The steel sector is a major contributor to global carbon emissions due to its energy-intensive production processes, primarily reliant on fossil fuels. As governments implement carbon pricing mechanisms, such as carbon taxes and emissions trading systems, the steel industry faces increasing costs related to its carbon footprint. Accurately quantifying these costs is complicated by significant data quality issues. Challenges include inconsistent emissions reporting standards, lack of transparency in supply chains, and variability in production technologies and fuel mixes across regions. Poor data quality hampers the ability to assess true carbon costs, undermining effective policy design and investment decisions aimed at decarbonization. Improving data accuracy and harmonizing reporting frameworks are critical for enabling the steel sector to respond effectively to carbon pricing, optimize emissions reductions, and transition towards low-carbon technologies such as electric arc furnaces and hydrogen-based steelmaking. Addressing these data challenges also supports better market functioning and investor confidence in sustainability initiatives within the steel industry.