Now is Time to Double Down on Analytics Investments

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In these COVID-19 days, I read the news obsessively. And I am sure I am not alone. I check news sites. I get notifications of headlines. I follow Twitter feeds. I read editorials. I listen to podcasts. I’m always looking for some new, hidden insight that I might have missed the last time I checked.

The more data available, the more tempting to try — and the harder it becomes — to make sense of such a major disruptive event. It’s exhausting.

Supply chain organizations face the same dilemma as we do in our daily life. They are constantly scouring for more data — publicly available data about the outbreak, changing economic indicators, enterprise data about their own supply chain performance, trading partner data. They are challenged to make sense of it all. They must not just make sense of the immediate impact of the event, but the long-term implications it will have on society, global economies and our supply chains.

I used an online grocery delivery service for the first time four weeks ago. I used to enjoy going to the grocery store multiple times a week, getting what my family needs for a few days at a time. Now, my shopping habits have changed significantly. I’m making less frequent orders, buying fewer perishable items and trying replacement items for out-of-stock first choices.

How will all these micro changes in family and individual buying and consuming habits add up and shape our supply chains? Ultimately, there is no clear answer. Countless interdependencies and unknowns will shape the future. But with careful analysis, leading organizations still plan effectively for the future. They can first sense and respond to disruptive events in the short-term, recover in the mid-term and design and position for long-term patterns. They do so with a comprehensive portfolio of analytics competencies. These include:

  • Real-time Analytics to Track Unfolding Disruption — Supply chain organizations can leverage publicly available data to track how disruptive events unfold. For example, Johns Hopkins Coronavirus Resource Center data offers up-to-the-minute updates of coronavirus cases and deaths. Supply chain organizations rely on this information to start gauging the impact of the pandemic on its employees, suppliers, trading partners and locations.
  • Visualization to Map Your Supply Chain Against the Disruption — Visualization analytics help organizations gauge the impact of disruptions on the supply chain. This is especially critical for companies with global, complex supply chains with thousands of suppliers for millions of parts and components. Overlaying the span of the disruptive event onto locations, multiple tiers of suppliers and customers can highlight supply chain vulnerabilities; critical fail points risk exposure.
  • Machine Learning and AI to Triage the Supply Chain in the Near Term — Combining machine learning and artificial intelligence allows organizations to track unfolding events and take quick actions to minimize the immediate impact on their supply chains. For example, a consumer products manufacturer can use machine learning algorithm sense changes in demand patterns and autonomously reallocate available supply to avoid a service disruption to a key customer.
  • Predictive Analytics and Simulation to Gauge Likely Future Scenarios — Once immediate actions are taken to dampen the short-term impact of the disruptions, supply chain organizations turn their attention to understanding short-, mid- and long-term scenarios to predict the impact of the disruption on their business. For example, due to a port shutdown from a labor strike, a high-tech manufacturer can use predictive analytics and simulation to analyze the likelihood of port strikes and simulate their potential impact on their ability to fulfill customer demand.
  • Scenario Modeling and Prescriptive Analytics to Revise Supply Chain Policies — Using optimization, companies can evaluate different supply chain policies, balancing the trade-offs of managing a lean supply chain while building a level of resilience that allows them to quickly recovery from or altogether avoid a disruption. For example, companies may opt to carry higher levels of inventory to build more resiliency in the supply chain.
  • Long-range Forecasting and Optimization to Redesign Supply Chains For New Business Reality —Using long-range forecasting, organizations can predict the long-term impact of disruptions on their business under different scenario conditions. They can leverage optimization modeling to increase supply chain resiliency. This was in play in 2019, when China-U.S. tariff wars prompted many organizations to evaluate shifting manufacturing and production capacities from China to Vietnam. Modeling their network, the objective of additional network resilience and agility was considered against the reality of additional costs incurred to achieve them.

In summary, now is the time to invest in analytics. In this age of highly complex supply chains, most companies agree that analytics is a must have. The COVID-19 pandemic underscores the need for a robust analytics foundation. Without this foundation, companies will likely be incapable of making sense of available data to monitor unfolding events. More critically, without analytics, companies will fail to gauge the impact of a major disruptive event on their mid-term supply chain policies, and long-term growth and viability.

Noha Tohamy,
Distinguished VP Analyst,
Gartner Supply Chain
[email protected]

 

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