Snowflake together with the Intelligence Unit of The Economist has published a series of key points studied in their report on the flood of data generated by the IIoT to create new strategies within this area.
The company interviewed 914 decision makers from eight market sectors, including more than 100 from the manufacturing sector, showing that this sector is the one most likely to achieve growth opportunities.
“Data generated by employees, teams, vehicles, and key business partners must be collected, integrated, and analyzed in a way that produces meaningful information for product design, factory operations, sales, and distribution,” says José Maria Alonso Elizo. , Snowflake’s Southern Europe Regional Director.
The IIoT as a generator of new strategies
According to the study, the need to upgrade data architectures is high, with 41% of respondents stating that it is a top priority at their business, while as many others stating that they need to develop or update their own data strategy. Once the new infrastructure is in place, respondents expect customer satisfaction (38%) and profitability (33%) to increase.
Every business is connected to an ecosystem of suppliers, partners, customers, and other organizations with which it must collaborate to run its operations. Manufacturers, for example, must collaborate with raw material suppliers to understand availability and account for it in their production schedules.
For their part, retailers and consumer goods companies depend on logistics partners to transport merchandise from distribution centers to their points of sale or to deliver online orders to consumers’ homes.
Decision makers in production are faced with a huge data surge, much of it consisting of semi-structured data from the Industrial Internet of Things (IIoT).
The IIoT to create new strategies within this business area
Other important findings
Other key findings from the survey include:
• More opportunities through data: Almost a third (27%) of decision makers also expect that improved data analytics capabilities will allow them to develop new products or improve existing ones. One fifth expect an increase in employee productivity, and another 16% believe that it may further shorten the time-to-market.
• Artificial intelligence: 40% of production managers want to invest in artificial intelligence or machine learning in the next three years. Consequently, nearly a quarter (22%) also plan to hire more data scientists.
• Democratization of data: Decision makers in the manufacturing sector stated that their top priority in the next three years was to train more employees to work with data (33% in the industrial sector compared to an average of 30 % in other sectors), and provide more employees with access to data and analytics tools (15%), according to the survey.