Preparing Your Supply Chain for the Future: A Foundation for AI and beyond
Successfully integrating advanced technologies like Artificial Intelligence (AI) into your supply chain requires more than just acquiring the latest tools. It demands a proactive approach focused on building a strong operational foundation. Here’s how to prepare your organization for a future powered by clever automation.
1. Establish a Clear Strategic Vision
Begin by clearly defining your desired future state.What specific improvements are you aiming for? are you looking to optimize inventory levels, streamline operations to maintain output with a leaner workforce, or improve the accuracy of demand forecasting? Framing these goals as solvable problems – and asking whether technology can be part of the solution – is the crucial first step towards impactful change. A well-defined problem statement provides direction for all subsequent efforts.2. Prioritize Process Standardization & People
Automation, including AI-driven automation, thrives on consistency. before implementing any technology, ensure your core processes are standardized and well-documented. Consider a common example: purchase order processing. The system needs clear instructions on verifying pricing,routing orders for approval based on value,and calculating expected delivery dates. These processes involve numerous decisions. Without established workflows and clear decision-making protocols, implementing automation – and AI - will be significantly more challenging.3. Data Quality is Paramount: Standardize and Cleanse
Technology systems are fundamentally reliant on high-quality data. inconsistencies in data entry can derail automation efforts. A system will treat “something,” “some.thing,” ”some_thing,” and “Smthg” as distinct entities, hindering accurate processing. While mapping tables can be used to train a system to recognize these variations, it’s far more efficient to proactively standardize and normalize data at its source. This may necessitate changes to data collection methods and storage locations.
For example,automated order entry - with or without AI assistance – requires the system to reliably locate and interpret information. some organizations address this by requiring customers to submit orders through portals or utilize standardized templates. While advanced systems can process unstructured documents like PDFs, thay still require training to accurately identify key fields like company name, order quantity, and purchase order number, accounting for the diverse ways customers might label them.4. Document Decision-Making Logic
AI readiness extends to explicitly documenting the rules that govern your decisions.Even with AI’s ability to analyze vast datasets, it still requires clear guidelines. Take the time to map out how your team currently makes decisions, even those that appear routine. This detailed documentation is essential for successfully integrating AI into your business operations. Essentially, you need to articulate the “if/then” logic that drives your current processes.
Don’t Neglect the Core System
these preparatory steps are predicated on having a robust core system in place,such as an Enterprise Resource planning (ERP) system. If your supply chain lacks a unified platform connecting order entry, procurement, production tracking, costing, and accounting, establishing that foundation should be your initial priority.
Furthermore, if your existing ERP system is underperforming, these strategies will not only yield immediate improvements but also position you for future success with AI and other advanced technologies.
Preparing for the Future, Today
Don’t postpone readiness while waiting for AI to reach full maturity. By focusing on a clear vision, strengthening processes, improving data quality, and defining decision rules now, you’ll be well-positioned to capitalize on the opportunities AI presents. Importantly, these efforts will likely deliver efficiencies and cost savings even before your first AI project is launched, providing tangible benefits in the short term.
