How the Supply Chain Can Get its Resiliency Back

The pandemic put an unprecedented strain on the supply chain, revealing the need for new technologies and strategies to overcome bottlenecks.

Brian Wallace of WebPro News explores why decision-makers desperately need NLG-powered augmented analytics

Business Intelligence: Better Supply Chain Resiliency is Found in The Data Story

Historically, data initiatives falter because of the massive number of spreadsheets and reports data scientists must read through and decipher before presenting actionable takeaways. Without access to real-time, actionable intelligence, decision-makers are stuck waiting for analysts to explain their findings.

Bottlenecks like this hinder agility, making it impossible to adapt to unforeseen events in a timely manner, sacrificing productivity and efficiency.

In hybrid work environments, stakeholders in disparate locations need self-service access to analytics to facilitate the kind of quick problem-solving customers demand, especially when they’re waiting for life-saving medications and other high-priority shipments.

 Business intelligence (BI) dashboards, accessible as-a-service, are quickly becoming the go-to tools for enterprises that count on real-time data intelligence for survival.

Pharma manufacturers, logistics and distribution companies are fortifying their supply chains by augmenting BI dashboards with artificial intelligence like natural language generation (NLG). NLG technology augments data visualizations by “narrating” all underlying data in BI dashboards.

Companies like Arria NLG embed no-code NLG plug-ins into BI dashboards, accelerating data understanding and informed decision-making.

According to Gartner, 90% of the world’s top 500 companies will have converged analytics governance into broader data and analytics governance initiatives by 2023. Likewise, by 2025, data stories will be the most widespread way of consuming analytics, and 75 percent of stories will be automatically generated using augmented analytics techniques.

Analytics presented in everyday vernacular extend data understanding across all lines of business. This not only gives supply chain and logistics companies a better understanding of their data, but it also makes actionable insights available more quickly to a broader range of decision-makers, not just the data scientists.

Data storytelling communicates real-time insights in plain English to distribution and fulfillment managers into daily loads against capacity commitments, for example, exposing areas in which demand consistently outpace the committed capacity. In addition, the democratization of data enables companies to make faster, better-informed decisions and know what’s happening, what may be coming, and what to do next.

Cloud-based, self-service analytics also represent an important milestone in AI adoption, with data-driven solutions at the center.

As we saw in the early stages of COVID-19 vaccinations, manufacturers and treatment centers were ill-prepared to manage the flood of people seeking vaccinations. Leadership teams need real-time visibility of operations to align production sites, distribution centers and material flows.

Transparency is the key to accounting for unexpected events that could affect supply and demand and lead to drug shortages. To move quickly from insight to action, pharma supply chains (continues at WebProNews)