What Businesses Lose When They Waste Time

In today’s hyper-connected world, the more time you lose, the less successful your business is. And there are enormous implications for burning valuable time that directly affect a business’s bottom line.

Loss of revenue 

Whether your business is the provider or consumer of data, your revenue is affected whenever time is wasted in moving information from its source to the algorithms and systems it will drive.

For businesses that deliver data, time is everything. Customers pick them because they can deliver the most accurate, most up-to-date information available. It’s the provider’s job to get that data from point A to point B, and customers believe in timeliness and reliability. 

But it’s not just delivering the data: it’s the sophistication of the systems to enrich the information while it’s in motion. Leading providers can manipulate, filter, and act on data before it even reaches the end user, enhancing the value of information without losing time or money processing it in a central location. 

For data-driven organizations, utilizing real-time data provides an unquestionable competitive advantage and creates the opportunity to do innovative things with the data at hand. Organizations can better understand customers, detect what’s successful and not, and even use current activity to predict what’s coming next confidently.

Loss of customer engagement opportunities

Real-time data is massively valuable for customer engagement: It’s often said that to be successful, you need to engage the customer with the right message at the right time. The key to recognizing “the right time” is to tap into what your customers are doing and the actions they are taking as the action happens and extrapolate insights that drive new and exciting ways to engage. 

Take a running app, for example. When a user goes out for a run, the application collects many powerful insights into the user: geolocation data, the time of the day they normally exercise, and even how many miles they’ve put on a certain pair of shoes. Imagine if, at the very moment when the user has put 300 miles on a pair of shoes, the manufacturer or distributor could deliver an alert and deliver a compelling offer to purchase a new pair. Real-time data is the key to acquiring valuable insights, and insights are the fuel that drives innovation.

Loss of the value of the information itself 

Delivering data without extracting insights or acting on it does not fit business demand. Technologies like serverless computing and event-driven architecture help businesses go beyond simple data-driven decision-making—opening up opportunities to extract more value out of each piece of data, whether it’s manipulating the data to work with other systems, connecting the data stream to 3rd party computation offerings, or automatically triggering valuable tasks in other systems.

What is the best way to utilize the small window of time you have?

Moving from request/response architecture to real-time data streaming systems has fundamentally shifted delivery speeds and altered the value and applicability of data. There’s been an explosion of protocols (long polling, MQTT, WebSockets), frameworks (Socket.IO), and infrastructure providers (PubNub) that enable software designers to open a network connection through which data can be streamed bidirectionally, quickly and reliably, between any number of connected devices or systems. 

This real-time innovation has enabled, and thus ushered in, new types of technologies and design patterns to take advantage of the ever-shortening window. 

Functions and serverless compute 

Functions let you run and execute business logic on your data in motion. You’ve probably by now come across Functions-as-a-Service (FaaS) services, where a vendor provides a scalable ‘virtual server’ model for running your code. Whether you build your serverless Functions from scratch or go with a serverless compute vendor like AWS Lambda or PubNub’s Functions feature, the concept of executing your code without provisioning any additional servers to affect the actual computations has been a game changer. 

Serverless computing takes real-time data streaming to the next level and enables systems to do more in a shorter amount of time with the data. Beyond simply sending and receiving data or continuously pinging additional servers or external services, functions bring the business logic directly into your data streams. There are broad use cases for this: 

Manipulate the data as it is in motion: 

Filtering, augmenting, translating, enriching, and transforming data before it reaches its destination. This could be as simple as translating a chat message from English to Spanish or as robust as ingesting a massive firehose of social media data, analyzing messages for their sentiment, and categorizing each message based on the perceived emotion. 

Connect third-party services: 

Loosely coupled by nature, serverless functions allow teams to integrate third-party services and execute business logic through them without spinning up additional infrastructure. Powerful third-party services, like the cognitive/machine learning services from Google, Amazon, Microsoft, and Watson, can live in the functions - delivering the capabilities of these services all in your app with a lightweight API request. 

Big data ingestion and analysis: 

For organizations that create massive amounts of data, like an industrial IoT company with thousands of sensors in the field, serverless functions help make sense of the data and deliver rapid insights and analysis. 

Serverless computing is massively beneficial for allowing apps and organizations to deliver more value in a fraction of the time. On top of the value delivered, serverless functions reduce costs and provide a more loosely coupled architecture, making your app more flexible and opening the doors to more innovation.

Edge computing 

With the explosion of data stream-based applications (applications and experiences relying on huge amounts of data points being sent and received by devices) and the expectation of real-time experiences from end users, edge computing has grown in both adoption and importance. 

To deliver these types of applications and the experiences end users demand, traditional request/response can’t keep up. With devices and end users constantly emitting and consuming large data streams, as well as serious security considerations, edge computing provides a solution to these challenges. 

In a nutshell, edge computing is computing as close to the data source as possible. Compared to cloud computing, where all data passes through and business logic is executed at the data center level, edge computing provides a faster, more efficient way to act. 

Relying on cloud computing for processing data is simply too slow. Latency aside, the cloud simply cannot keep up with the massive data volume and velocity generated by data-intensive deployments, like large-scale chat or IoT. 

Gathering, processing, and storing data at edge devices significantly alleviates the network of potential bandwidth bottlenecks. Not every bit of data needs to be sent to the cloud, and the cloud doesn’t need to be consulted for every minor decision. 

Cloud computing shouldn’t be done away with. It and the traditional ‘data warehouse’ model are still needed in situations requiring heavy computing and storage resources, such as big data analytics on historical data. However, moving data processing and serverless functions execution to the edge greatly increases the speed at which organizations can deliver insights and experiences to end users.

If you’re struggling to extend your application to mobile and IoT devices without breaking your security models, consider using an edge messaging network. The PubNub Edge Messaging Network extends event-driven architectures through firewalls worldwide. As applications deploy across data centers and mobile and IoT devices are deployed globally, PubNub provides a secure, enterprise-grade way to connect, communicate, and control services and devices using design patterns similar to your existing “behind the firewall” message bus. 

Event-driven architecture 

Both edge computing and serverless functions are part of a larger movement of how we architect software—event-driven architecture. The backbone of event-driven architecture is loosely coupled, meaning the app is highly distributed with fewer dependencies, making it incredibly flexible and dynamic. 

Event-driven applications are built for responsiveness, creating and responding to internal and external events in near real-time. This allows the app to proactively respond to business activities - delivering immediate information dissemination and business logic execution. 

Because it’s loosely coupled by design, event-driven architecture is optimal for integrating third-party services and building apps of powerful and easy-to-manage microservices. With event-driven, it’s easier to innovate with new features and capabilities while providing speed and accuracy for data processing and business logic execution. 

Time is of the essence

Apps are faster than ever, businesses are getting smarter, and organizations continue to innovate. The common theme among the reasons why, in one way or another, is based on how they manage time and data.