The pandemic put an unprecedented strain on the supply chain, revealing the need for new technologies and strategies to overcome bottlenecks.
Shipping delays and material shortages continue making headlines as manufacturers worldwide struggle to meet consumer demand for everything from auto parts to pharmaceuticals.
COVID-19 exposed a glaring lack of agility in supply chains which, if left unchecked, will both sabotage the economic recovery and put lives in danger.
Before 2020, many people would have described US supply chains as resilient. However, the past 18 months added a less desirable set of adjectives to the list, such as brittle, inelastic, fragile, and vulnerable. While the need for critical care medications surge, manufacturers lack the necessary insights to respond to site closures and impaired transportation routes that immobilize supply chains.
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 – from manufacturer to distributors and delivery – must have ready-access to the same real-time, actionable intelligence.
Augmented analytics provide the answers to pivot without sacrificing productivity. Such adaptability and flexibility are the cornerstones of agility and supply chain resilience.
According to Bain, Pharma companies that integrate flexibility and redundancy into the entire value chain, and that improve visibility, will be best positioned to predict chain disruptions and respond to them rapidly. Resilient supply chains bolster problem-solving capabilities throughout their organization and at manufacturing sites, empowering local organizations to make decisions that prevent disruptions in business continuity.
Simply put, the sooner they can alert carriers to their need for more capacity, the better they can fill the gap.
Supply chain resilience will be vital to navigating an increasingly turbulent market over the coming decade. Augmented analytics, which combines business intelligence and natural language AI, empower supply chains with data-driven, actionable intelligence to prevent manufacturing and shipping delays, which can have life and death implications.
Supply chain and logistics companies don’t need to collect any more data to achieve better resiliency. They just need a way to more quickly extract, process and communicate the insights from their data so they can respond faster.
Business intelligence and augmented analytics can make that goal a reality.