With experts predicting that global supply chain disruptions will get worse before they get better, organizations are relying on their data teams to enable faster decision making and rapid response-to-market changes. Businesses need the insights to detect and react to challenges in real time so they can improve production planning, better manage inventory, and track the movement of goods more efficiently. They also need to ensure network reliability and seamless support for customers dealing with the frustrations of stock shortages and delivery delays.
But many organizations are struggling to meet the moment because they lack the infrastructure to keep pace with the demands of managing complex, ever-changing data.
Data ages quickly. Supply chain leaders across all industries are striving for real-time services to improve operations, delight customers, and gain a competitive edge. Yet, most enterprises still rely on a message broker (or log aggregator) to ingest their data into databases, data lakes, or log managers, then perform batch processing to gain analytical insights. The database/batch/bolt-on processing approach is just too slow for many of the time critical decisions facing today’s organizations.
A common process that causes supply chains to fall behind their data is “Periodic Lookup,” in which data is streamed to a data store as quickly as possible to be then queried for insights at recurring intervals. But how often should you query? Every minute? Every hour? Also, as data accumulates, how much time does it take for the query to return?
Batch processing is far too slow for organizations that are striving to meet customer expectations for frictionless experiences. The attention span of your average customer is measured in low digit seconds, and even a minute of network downtime can be disastrous. Gartner analyst Andrew Lerner estimates that each minute of downtime costs organizations about $5,600. Time and delays processing queries grows exponentially as the volume of data increases.
In today’s data-driven organizations, where time-to-value is measured in milliseconds rather than hours, Continuous Delivery is the best approach. With Continuous Delivery, insights are harvested in real time, while being streamed from users and services in the network. Continuous Delivery enables faster business decisions and better brand experiences.
A Forrester Research report recently mentioned in Forbes reveals that 90% of enterprise leaders understand the importance of real-time insights, and 84% think that being able to execute real-time course corrections is vital to the long-term success of their organizations. We see this with giants like Amazon, Netflix, Google, and Alibaba, which are well-known for maintaining their competitive advantage by reacting in real time.
Real-time data opens the door for CDOs to drive innovation and turn data into valuable insights that result in actionable business decisions. But the vast majority of companies struggle to roll out real-time services. Why? The root cause is a lack of intelligent infrastructure. Real-time services and insights require a deep stack of intelligent tools and services that need significant time, skill, and cost to build, deploy and operate.
One solution is to implement a cloud-native continuous intelligence platform. This type of platform is scalable, easily integrates with existing systems and tools, and enables organizations to detect, react, and respond to meaningful events in milliseconds, rather than hours, days or weeks – and it doesn’t require an infrastructure overhaul! Data leaders can link their data sources, compose intelligent pipelines in minutes and dispatch actionable events to all relevant stakeholders.
Continuous intelligence helps balance organizational data, deliver real-time event correlation and accelerate business actions by improving collaboration and efficiency across teams. It helps data leaders stay on top of market and competitor trends, and facilitates smarter, faster decisions by alerting stakeholders of unusual events and delays in the supply chain with real-time data to support reactions.
With a continuous intelligence platform, company performance metrics can be delivered in real time and customer churn can be predicted. AI chatbots can provide 24-7 customer support and push out relevant “make-good” offers to mitigate frustrations. Organizations can adjust supply chains in seconds to react to demand fluctuations; forecast logistics challenges; produce audit decisions; identify root cause; remediate faulty operations; and, ultimately, speed the way products and services move across the globe to consumers.
Now is the time for organizations to lead with their data, and cloud-based, continuous intelligence makes it possible to take action.