Business is about serving the needs of customers. But customer expectations are changing quickly, and most organizations are not truly aware of how fast that’s happening.
Most businesses are moving in slow motion relative to their customers. That means they miss out on opportunities to make decisions about and act on the moments that matter.
In the past, lag time was accepted. Nielsen called people on the phone to understand their TV viewing habits. Broadcast TV networks set advertising rates and advertisers gauged viewership based on Nielsen ratings. It took a long time for a legion of people to collect this data, and once they got the data, it was typically a small and outdated sample size. But this was the best available method given the technology of the time.
Today these types of approaches simply don’t work — and they don’t have to. Organizations can use modern technology to move quickly and benefit from in-the-moment opportunities. That enables them to act in real time to deliver better experiences to retain and add customers — and optimize solutions for their clients and business partners.
What Is Real Time?
The definition of “real time” depends upon the context. In the context of a video streaming service, “now” means instantaneously. If you’re serving up pixelated videos or you can’t deliver an advertisement, you can lose consumer users or advertising sponsors. Latency is also a conversion killer for websites and a costly problem for financial traders. Akamai, one of my company’s clients, reports that conversion rates drop 7% for every 100 milliseconds of added latency.
Real time can mean seconds or minutes. Thorn, another client of my company, which works to prevent child sex trafficking, processes massive amounts of web data quickly. This improves child identification and investigation time by up to 63%. Each passing minute matters and determines the likelihood of saving a child.
Speed is also key in fighting the pandemic. True Digital, also one of my company’s clients, is using real-time data to monitor human movement using anonymized cellular location information. This can help authorities prevent large gatherings that can become coronavirus hot spots.
In each of these scenarios, what is considered “real time” is dependent upon the context and the goal. But all of these scenarios define crucial moments in which having the relevant current and historical data immediately available for processing is essential.
In-The-Moment Decision-Making Requires Infrastructure Simplicity
You have to simplify to accelerate business in this way. To go faster and get finer-grained, real-time metrics, you can’t have 15 different steps in the process and 15 different types of databases and storage. That adds up to too much latency and exorbitant maintenance fees.
Instead, you need to be able to do the same things and add new business functions, with less infrastructure. This requires technology convergence.
As Andrew Pavlo of Carnegie Mellon University and Matthew Aslett of 451 Research wrote, NewSQL database management systems now converge the capabilities that in the past were implemented one at a time in separate systems. This a byproduct “of a new era where distributed computing resources are plentiful and affordable, but at the same time the demands of applications [are] much greater.”
Now you can go faster. You can make decisions and act on them in real time. You’re in the game rather than sitting on the sidelines waiting for information while competitors are acting.
Modern Businesses And Their Customers Benefit From Real-Time Data Today
FedEx founder and CEO Fred Smith said in 1979 that “the information about the package is as important as the package itself.” This highlights the power of data.
Companies like FedEx now use this power to dynamically reroute packages based on customer interactions and to optimize their routes. Real-time data allows customers to employ digital interfaces to see when and where their packages will be delivered, request that a package be sent to an alternate location and have that request honored. It’s not just FedEx that’s doing this; other companies like DHL and UPS have done dynamic rerouting for years.
This is important because people are a lot more mobile these days; customers expect businesses to be more responsive to their needs and tend to give businesses that cater to them higher customer satisfaction and Net Promoter Scores. On-time delivery helps logistics companies avoid missing service level agreements and then paying penalties.
You can’t do route optimization and dynamic rerouting if your information about the package and other relevant details is hours behind where the package actually exists. You need your digital environment to mirror what’s happening in the real world.
When you create a digital mirror of your environment, you get what is called a digital twin. As our co-founder recently explained, digital twins are often associated with industrial and heavy machinery. But organizations in many sectors are now exploring and implementing digital twins to get a 360-degree view of how their businesses operate.
This requires organizations to have converged, cloud-native, massively scalable and fast-performing infrastructure that supports artificial intelligence and machine learning models. Organizations that don’t have these capabilities will be outmaneuvered by faster companies that do have the intelligence and agility to make decisions and act in the now.
Embracing Intelligence And Agility
Understand that delivering faster data isn’t the objective. The objective is to deliver the optimal customer experience and improved operational insights. Let these two objectives be your guide — and seek ways to leverage all relevant data in the moments that matter.
Dreaming big is important. But to start, identify a small project combining current, live and real-time data with historical data for in-the-moment views and automated decision-making and trendspotting to address customer experience or operational opportunities or challenges.
Polyglot persistence provides real development advantages. But it’s not necessary to assemble multiple types of data stores to get those advantages. Choose simplicity with flexibility by searching for solutions that provide support for a spectrum of workloads, reducing cloud data infrastructure complexity.
This was previously posted on Forbes.