Air pollution today is not just an environmental issue; it has become an economic, social, and even security issue. Every day, metropolises pay heavy costs in terms of diseases, reduced productivity, infrastructure erosion, and decreased quality of life. In such circumstances, “economic intelligence,” when combined with “lean thinking” and “digital transformation,” can save cities from the vicious cycle of pollution and transform managers’ decision-making from a reactive mode to a predictive and value-creating one. In the lean approach, the principle is to eliminate waste and focus on real value; that is, all actions that do not lead to clean air are discarded and decision-making is directed toward actions that create the greatest return at the lowest cost. This is exactly where economic intelligence comes in. Economic intelligence can bring together vast amounts of environmental, traffic, transportation, economic, health, and citizen behavior data and, by analyzing them, tell managers which intervention is the least expensive and most effective way to reduce pollution. In leading countries, the role of this intelligence is clearly visible. For example, the Netherlands was able to show by analyzing the cost-benefit of projects that every 1% increase in the share of cycling in large cities saves 240 million euros in health and energy costs annually. This same data-driven approach led to the share of bicycles in daily commutes in Amsterdam and The Hague reaching 50%. This process was lean, because it was based on eliminating energy waste and reducing long-term costs. In Denmark, the city of Copenhagen used economic intelligence platforms to combine data on building energy consumption, wind flow, vehicle density, and peak pollution times. Its output showed that by optimizing the energy consumption of office buildings alone, 8% of urban pollutant emissions could be reduced. These results were implemented in a targeted and precise manner without wasting resources. That is, the same lean logic. In East Asian countries, Japan is a pioneer in using economic data for environmental policymaking. For example, Tokyo was able to calculate with economic intelligence models how much installing smart sensors on city cars and buses would help reduce fine dust. The result was that by implementing this plan, PM2.5 levels were reduced by between 20 and 25%. Importantly, these measures were taken within the framework of lean management: that is, focusing on bottlenecks and preventing resources from being diverted to projects that look stylish but have low environmental efficiency. In industrialized countries such as Germany, the combination of economic intelligence and lean thinking has also created a successful model. Economic analyses have shown that limiting the traffic of diesel cars in central Berlin would save €1.2 billion annually in pollution-related costs. Instead of taking clichéd and costly measures, decision makers focused on this main bottleneck; that is, implementing lean for maximum efficiency. Now, if we generalize these experiences to our own country's metropolises, economic intelligence can tell us by analyzing data: Does more pollution come from the transportation sector or from peripheral industries? Is it more cost-effective to invest in an industrial filter or to expand public transportation? Does closing schools really reduce pollution or is it just an ineffective social cost? Which streets and hours contribute the most to the production of PM2.5 and how should we intervene? This type of decision-making takes the city out of trial and error mode, and limited resources are spent in the areas that are most efficient. This is the principle of lean: identifying the bottleneck and attacking it precisely. In an evolutionary model, when economic intelligence is combined with digital transformation, the city becomes a living organism: sensors provide data, the platform analyzes, intelligent systems suggest corrective action, and city management makes quick, low-cost, and effective decisions. In such a cycle, air pollution is controlled not by slogans but by “calculation” and “value creation.”

Tehran Online