{"id":56342,"date":"2025-11-08T08:34:00","date_gmt":"2025-11-08T08:34:00","guid":{"rendered":"https:\/\/manufacturing-today.com\/?p=56342"},"modified":"2025-11-05T11:51:30","modified_gmt":"2025-11-05T11:51:30","slug":"why-dont-we-trust-our-data-by-bjorn-gerster","status":"publish","type":"post","link":"https:\/\/manufacturing-today.com\/news\/why-dont-we-trust-our-data-by-bjorn-gerster\/","title":{"rendered":"Why don\u2019t we trust our data? By Bj\u00f6rn Gerster\u00a0"},"content":{"rendered":"

It\u2019s\u00a0no secret that the manufacturing industry is\u00a0in the midst of\u00a0a significant transformation, grappling with technological shifts, increased customer expectations, and supply chain vulnerabilities. The effects are starting to show. Our latest Global Business Optimism Insight Report reveals that confidence in supply chain resilience is still slipping. After a sharp 9.7 percent drop in Q3, the index dipped again in Q4, pointing to ongoing uncertainty.<\/span>\u00a0<\/span><\/p>\n

In a landscape this complex, data is a manufacturer\u2019s critical ally, allowing teams to stay agile,\u00a0anticipate\u00a0disruption, and make smarter decisions. Yet, in my daily conversations with manufacturing leaders, one thing has become increasingly clear: despite having more data than ever at their fingertips, many still\u00a0aren\u2019t\u00a0using it to inform critical business decisions.\u00a0There\u2019s\u00a0a clear confidence gap when it comes to\u00a0actually turning\u00a0data into action. So why has this happened and how do we fix it?<\/span>\u00a0<\/span><\/p>\n

\"aThe root causes of the data confidence gap<\/span>\u00a0<\/span><\/h3>\n
    \n
  1. Poor data quality and manual processes<\/strong><\/li>\n<\/ol>\n

    Clean, structured, compliant, and up-to-date data is the foundation of effective decision-making, but many manufacturers still struggle to achieve it. The reliance on manual data collection, a practice still widespread, introduces errors and delays that erode trust in the data from the start. When data is collected manually,\u00a0it\u2019s\u00a0susceptible to human error and outdated information, making it unreliable for analysis. These issues often cause leaders to rely on intuition and experience rather than a data-driven approach. While intuition will always have its place, it\u00a0can\u2019t\u00a0keep pace with the complexities of modern manufacturing, such as volatile supply chains and technological change. Inaccurate supplier data can lead to sourcing from high-risk partners, or\u00a0failing to comply\u00a0with crucial regulations, directly\u00a0impacting\u00a0the entire supply chain and the manufacturer\u2019s bottom line.<\/span>\u00a0<\/span><\/p>\n

      \n
    1. Absence of a clear data strategy<\/strong><\/li>\n<\/ol>\n

      The sheer volume of data at the modern manufacturer\u2019s fingertips is often viewed as a challenge, but the real problem\u00a0isn\u2019t\u00a0a lack of information,\u00a0it\u2019s\u00a0the absence of a clear, coherent plan for how to use it. Many companies struggle with fragmented data, where information is trapped in isolated silos across different systems and formats. This makes it\u00a0nearly impossible\u00a0to get a unified, real-time view of operations. Leaders\u00a0can\u2019t\u00a0trust what they\u00a0can\u2019t\u00a0see, and they become reluctant to make decisions based on an incomplete or disconnected picture.<\/span>\u00a0<\/span><\/p>\n

      Without a clear data strategy, this fragmented data is simply noise.\u00a0It\u2019s\u00a0a resource that\u00a0isn\u2019t\u00a0being\u00a0leveraged, leaving companies unable to effectively\u00a0identify\u00a0trends,\u00a0optimize\u00a0processes, or predict future outcomes. This is critical for the supplier lifecycle, where a lack of a trusted data layer prevents a holistic view of potential risks. Without this, manufacturers\u00a0can\u2019t\u00a0effectively vet new suppliers, find competitive costs, or manage\u00a0logistics\u00a0efficiently. The same challenges appear across sales and marketing. Poor or missing data creates gaps in evaluating market potential, qualifying leads, and\u00a0analyzing\u00a0cross-sell and up-sell opportunities. The result is a cycle of hesitation and reliance on intuition, as the data, though plentiful, is not presented in a way that inspires confidence or enables action.<\/span>\u00a0<\/span><\/p>\n

