Misinformation, Confusion, and Fear Mongering characterize the general state of public information about Artificial Intelligence (AI)!
Between the government mindlessly trying to “slow” the growth of AI and the media trying to scare you that AI is coming for your job, the public has been totally confused. AI needs new Public Relations representation!
AI has the potential to bring significant process improvements and financial benefits to supply chain management, but few companies have a thorough understanding of how and where to apply AI and how to integrate it with existing supply chain processes and technologies. In this post, I’ll attempt to bring clarity to the types, usage, and application of AI in your supply chain, identify the best method to get started, and chart a strategic course for AI implementation.
The Current State of AI Comprehension
To begin, let’s examine the state of AI comprehension in most organizations. Through his Indago research community, Adrian Gonzalez published a survey of the state of the supply chain industry’s understanding of AI. His summary stated:
“Almost a third of our member respondents (32%) said they either have a ‘Very Low’ (9%) or ‘Low’ (23%) knowledge/understanding of AI and how it can be used in supply chain management. Most of the other respondents (64%) said they have ‘Moderate’ knowledge, while only 5% said they have ‘High’ knowledge.”
Source: Indago, January 2023 survey (n=22)
My experience is similar. I recently spoke at the “2023 Applied AI for Distributors Conference.” I was surprised by the predominance of attendees who instead of seeking specific supply chain solutions were just looking for basic knowledge of AI and methods to get started integrating AI into their supply chains.
So let me offer some basic context and an approach for those seeking next steps. AI focuses on learning from big data from a multitude of sources and delivering intelligent Insights, Predictions, and Recommendations based on that learning. It uses complete internal and external data, advanced algorithms, and machine learning models to predict future trends and outcomes. AI models also tend to operate continually looking for data changes and evaluating the impact of that change. They can be trained to then alert knowledge workers or legacy systems about that change event.
The distinction to ERP systems is fundamental. ERP systems are primarily designed for process automation across various business functions. ERP systems assume predictable demand and reliable supply. ERP systems tend to plan periodically, not continually, and they do not react quickly or well to rapid change.
It’s worth noting that real power comes from integrating AI capabilities into your ERP system and other enterprise applications. AI tools can provide depth and capabilities that are not present in ERP systems. You also want to implement seamlessly and without cultural disruption—that is, you want to significantly improve your operational methodology while keeping your IT landscape and ways-of-working intact. By directly updating your ERP, CRM, and Supply Chain systems with AI recommendations, the optimum results become easily accessible and consumable by all your knowledge workers without cultural disruption.
Developing an AI Strategy
So, how do you develop an AI strategy? One approach is to conduct a Rapid AI Assessment. This evaluates your planning, fulfillment, and supply chain operations, identifying opportunities and threats, then proposes remedial actions and AI-based process improvements. It consists of three steps:
Identifying and understanding your current state and operating practices, and revealing key issues that impair your process efficiency and cost you money.
Determining AI-enhanced, best practice-based future state operations and technology.
Developing a Roadmap that identifies process improvement programs and optimum results.
Your Roadmap is a list of initiatives with their recommended sequence, key strategic assumptions, and alternatives. It helps you define the magnitude of your opportunity. We emphasize “Quick Wins” when possible – changes that rapidly deliver value and have minimal organization impact, technology requirements, and cost.
Some of the key benefits with this approach include:
It is your strategically-incremental plan to improve your business management functions. You receive a strategic vision that is divided into “bite-sized chunks” for implementation. It avoids the “Big Bang” approach with massive changes to your business processes and IT landscape.
Your economic benefits are delineated in advance providing justification for employing AI to enhance your business processes.
You avoid organizational change or disruption and keep your IT landscape intact – you continue using your familiar legacy systems. Your supply chain planning and operations become significantly more efficient, delivering better results, while your information consumers experience no disruptions to their normal ways-of-working.
You avoid risk. You have no need to spend on protracted process reengineering, consultants, and data acquisition. We find that CIOs want to protect themselves from incorrect short-term AI decisions. The strategically-incremental approach insulates you from rapid change – and the rate of advancement and transformation in AI is astounding.
