This article was written by Snowflake and originally appeared on the Snowflake Blog here: https://www.snowflake.com/blog/datas-evolution-in-the-cloud-smarter-data-insights-in-manufacturing/
The COVID-19 pandemic caused production slowdowns and supply chain disruptions around the world, posing unprecedented challenges for the manufacturing industry. Manufacturers face continued pressure from decreased demand, production, and revenues; cash-flow liquidity challenges; and difficulties in managing debt obligations; among other issues. 1
But despite the financial crises, manufacturers are still focused on investing in smart solutions that will help them leverage new technologies such as artificial intelligence, machine learning, and the Industrial Internet of Things (IIoT). These solutions will enable them to glean data-driven insights, make better business decisions, and ultimately stay ahead of the competition.
These are some of the insights from a recent survey, conducted by The Economist
Intelligence Unit and sponsored by Snowflake, of 914 global executives across eight
industries, including 117 from the manufacturing sector. The survey reveals how this sector’s leaders are adapting their data strategies, engaging with the broader data ecosystem, and converting data insights into growth and performance.
Survey results reveal that executives in the manufacturing industry see major opportunities from using data-driven insights. The biggest opportunities are increasing customer satisfaction, improving the customer experience, growing revenue and profits, and expanding the customer base. At the same time, 71% of manufacturing respondents agree that it is a challenge to integrate data from varied sources, perhaps attributable to the huge volumes and semi-structured nature of IIoT log data.
Asked about their top priorities in enhancing digital capabilities over the next three years, 41% cite improving their data infrastructure, 41% plan to develop or update their data strategy, and 40% plan to invest in artificial intelligence and machine learning tools. By making their data environments and processes more robust, manufacturing companies will be able to survive the current disruptions and better prepare for the future.