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The State of BI, Data, and Analytics in Manufacturing

Introduction

This Research Insight is part of a series focusing on industry-specific analysis of business intelligence (BI), data, and analytics.

Even before the COVID-19 pandemic, the global manufacturing industry saw significant transformation and growth. Smart manufacturing, 3-D printing, the Internet of Things (IoT), and artificial intelligence (AI) will alter the status quo for many in Manufacturing. Industry 4.0, the fourth industrial revolution, automates, augments, evolves, and transforms industrial processes using smart technology. BI, data, and analytics play a critical role in this revolution. IoT creates a potential trove of new data, with AI improving manufacturing systems and processes without the need for direct human intervention.

The impacts of COVID-19 exacerbate the challenges associated with these transitions. Some players rely heavily on online business and e-commerce, which can create significant supply-chain issues. Others temporarily or permanently ceased operations, which affects the competitive landscape. Yet, a sizeable segment of the industry also flourishes as businesses adapt and meet rapidly changing customer needs.

Because we collected the survey data analyzed in this report during the early stages of the pandemic, the view is mixed and you should temper it for the vastly different reality that set in after 1Q20 (see the Research Insight “COVID-19 Impacts on Businesses, Budgets, and Projects: Dresner Advisory’s Third Set of Findings”).

Executive Summary

  • Manufacturing organizations report more success with their BI solutions than their peers in other industries. Their levels of data-driven decision-making exceed other industries.
  • The higher-than-average rates of BI success and data-driven decision-making that manufacturing organizations report indicate they tend to have a high level of overall data quality, and their users trust in data as “truth.”
  • Manufacturing organizations indicate increasing BI budgets, with the largest portion of planned spending allocated to internal headcount.
  • Although manufacturing organizations show lower levels of data literacy, they report higher rates of building or planning data-literacy programs.
  • Manufacturing organizations score the same or lower than other industries on the Dresner Advisory Services Hyper-Decisive® Maturity Model.
  • Although many manufacturing organizations lack formal BI, data, and analytics leadership—as do their peers in other industries—they are more likely will to have added these positions this year.
  • The rate of BI penetration in manufacturing organizations lags other industries, and we expect this will continue.
  • Manufacturing organizations consider improved operational efficiency and reduced costs, growth in revenue, and making better decisions as their top three BI objectives.
  • Compared to other industries, manufacturing organizations show a higher propensity for the manufacturing, operations, finance, and sales functions (lines of business) to drive their BI initiatives.
  • Manufacturing organizations show a higher consumption of information from middle management, line managers, and suppliers when compared to other industries.
  • Manufacturing organizations rate sales planning as a much higher technology priority than do respondents in other industries. However, the lack of other meaningful higher-priority differences reflects that manufacturing organizations tend to adopt new technologies slowly and conservatively.
  • The majority of manufacturing organizations prefer a best-of-breed BI solution, which is significantly higher than other industries.

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