Summary
Don’t let Misinformation, Confusion, and Fear Mongering prevent you from getting started on evaluating how AI can deliver significant supply chain process improvements and financial benefits to your company. There are a growing number of use cases and success stories already out there, like the Delly’s case study featured recently on Talking Logistics. For many companies, knowing where and how to begin is the most difficult step, which is why developing an AI strategy using an approach like a Rapid AI Assessment is a smart first step.
Pete Stiles is Chief Marketing Officer at Analytics2Go, where he is responsible for all sales and marketing activities. Pete has over 40 years experience developing strategies and building and creating sales and marketing programs for multiple supply chain technology and service companies. Throughout his career, Pete has used the Rapid Assessment model to help clients identify and focus their business improvement efforts. To learn more about the Rapid AI Assessment model, you can contact Pete at pstiles@analytics2go.com
A Rapid Assessment Approach to Developing a Supply Chain AI Strategy
Misinformation, Confusion, and Fear Mongering characterize the general state of public information about Artificial Intelligence (AI)!
Between the government mindlessly trying to “slow” the growth of AI and the media trying to scare you that AI is coming for your job, the public has been totally confused. AI needs new Public Relations representation!
AI has the potential to bring significant process improvements and financial benefits to supply chain management, but few companies have a thorough understanding of how and where to apply AI and how to integrate it with existing supply chain processes and technologies. In this post, I’ll attempt to bring clarity to the types, usage, and application of AI in your supply chain, identify the best method to get started, and chart a strategic course for AI implementation.
The Current State of AI Comprehension
To begin, let’s examine the state of AI comprehension in most organizations. Through his Indago research community, Adrian Gonzalez published a survey of the state of the supply chain industry’s understanding of AI. His summary stated:
My experience is similar. I recently spoke at the “2023 Applied AI for Distributors Conference.” I was surprised by the predominance of attendees who instead of seeking specific supply chain solutions were just looking for basic knowledge of AI and methods to get started integrating AI into their supply chains.
So let me offer some basic context and an approach for those seeking next steps. AI focuses on learning from big data from a multitude of sources and delivering intelligent Insights, Predictions, and Recommendations based on that learning. It uses complete internal and external data, advanced algorithms, and machine learning models to predict future trends and outcomes. AI models also tend to operate continually looking for data changes and evaluating the impact of that change. They can be trained to then alert knowledge workers or legacy systems about that change event.
The distinction to ERP systems is fundamental. ERP systems are primarily designed for process automation across various business functions. ERP systems assume predictable demand and reliable supply. ERP systems tend to plan periodically, not continually, and they do not react quickly or well to rapid change.
It’s worth noting that real power comes from integrating AI capabilities into your ERP system and other enterprise applications. AI tools can provide depth and capabilities that are not present in ERP systems. You also want to implement seamlessly and without cultural disruption—that is, you want to significantly improve your operational methodology while keeping your IT landscape and ways-of-working intact. By directly updating your ERP, CRM, and Supply Chain systems with AI recommendations, the optimum results become easily accessible and consumable by all your knowledge workers without cultural disruption.
Developing an AI Strategy
So, how do you develop an AI strategy? One approach is to conduct a Rapid AI Assessment. This evaluates your planning, fulfillment, and supply chain operations, identifying opportunities and threats, then proposes remedial actions and AI-based process improvements. It consists of three steps:
Your Roadmap is a list of initiatives with their recommended sequence, key strategic assumptions, and alternatives. It helps you define the magnitude of your opportunity. We emphasize “Quick Wins” when possible – changes that rapidly deliver value and have minimal organization impact, technology requirements, and cost.
Some of the key benefits with this approach include:
Summary
Don’t let Misinformation, Confusion, and Fear Mongering prevent you from getting started on evaluating how AI can deliver significant supply chain process improvements and financial benefits to your company. There are a growing number of use cases and success stories already out there, like the Delly’s case study featured recently on Talking Logistics. For many companies, knowing where and how to begin is the most difficult step, which is why developing an AI strategy using an approach like a Rapid AI Assessment is a smart first step.
Pete Stiles is Chief Marketing Officer at Analytics2Go, where he is responsible for all sales and marketing activities. Pete has over 40 years experience developing strategies and building and creating sales and marketing programs for multiple supply chain technology and service companies. Throughout his career, Pete has used the Rapid Assessment model to help clients identify and focus their business improvement efforts. To learn more about the Rapid AI Assessment model, you can contact Pete at pstiles@analytics2go.com
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