Numbers are not reality

The ability to collect and utilize data has become essential in today’s world. Since the second half of the 20th century, we've witnessed accelerating societal changes as humanity entered the information or digital age. Phenomena like the global network, digitization, artificial intelligence, machine learning, and the Internet of Things have led to an exponential increase in data generation and processing. This ability to utilize data is now essential for driving efficiency, gaining knowledge, boosting competitiveness, managing risks more effectively, and reducing costs. This shift is evident in the growing economic and social impact of tech giants such as Google, Meta, Tesla, Uber, and OpenAI.

How does data shape — and deform — our view of sustainable development?

In the realm of sustainable development, reliable data forms the foundation for strategic planning and complex decision-making at all levels. The first step in gathering this data is often identifying the right indicators or set of indicators that best capture the phenomenon in question. For instance, climate change can be tracked using indicators like glacier size and volume, or the global average surface temperature. Consequently, historical trends combined with models predicting future developments are used to set goals and shape strategies—such as limiting global temperature rise to below 2°C compared to pre-industrial levels.

While numbers, statistics, and trends provide an objective way to understand and evaluate reality, they remain tools that can be misused or misunderstood. Beyond ensuring the quality of the data, there’s also the risk of oversimplifying complex issues by reducing them to mere numbers. Misinterpretation of data can lead to stereotypes, false claims, and the spread of misinformation. In the field of sustainable development, this can result in an unintentional form of greenwashing, which can be just as damaging as manipulating data on purpose for marketing or falsely claiming green credentials.

Sustainability. What does it even mean?

Sustainability has become such an overused and generic term that it has lost its meaning, leaving people unsure of what they’re really discussing. For years, organizations and individuals have attempted to provide a clear definition of sustainability, but these efforts have often only added to the confusion. Definitions that are too precise tend to be temporary, bound by specific political, economic, environmental, or cultural contexts. On the other hand, definitions that are too vague don’t fit well with today’s data-driven approach to assessing sustainability.

In attempting to responsibly simplify the definition of complex concepts like sustainability, we enter a never-ending cycle. For instance, if we were to try measuring sustainable development based on the famous 1987 Brundtland definition (“meeting the needs of the present without compromising the ability of future generations to meet their own needs”), we would first need to define the current and future needs of people. Naturally, these needs vary depending on location, political climate, culture, or values. Furthermore, we would have to distinguish between a need and a want, and define what we mean by "future generations." Although such processes might eventually lead to easily measurable concepts, they also force us to make unreliable arbitrary decisions—such as determining people's needs and time horizons for future generations—thus modifying the original concept of sustainable development.

Today, almost any activity can be labeled as sustainable, a fact clearly illustrated by the widespread misuse of the 17 UN Sustainable Development Goals (SDGs). Many businesses claim to contribute positively to several goals, but such claims must be scrutinized more thoroughly. A business or activity should not be evaluated solely for its positive impacts but should offer a complete view of its interaction with all the Goals, including any negative consequences. At the same time, evaluating a business against all 17 SDGs is costly, complex, and often disadvantageous.

False sustainability indicators

Indicators often bend reality. For example, when estimating travel time savings, a driver may overestimate the savings when increasing speed from 90 to 100 mph, but underestimate it when increasing between 30 and 40 mph. Although the speed increase is the same, 10 mph, the time savings at the initial 30 mph speed is five minutes, while at 90 mph it is less than one minute. The relationship between speed and time savings is not linear, nor is the increasing hazard at higher speeds. The risk increases faster than people often realize. Just as a wrong estimate of speed can lead to accidents, a wrong interpretation of the indicator can lead to wrong decisions, for example in sustainability.

Figure 1: "Paceometer" - a speedometer showing the pace values (in minutes per 10 miles) at selected levels (mph). Source: Peer, E., & Gamliel, E. (2013). Pace yourself: improving time-saving judgments when increasing activity speed. Judgment and Decision Making, 8(2), 106-115.

‍

Indicators often represent a concept in a limited way, leading to oversimplification or confusion. For example, if we aim to improve public health, we need to monitor the relevant factors and quantify people’s health issues. It’s common to use an existing indicator, such as the number of deaths per 1,000 inhabitants per year, which is widely available and accurate at a national level. However, this indicator doesn’t directly measure health problems but instead tracks the number of deaths. This deforms the definition of the original concept being measured and, consequently, the strategy for improving public health. Placing too much emphasis on a misleading metric can, in extreme cases, result in the implementation of ineffective or even counterproductive measures.

In complex areas like sustainability, where evaluation is key, the concept is often shaped to fit the available data and existing indicators. Without a clear, robust definition of sustainability and a broad set of high-quality indicators, there is a high risk of selecting nonrepresentative or even arbitrary indicators. This creates a feedback loop where varying interpretations of sustainability arise from selected indicators, making the concept increasingly incoherent and eventually meaningless. Therefore, it can be argued that the absence or inadequacy of indicators actually shapes the definition of the phenomenon being measured—in this case, sustainability.

The combination of these two dynamics—where the indicator is treated as the whole concept of sustainability and where the definition of sustainability is driven by available indicators—creates numerous risks and leads to many misinterpretations. A clear example is when overall sustainability gets confused with specific indicators or groups of indicators, such as reductions in greenhouse gas emissions. This can result in practices being incorrectly labeled as sustainable, even when they are unsustainable overall, which undermines the ability to make correct decisions.

This incompetent focus can strongly influence both theory and practice, narrowing attention to only measurable phenomena such as monetary values, energy consumption, carbon footprints, water usage, waste production, workplace accidents, or basic employee characteristics like age and gender.

The need for thinking outside of the box.

It’s undeniable that the role of data in decision-making and planning will continue to grow. However, in a complex field like sustainability, we face numerous challenges that need to be proactively addressed—especially in the context of the increasing volume of EU legislation. Sustainability is a vague and evolving concept, and thus must be treated as such. Measuring sustainability solely through indicators and numbers significantly increases the risk of manipulation, oversimplification, or misinterpretation. For instance, sustainability often gets reduced to greenhouse gas emissions problem, which is further simplified to focus solely on electromobility.

Therefore, it’s crucial to gather and understand both quantitative and qualitative information and to apply a holistic approach. This means considering the entire spectrum of sustainability when evaluating its individual components, while respecting the interconnectedness of various issues and the dynamic nature of their development.

‍

The growing calls to action are vital for the successful implementation of sustainability concept. But it’s important to recognize that individual goals and actions are based on data and information. This is why, as we work to transform our society and economy, it’s essential to continually debate, critically assess, and refine what sustainability truly means, what it looks like in practice, and, equally important, what it isn’t. Perhaps we should even dial back the overuse of the term "sustainable," which has become so ever-present that it feels like we could use it as a new renewable energy source.

We must always remember that metrics and indicators are just tools—helpful servants but dangerous masters.