Transforming The Supply Chain With Data Analytics And Intelligence

Supply chain transformation happens by unlocking the value of your analytics with processes, technology and experience.

This post was originally printed on Forbes.com

Data may not be considered a revolutionary concept, but today, it is considered a fundamental component of digital transformation. Data is the key to achieving breakthroughs in supply chain management that the industry once considered impossible. Now, with the advent of the metaverse, the lines between the digital and physical worlds continue to blur. To compose a supply chain agile enough and prepared for such a future world, organizations must invest in effective data analytics to mine data for valuable, proactive insights and accelerate intelligent decision-making.

As we come upon the two-year mark since the onset of the pandemic, organizations are keen to digitally transform and adopt intelligent supply chain management. On top of pandemic disruptions, organizations across sectors are also contending with growing labor shortages, supply shortages and rising costs. As disruption has become an everyday occurrence to supply chains, chief supply chain officers (CSCOs) are under growing pressure to capture real-time data, analyze it and respond quickly to mitigate risk. Supply chains must adapt for continued agility, resilience and transparency.

In their “2021 Future of Supply Chain Survey,” Gartner discovered that 43% of enterprises will continue to digitalize and integrate innovative technology into enterprise-wide systems. This means that in the coming year, the ability to augment operations and decision-making with data analytics will prove to be a transformative and highly-favored capability.

Digital Reinvention Is Today’s Necessity

While transformation is an ambitious undertaking, the benefits go well beyond improving supply chain performance and profitability. A late 2020 Gartner survey showed that nearly 70% of companies surveyed accelerated their digital road maps during the pandemic. That being said, digital reinvention in the supply chain is now a necessity.

A myriad of use cases for supply chain analytics exist — and the number will only continue to grow as forward-thinking leaders embrace the opportunity of human and machine collaboration. Consistently ranked as one of the top five corporate supply chains, Schneider Electric leverages a supply chain data platform within their control tower to integrate internal data with external data from partner ecosystems in real time. By unlocking newfound value in analytics, Schneider Electric achieves full visibility of their end-to-end supply chain. Ultimately, this allows the company to boost agility, effectively manage supplier relations, extend visibility and support intelligent decision-making.

The Intelligent Building Blocks

Data-based decisions require a fundamental change in how supply chain organizations think about data. Implementing data analytics is not soley a matter of tacking on new technologies, but rather a series of digital initiatives to capture the full value of data analytics and intelligence. To make this shift, start by looking at the following:

• Link The Business Strategy: Linking business priorities to investments with a transformation road map — not IT stack improvements — helps drive successful transformation across the enterprise.

• An Agile Method: A complete digital transformation is a multi-year project, making an iterative, agile approach the best method for success. With quick wins and a clearly defined strategy, organizations can minimize future losses and demonstrate positive ROI.

• Implementation And Integration: An integrated, holistic approach can address the opportunities and constraints of all stakeholders, from procurement to sales. Data intelligence drives integration across once-siloed systems, with added workflows helping turn insights into actions.

• A Partner Ecosystem: Participating in an ecosystem is crucial to mitigating risk. Supply chain mapping across stakeholders improves internal and external collaboration to benefit customers and enhance end-to-end visibility. In conjunction with data-powered insights, operations can better predict demand and cognitively source needed supplies.

• Embrace The Metaverse: Delivering predictive insights and fostering intelligence across supply chain networks will be compounded exponentially with the introduction of the metaverse. Simulating real-world models with synthetic data, IoT device data and more will prove to reduce development times and risk, achieve higher operational efficiency and improve resilience.

Where Do We Go From Here?

Supply chain transformation happens by unlocking the value of your analytics with processes, technology and experience. A lack of capabilities and a structured approach is holding many companies back. In the end, transformation is not immediate; it’s rather a proactive journey. In due time, harmonizing analytics can put organizations on a path to intelligent supply chain management and the ability to compete with organizations that are setting the bar.

At the end of the day, building a future-ready supply chain is not immediate, but a proactive journey toward the benefits digitization provides. In due time, organizations that commit to digital transformation with a strategic implementation plan across their organizations, especially in the supply chain, will find success in a new age.