The world of supply chain management is rapidly evolving, and high-performing organizations are leading the charge by investing in artificial intelligence and machine learning (AI/ML) technologies. According to a recent survey conducted by Gartner, Inc., these top performers are investing in AI/ML at a rate more than double that of their low-performing counterparts.
The survey, which gathered insights from 818 supply chain practitioners across different industries and geographies, aimed to understand how the supply chain is adapting to economic changes, embracing sustainability, leveraging digital assets, and revitalizing the workforce and network of people.
One key finding from the survey was that high-performing supply chain organizations are using productivity as their primary focus for sustaining business momentum over the next three years. Instead of solely prioritizing efficiency and cost savings, these top performers recognize the importance of enhancing productivity to drive future success.
“Enhancing productivity is the key factor that will drive future success and the key to unlocking that productivity lies in leveraging intangible assets. We see this divide especially in the digital domain where the best organizations are far ahead in optimizing their supply chain data with AI/ML applications to unlock value,” explained Ken Chadwick, VP Analyst in Gartner’s Supply Chain Practice.
The data also revealed that high-performing organizations are significantly ahead when it comes to automating and optimizing processes using AI/ML technology. These companies have recognized the potential of AI/ML applications in extracting value from their supply chain data and are fully embracing these technologies.
This divide between high and low performers in AI/ML adoption sheds light on a broader strategic difference among organizations. Top performers are shifting their focus towards extracting value from digital assets to drive productivity, rather than solely aiming for efficiencies and cost savings.
“Capturing, protecting, and leveraging an organization’s data through the use of AI/ML is an example of how organizations are increasingly turning towards intangible assets to extract new sources of value,” stated Chadwick. “High-performing organizations are moving beyond the initial implementation stage to full adoption, resulting in better decision-making that unlocks new sources of value.”
In conclusion, high-performing supply chain organizations recognize the potential of AI and ML technologies in enhancing productivity and driving sustainable success. By prioritizing value extraction from digital assets and fully embracing these cutting-edge technologies, these organizations are paving the way for optimal efficiency in the supply chain management landscape.
FAQ Section:
1. What are high-performing organizations in supply chain management investing in?
High-performing organizations in supply chain management are investing in artificial intelligence and machine learning (AI/ML) technologies.
2. According to a survey, how is the investment in AI/ML different between high-performing and low-performing organizations?
According to the survey, high-performing organizations are investing in AI/ML at a rate more than double that of their low-performing counterparts.
3. What was the focus of the survey on supply chain practitioners?
The survey aimed to understand how the supply chain is adapting to economic changes, embracing sustainability, leveraging digital assets, and revitalizing the workforce and network of people.
4. What is the primary focus for sustaining business momentum for high-performing supply chain organizations?
The primary focus for sustaining business momentum for high-performing supply chain organizations is enhancing productivity.
5. How do high-performing organizations unlock productivity in their supply chain?
High-performing organizations unlock productivity by leveraging intangible assets, particularly by optimizing their supply chain data with AI/ML applications.
6. How do high-performing organizations differ from low-performing ones in terms of automating and optimizing processes?
High-performing organizations are significantly ahead in automating and optimizing processes using AI/ML technology compared to low-performing organizations.
7. What strategic difference is highlighted by the adoption of AI/ML between high and low performers?
The adoption of AI/ML highlights a strategic difference: high-performing organizations focus on extracting value from digital assets to drive productivity, while low-performing organizations mainly prioritize efficiencies and cost savings.
8. How are organizations increasingly extracting new sources of value?
Organizations are increasingly extracting new sources of value by capturing, protecting, and leveraging their data through the use of AI/ML technologies.
Key Terms and Jargon:
– Supply chain management: The management of the flow of goods and services from the point of origin to the point of consumption.
– Artificial intelligence (AI): The simulation of human intelligence in machines that are programmed to think and learn like humans.
– Machine learning (ML): A subset of artificial intelligence that enables machines to learn and make predictions or decisions without being explicitly programmed.
– Productivity: The measurement of efficiency in converting inputs into valuable outputs.
– Digital assets: Intangible assets that involve digital technology, such as data and software.
– Efficiency: The ability to accomplish tasks with the least amount of wasted resources, such as time, effort, and money.
– Cost savings: Reductions in expenses or expenditures to improve financial performance.
– Value extraction: The process of obtaining value or benefit from something, in this case, digital assets through the use of AI/ML.
Suggested Related Links:
– Gartner Supply Chain Management
– How AI Aids Supply Chains
– What is Machine Learning?
The source of the article is from the blog publicsectortravel.org.uk