Excitement about blockchain—the revolutionary cryptocurrency technology—has triggered a wildfire of public and private proposals to adopt industry-based blockchain solutions.
Companies today have a wealth of data about their customers, and executives know there is a lot of value in that data. However, recognizing that potential value and actually realizing it are two different things.
In deciding what they want to achieve with their data, companies can usually begin by looking for ways to do more business with existing...
GDPR broadens the definition of "personal information." This has particular relevance for the manufacturing industry, which is using AI and RFID to collect, use and integrate personal information into product manufacturing.
Machine learning is poised to revolutionize manufacturing by increasing production capacity, while lowering material consumption rates.
Complex digital models are helping manufacturers across all industries make process improvements and thwart potential problems, including cyberattacks.
CEOs left bewildered by the jumble of so-called big data at their fingertips better start connecting the dots soon. Otherwise, they could fall behind the competition over the next five years, especially if they're in financial services or healthcare.
As consumers increasingly demand more customized products at lower costs, manufacturing is only becoming more complex. These changes are presenting big challenges for manufacturers, and those that adapt and embrace data may be able to use that complexity to create a competitive advantage.
Manufacturers are increasingly deploying digital technologies to boost efficiencies and optimize their production lines. But while sensors, data and processing can provide actionable information, manufacturers still need humans with the skill and ability to manage it all.
Talk of machines replacing most customer-facing staff, let alone company managers, has so far been little more than that: talk.