### Is Supply Chain Technology Finally Ready to Meet Market Expectations?

Having spent over a quarter-century in supply chain management, one thing remains indisputable:

Change is inevitable.

Even in the best of times, variability is the constant factor that constricts supply chains. Variability in supply chains manifests in three primary forms: demand variability, supply variability, and lead time/cycle time variability.

Impact in any one area invariably affects all other areas. This interconnection is evident in the graphs below, which depict systemic impacts with the "bullwhip" effect shown by data from the US Federal Reserve.

**Figure 1: Demand Variability – Advance Retail Demands (FRED 1998-2023)**

**Figure 2: Supply Variability (FRED 1998-2023)**

**Figure 3: Delivery Lead Time Variability (FRED 1998-2023)**

Recently, these variables have significantly impacted global supply chains, becoming more noticeable to the public. As consumer demand and distribution channels evolved, the supply chain struggled to keep pace. The resulting bullwhip effect led to longer lead times and capacity constraints, making it challenging to meet the point of consumption.

### Five Emerging Trends Shaping the Future of Supply Chains

Of course, the COVID-19 pandemic exacerbated these issues, but the fundamental challenges have persisted for decades. Variability drives disruption in global commerce. The Global Supply Chain Pressure Index from the NY Federal Reserve illustrates the increasing risk in amplitude, frequency, and wavelength.

The bad news is that these challenges are here to stay.

However, the convergence of business processes and technology offers an opportunity to mitigate these effects. By leveraging data and insights, companies can achieve agility and resilience, transforming these concepts from mere buzzwords into actionable strategies.

**The Data Imperative**

W. Edwards Deming famously said, "Without data, you’re just another person with an opinion." In supply chain management, data is crucial yet often elusive. Companies mastering data collection, cleansing, and synchronization will dominate, acting with speed and confidence. The US market for master data management alone is a multi-billion-dollar industry, emphasizing the importance of quality data.

Transactional data, rather than master data, drives supply chain operations. The ability to manage both contextual and unstructured data in sync with operations is now a baseline requirement. The market is weary of investing in point solutions that fail to integrate seamlessly. Future solutions must lower operational costs and ensure data reliability.

**True Supply Chain Visibility (Beyond Tier 1 and Tier 2)**

"If you can’t see it, you can’t solve it." Visibility solutions have long promised value but often fall short. The key issue is the lack of mutual value in data sharing among supply chain partners. Effective visibility solutions must provide reciprocal value, ensuring participation and comprehensive visibility.

**ESG & Risk Management**

Sustainability, legislation, and geopolitical factors have always impacted supply chains. Companies that can adapt without significant redesign will succeed. ESG initiatives must encompass all supply chain tiers, providing real-time, prescriptive insights. Risk management must go beyond alerts to offer precise, actionable resolutions tailored to each supply chain.

**AI-Enabled (No/Low Touch) Demand Planning with Execution**

S&OP and IBP have improved P&L but remain disconnected from execution. Planning must reflect real-time operational realities. Systems integrating execution with planning, considering all supply chain tiers, will outperform those with an internal focus. AI can now analyze vast amounts of data, detecting anomalies and optimizing plans almost instantaneously.

**Generative AI in Supply Chain Management**

Generative AI, a subset of machine learning, generates outputs based on comprehensive data analysis. Unlike traditional decision-support tools, generative AI considers millions of variables to prescribe optimal decisions. Companies that adopt generative AI will gain unprecedented speed, value, and results.

In 2024, generative AI may still be viewed with caution, but solutions that demonstrate transparency and interactive decision-making will gain trust. Clients now expect AI to provide not just insights but actionable, guided workflows, eventually leading to full automation.

For more insights, visit [hsonetwork.in](https://hsonetwork.in).