, with only around a quarter of companies considering themselves sufficiently prepared for upcoming ESG requirements. On the other hand, the potential of digital levers is enormous, from more efficient reporting to substantial emissions reductions along the entire value chain.

The decisive factor will therefore not be whether companies engage in twin transformation, but how consistently they combine digitalization and sustainability. Those who continue to view the two issues in isolation risk additional costs, inconsistent data, and missed control potential. Those who think in an integrated way create the basis for robust decisions, regulatory certainty, and sustainable competitiveness.