While most business sectors have welcomed the efficiencies and benefits that cloud technologies and software-as-a-service (SaaS) offerings bring, the life sciences industry has been slow to embrace external cloud networks.
Faced with a growing range of tech solutions in marketing, from AI to big data to blockchain, business-to-business (B2B) companies too often choose the status quo.
As early as 2015, McKinsey’s “Digital America” report projected that adoption of Industry 4.0 technologies in manufacturing alone was expected to increase domestic GDP by more than $2 trillion by 2025.
In manufacturing today, data analysis tools can give management the information it needs to make better decisions in areas such as maintenance and labor.
Is your enterprise dominated by passive thinking and prescribed routines? Or is it one that generates fresh thinking and unlocks insights into the future?
Do you know what a retailer and a tightrope walker have in common? They both have to balance. For the tightrope walker, the logic is clear. But what’s the balance that a retailer is looking for?
Current business conversation often focuses on data and big data. Data are the raw information from which statistics are created and provide an interpretation and summary of data.
According to a report by PwC, industrial sectors worldwide plan to invest $900 billion in Industry 4.0 each year. Despite these growing technology investments, only a few technologies are significantly mature to drive measurable quality impacts.
Lean manufacturing is a philosophy focused on maximizing productivity and eliminating waste while creating a quality product.
In the article, “ANSI’s Role in the Wide World of Standards,” (Quality Digest, March 12, 2019), we looked at where standards originate and how companies a