        \n
      1. Organizational and cultural resistance<\/strong><\/li>\n<\/ol>\n

        Even with the right data and technology, a data-driven culture cannot thrive without the right people and mindset. Organizational resistance is a major barrier, with employees\u00a0and managers who are accustomed to traditional methods being\u00a0skeptical\u00a0of new data-driven approaches. This cultural gap often stems from a lack of data literacy and training. Many employees do not have the skills needed to interpret and use data effectively, which leads to a lack of confidence in their abilities and a return to outdated, intuition-based decision-making. This extends to supply chain or sales teams who, without the confidence to use data, may rely on\u00a0established, but potentially outdated, relationships instead of\u00a0leveraging\u00a0insights to build more resilient networks.<\/span>\u00a0<\/span><\/p>\n

        Practical steps to overcome the challenges<\/span> \"n<\/span><\/h3>\n

        So, while the issues I outline above\u00a0aren\u2019t\u00a0the only ones, they are the three most common reasons for the data disconnect we see across the manufacturing sector. How can we, as an industry, overcome these challenges?<\/span>\u00a0<\/span><\/p>\n

          \n
        1. Build a data-driven culture<\/strong><\/li>\n<\/ol>\n

          Leadership must champion the use of data in all decision-making processes.\u00a0It\u2019s\u00a0about fostering a culture where data is a shared asset and a common language. Encourage collaboration between IT, operations, and executive teams to break down data silos and ensure everyone understands the value of the information being collected. That data must also be shared across the relevant processes and with the right users to ensure it drives meaningful action within the organization.<\/span>\u00a0<\/span><\/p>\n

            \n
          1. Invest in targeted training<\/strong><\/li>\n<\/ol>\n

            To close the data literacy gap, manufacturers need to offer targeted training. This empowers employees to understand and interpret data relevant to their specific roles, enabling them to make smarter decisions and solve problems more effectively.<\/span>\u00a0<\/span><\/p>\n

              \n
            1. Implement a comprehensive data strategy<\/strong><\/span><\/li>\n<\/ol>\n

              A comprehensive data strategy is key to transforming raw data into a powerful asset. It begins with improving data quality through robust master data management, ensuring all information, from supplier to customer records, is\u00a0accurate\u00a0at the source. This trusted data then enables enhanced visibility, breaking down departmental silos to create a unified platform. This holistic view is crucial for proactively\u00a0identifying\u00a0supply chain risks and empowering data-driven sales efforts throughout the customer lifecycle. The\u00a0final step\u00a0is\u00a0leveraging\u00a0data for strategic insights, moving beyond simple reporting to advanced analytics that support critical decisions on everything from ESG compliance to market positioning.<\/span>\u00a0<\/span><\/p>\n

              Ultimately, a\u00a0strong data strategy shifts an organization from a reactive to a proactive and predictive state, helping it to not just react to change, but to actively thrive in it.\u00a0<\/span><\/p>\n

              Bj\u00f6rn Gerster\u00a0\u00a0<\/strong><\/p>\n

              www.dnb.co.uk\u00a0<\/span>\u00a0<\/span><\/a><\/p>\n

              Bj\u00f6rn Gerster is European Lead Centre of Excellence, Manufacturing at Dun & Bradstreet. Dun & Bradstreet, a leading global provider of business decisioning data and analytics, enables companies around the world to improve their business performance. Dun & Bradstreet\u2019s Data Cloud fuels solutions and delivers insights that empower customers to accelerate revenue, lower cost, mitigate risk, and transform their businesses. Since 1841, companies of every size have relied on Dun & Bradstreet to help them manage risk and reveal opportunity.\u00a0<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

              It\u2019s\u00a0no secret that the manufacturing industry is\u00a0in the midst of\u00a0a significant transformation, grappling with technological shifts, increased customer expectations, and<\/p>\n","protected":false},"author":6,"featured_media":56343,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[685,2],"tags":[4077,4078,18,4034],"class_list":["post-56342","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","category-features","tag-bjorn-gerster","tag-dun-bradstreet","tag-data","tag-4034"],"acf":[],"yoast_head":"\nWhy don\u2019t we trust our data? 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