Supply chain disruption to affect holidays, but analytics can help

Analytics an answer to disruption

The COVID-19 pandemic has played a significant role in the current supply chain disruption, but it's not the only cause, according to Simon Ellis, practice director at IDC.

Simon Ellis

There have been many smaller disruptions, such as climate-related events or the Suez Canal obstruction, that hit at an unprecedented pace, he said. Taken together, they have overwhelmed the global supply chain and exposed shortcomings in business operations models.

"The pandemic ended up being an inflection point for supply chains, in moving from supply chains that were largely resource-unconstrained to supply chains that are now very much resource-constrained," Ellis said. "Moving forward, data analytics and decision-making capabilities, to the degree that they can allow companies to make faster decisions, are going to actually play really well in a resource-constrained supply chain."

Akhilesh Ayer

Companies are facing a challenging environment today, according to Akhilesh Ayer, executive vice president and head of research and analytics at WNS Global Services.

WNS is a business process management company based in Mumbai, India, that runs back office and middle office operations for retail, manufacturing, consumer packaged goods and healthcare industries, among others around the world.

Today, companies are facing global competition and diverse customer preferences and expectations, Ayer said. They have to operate in an almost made-to-order fulfillment model and must either react to product demand or risk losing the sale to another company.

"If you don't react properly and fulfill the sale, there's an extremely high cost for inventory and other things," he said. "Analytics is one of the ways you can get a good assessment of the demand. If you don't have the demand planning aspect nailed, you will end up in trouble."

Real-time analytics and the road ahead

Data-driven demand forecasting can use new data sources, such as point-of-sale (POS) and social media data, to generate flexible forecasts on a more frequent basis, even daily, than traditional monthly forecasts, Ayer explained. Organizations should also conduct concurrent rather than sequential forecasts where data is interdependent and flows across a web of systems rather than in a single, hierarchical direction.

Analytics is one of the ways you can get a good assessment of the demand. If you don't have the demand planning aspect nailed, you will end up in trouble.

"If you're able to address the demand spikes [faster], that paves the way for concurrent planning solutions, which can enable real-time optimization for manufacturers," he said.

Analytics can also work on the supply side, helping companies find optimal locations for distribution centers, determine proper stock levels and make sure that manufacturers get the right signals from suppliers, according to Ayer.

"Concurrent planning that uses analytics helps optimize the supply chain and allows you to be more responsive and faster when changes happen," he said.

Organizations can be more confident in concurrent planning because it's based on real-time data and is not dependent on traditional planning models that supply chain planners have long relied on, Ayer said.

Poornima Ramaswamy

Figuring out how to make faster and more flexible decisions can dull the unpredictability brought by the last few years, according to Poornima Ramaswamy, executive vice president of solutions and partners at Qlik, a business intelligence (BI) vendor.

"Organizations that used to depend on models that were relying on data that was maybe 15 days old, a month old, or even a day old, can no longer rely on that model for insights," Ramaswamy said. "But there's an increasing emphasis on real-time data because the situational awareness that you need is becoming even more critical to be able to make decisions in the moment with data that's very recent and fresh."

Data analytics and BI are useful for understanding a firm's immediate needs in the supply chain. But they can also help predict whether a shortage or another supply chain issue will have secondary or tertiary impacts on the business, she explained. For example, an event like the shortage of computer chips may affect the automobile industry directly but can affect other industries months later.

"You can't do that with just experience and gut feel; you need data for it, and you need real-time data to be able to understand all of those correlations and then figure out whether the correlation leads to causation or not," Ramaswamy said.

Cloud apps more attainable and affordable

There's a wealth of cloud SaaS analytics tools and resources available, including applications from SAP, Oracle, Blue Yonder, Manhattan Associates, Kinaxis, Birst, Qlik and others that provide a variety of supply chain analytics.  

These applications are easy to attain and affordable, according to Gardner.

"You can spin up a cloud resource and spin it down just as easily, and you can retain the knowledge and data without necessarily having to make a leap of an infrastructure investment by taking advantage of SaaS, cloud and analytics-as-a-service offerings," he said.

It may appear that the time to resolve supply chain issues is running out before the holidays arrive, but Ramaswamy said there's still time to dig into the data and use it to provide guidance. Seasonal pop-up stores, for example, can still try to figure out what stock works best for certain demographics and locations.

"It's never too late to get started with data and insights," she said. "It sets the foundation whenever you get started, and it helps you in responding to the next event. You can apply those insights in a smart way to get short-term benefits while setting the foundations for the long term."

Making better use of data analytics enables organizations to be nimbler and more flexible, IDC's Ellis said. Companies that take advantage of the information will be able to more quickly understand alternatives when supply chains are disrupted, but they may not be much help in solving the immediate supply chain disruption, a situation analytics alone can't solve.

"Data analytics, machine learning, AI -- all the decision-making automation technologies that we have are really important for companies moving forward," he said. "I'm just not sure how much those can really help them in the here and now."

While the pandemic continues to strain global supply chain operations, companies should see the disruption as an opportunity rather than as threat, Gardner said.

"This is a time for people to try to get competitive advantage from more data services. You don't have time to do an 18-month ERP rehaul; this is crisis mode and needs to happen quickly, which is why the cloud is an indispensable IT resource in a present and post-COVID world."

Jim O'Donnell is a TechTarget news writer who covers ERP and other enterprise applications for SearchSAP and SearchERP.