5 Must-Haves for Supply Chain Leaders Before Implementing AI
The integration of artificial intelligence (AI) has become increasingly popular within supply chain management. The potential benefits of AI-backed supply chains are numerous, including improved efficiency, increased productivity, and reduced costs. Many organizations use AI to improve everything from inventory planning, to optimized vehicle routes. However, before supply chain operators and executives implement AI within their supply chain, they must consider these five key factors to create a seamless transition for this new technology.
Here are Osa’s top considerations for brands, retailers, or third-party logistics (3PLs) businesses hoping to implement AI:
1. Quality Data
We all know the old adage: garbage in garbage out. The first priority a supply chain needs to think about before implementing AI is quality data. AI requires a sufficient amount of data to train and learn from, and if the data is of poor quality, the AI's output will be unreliable. Supply chains must have accurate and up-to-date data that is accessible and well-organized.
To ensure the intended benefits of your AI strategy will be realized, it is also recommended to include both historical and real-time data from a variety of sources including suppliers, logistics providers, and customers. While the amount of data needed may differ depending on what your business is using AI for, machine learning requires a comprehensive amount of data. Supply chain leaders within an organization should research where they will be gathering data, how much data they expect to have at their disposal, and the quality to implement an AI strategy a.
2. Clear Objectives
AI is a powerful tool, but it is not a magic solution to all supply chain problems. Before implementing AI, supply chain practitioners must have clear objectives for what they hope to achieve through the integration of AI. Most importantly, how will utilizing AI impact supply chain operations and help meet business goals? These objectives should be specific, measurable, achievable, relevant, and time-bound. Having clear goals will help ensure that AI is used effectively and that it delivers the desired results.
Supply chain leaders should be able to identify the desired impact of implementing AI into their organization’s framework with clear use cases and unique selling points. When developing a plan, company leaders should consider ongoing issues that have not been solved by other software; they should be able to demonstrate to stakeholders how AI technology can mitigate that problem within a specific time frame.
3. Skilled Personnel
The integration of AI within a supply chain requires skilled personnel who understand both the technology and the supply chain processes. It is essential to have a team with a diverse range of skills, including data scientists, software developers, supply chain experts, and IT professionals. This team will be responsible for developing, implementing, and managing the AI system within the supply chain. Company leaders should also consider upskilling and reskilling existing employees, to foster loyalty and save costs for the business. Supply chain leaders should provide training and support to employees and partners to ensure they are prepared to work with AI-driven processes.
However, it may be beneficial to initially use outside AI expertise to help your business adequately begin to use the new technology. As more team members grow used to the software, in-house IT specialists can step in and mitigate the need for a third party.
4. Adequate Infrastructure
AI requires a robust and reliable infrastructure to operate effectively. AI requires a lot of computing power and storage capacity, which may require upgrading or expanding the existing IT infrastructure. Supply chain organizations need to invest in the necessary infrastructure to support the integration of AI within their operations. This infrastructure includes:
- High-performance computing (HPC) systems, which are designed to handle large-scale data processing and modeling tasks
- Storage systems, since AI models require access to large volumes of data to learn and improve
- Networking infrastructure because AI requires high-speed connectivity to move data between storage systems and computing resources; this infrastructure needs to support the high-bandwidth and low-latency requirements of AI workloads
- AI software tools such as programming languages, libraries, frameworks, and development environments
- Data integration and management tools, such as software that integrates and manages data from multiple sources, including suppliers, partners, and customers
5. Change Management Plan
Finally, before implementing AI, businesses should have an extensive change management plan in place. The integration of AI will likely require shifts to existing supply chain processes and may cause disruptions to workflows if not properly mapped out. A change management plan will help mitigate these risks by providing a structured approach to managing the transition to the new AI-driven processes. In many cases, businesses can work with their supply chain technology partners for additional resources and advice to ensure a smooth transition.
The plan to incorporate AI should include identifying and engaging with key stakeholders who will be impacted by the integration of AI, including employees, suppliers, customers, and partners. Good communication within the organization is also vital; supply chain leaders should develop a communication plan that outlines the implementation timeline, and the potential effects on existing processes and workflows.
AI offers supply chain leaders the potential to revolutionize their operations. But it requires careful planning and preparation in order to bring significant benefits. Supply chain leaders must have quality data, clear objectives, skilled employees, sufficient infrastructure, and a change management plan in place before implementing AI. By taking these steps, supply chains can ensure that the integration of AI is successful and delivers the desired results.
Interested in learning how AI can make an impact on your supply chain? Speak to an Osa representative to learn if you qualify for an Osa 360 Evaluation and learn how to determine a path that is more efficient, effective, and successful.
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