These 4 Strategies can Steer your Digital Supply Chain Transformation
As customers adopt digital media for everything from news consumption to socialization, companies are re-imagining their approach toward modifying their business processes.
FREMONT, CA: Supply chain managers, like other business leaders, can view digital transformation as both an opportunity and a challenge. While realizing that digital technologies can drive performance enhancement, there is often a lack of an extensive plan for digital transformation, making it unclear where to begin or how to implement digital technology. Supply chain as an aspect within enterprises becomes much more of a stakeholder.
So with Enterprise Resource Planning (ERP) at the core, a significant transition from the internally focused approach to a much broader and more cooperative approach using current technologies is seen.
Strategies to Drive Digital Supply Chain Transformation:
• Use of Multi-Party Network: The first trend is moving towards a multi-party or multi-enterprise network. This will be more evident with procedures such as procure-to-pay, order-to-cash, and multi-party procedures of this kind will transfer to the systems. This is a significant change away from ERP. ERP is useful for human resources and finance. But many businesses don't want to take on these expensive projects drawn out. Simplified, network-based deployment with lower cost and faster cloud results are effective. Multi-party networks feature multi-level supply chain cooperative planning and implementation.
• Enhanced Machine Learning and AI Planning: Planning is an area where increasing numbers of clients are looking to leverage AI. The need to take correct decisions at the transaction layer is most important. This is where platforms with autonomous agent tools that make real-time transactional decisions provide a disruptive approach. Technologies like AI and machine learning are not performing well as these technologies have limited access. A change to multi-enterprise networks will allow businesses to gain significantly higher value from these techniques as they can leverage the system.
• Active and Autonomous Towers of Control: Moving to Actionable / Autonomous towers of command will drive more value than mere analytics. Big data projects tend to be paradigms that look backward as well as business / internally concentrated. Processes need to sit as planning, decision-making, AI, etc. on the transaction layer. Instead of company teams, these information projects are run by IT teams. Moving to Actionable / Autonomous towers of command will drive more value than mere analytics.
• Finding and Maintaining New Technology Talent: These new techniques involve fresh abilities, of which there is currently an evident shortage. As these techniques grow, this will only worsen. As we move toward this artificial intelligence and machine learning-driven paradigms, there will be a distinct advantage for businesses that can train employees or attract the right talent with these skills.
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