What If Real-Time Wasn’t in Real Time?

What if there was a delay between a racing driver’s steering wheel and the desired change in direction of the vehicle travelling at 350 km/h? The results would be devastating. What about a delay between a pilot’s stick input and the response from the aircraft’s flight control system? The ramifications could be fatal for all onboard the flight and, potentially, for those on the ground as well. Or a delay in the quality detection of expensive, raw materials before they embark on the next stage for irreversible processing? This would be extremely costly and disruptive to everyday operations and production.

The impact of “lag” (or maybe latency or delay) in real-time, mission-critical systems is clear to see in these three examples, and there are many other cases where response lag could have an immeasurably disastrous and costly impact, for example:

• Nuclear reactor control systems
• Air traffic control systems
• Healthcare systems
• Transport signalling systems
• Space exploration

But the above industries have billion-dollar budgets and huge amounts of resources supporting them around the clock to ensure that lag never happens.

What about examples where the outcome or impact may not be as severe, but nonetheless critical to those affected, like in modern business environments?

Consider an e-commerce business. If you had lag in your website response time, that would create frustration with your customer base and cause sales to drop. In fact, one major North American fashion retailer experienced this very situation – their online sales fell by 11 percent when the response to their website slowed by just half a second. That resulted in tens of millions of dollars being lost in that financial year. If you are a financial services company and your fraud detection system couldn’t accurately detect fraud while a payment was being made, what would happen? Denying customer purchases due to inadequate fraud systems could result in customer churn as well as a negative brand association. And failing to detect fraudulent payments (false negatives) could result in significant financial loss and penalties. Neither is a very good outcome.

Now, to avoid any confusion, let’s be clear about what real-time means. 

Real-time means:

“Acting on information in the moment. While, when, during and before an event, not after”.

Let’s look at some examples:

• When a customer is shopping online – offering real-time recommendations and personalisation
• During a fraudulent event – making sure you make the right call.
• Before a process breaks something in an industrial machine
• When a patient needs immediate attention

Nowadays, the term “real-time” has been adopted by leading businesses. They know they can gain competitive advantage, dominate the market, and become much more agile and efficient if they build applications that are responsive to their real-time, in other words, their SLA. Like automatically upselling to a customer while they’re purchasing online, or identifying a fraudulent transaction as it begins processing, for example. 

So, it’s clear that you need real-time action in an ever-changing, competitive landscape. But you need applications that can be built quickly and easily to provide continuous and consistent real-time capabilities and always be available. Many platforms claim to deliver real-time, but the reality is that they’re only retrieving the data very quickly. But data retrieval happens well after the event, along with the data extraction, transformation, loading, aggregation, and analytics. And even after that there may be a dependency on human action, which is a significant source of delay. So, the value of that data diminishes since the opportunity is missed. Collecting data in real-time is one thing, while acting on it is another. Knowing what needs to be done is a good step but automated action (i.e., real-time responsiveness) is needed to deliver the desired positive outcome. True real-time applications involve continuously ingesting, analysing, processing, and then acting on the data “in-flow” outside of a database or any other service so that the maximum value can be gained – in the moment, while the event is taking place.

One additional, crucial component needed to support effective real-time action is reference data. This is external data that, when merged in, enriches the freshly created, in-flow data to add context, meaning, truth and credibility. We all know that the best way to make important decisions is to have all the supporting information to hand. Context is everything. Being able to answer the who, what, where, why and when, as well as other questions, offers the best chance of making the best decision. 

So, the ideal platform will allow you to build applications that can ingest multiple streams of continuous, fast flowing data, analyse it, merge it with reference data and give you the ability to act on data automatically – all in real-time.

The Hazelcast Effect

The Hazelcast Platform delivers true real-time capabilities that drives greater innovation. We combine a high-performance stream processing engine with low-latency storage and machine learning inference capabilities. This enables you to swiftly and easily build high-performance, intelligent, business applications that can ingest huge volumes of perpetually flowing data and deliver valuable real-time insights and action for any use case. Being able to process more quality data can yield more accurate, context-rich insights, removing the need for guesswork and assumptions when acting on data – all within your business SLAs, in real-time. With vast quantities of data from various data sources, you can build logic to determine patterns by correlating multiple streams of changing event data based on conditions common to both streams of events. 

You can deploy anywhere – in any cloud, on-premises, or hybrid – and deliver a fully-managed service for those not wanting to manage infrastructure operations. You also get  connectivity to any data source and destination, benefiting omnichannel partnerships by providing a seamless experience across the divide.

Real-Time Use Cases 

Here’s a list of just a few use cases that benefit from real-time responses

• Personalized recommendations in e-commerce
• Payment processing
• Fraud detection
• Industrial operations optimisation
• Distracted driver analysis
• Predictive maintenance
• Back-office trade monitoring
• Counterparty risk calculations
• Credit value adjustments

Real-Time Case Studies

Real-time is about meeting SLAs with narrow time windows. That means you can get:

• Accurate fraud detection within milliseconds to avoid millions of dollars of fraud loss
• Real-time offers that dramatically improve conversions that add revenue
• Creating big-picture views of your business’s operations to improve operational efficiency and reduce costs
• Minimize wait times to boost customer acquisition retention and reduce churn

Real-time is here. Now. In fact, very soon, real-time action will be such a standard expectation in our lives that, without it, our lives will be dramatically inconvenienced.