5 Questions for IT and Data Innovators

We speak daily with potential and existing customers who see the importance of being able to identify and act instantly on new data as it’s streaming into their organization. They understand the key is analyzing this data within the context of historical data, to take the right action at the right time.

Here are five questions I hear everyone asking themselves as they begin the journey to become a real-time business. My hope is their insight will help clarify your journey.

1. What business outcomes would we like to accelerate? What process delays are currently holding us back?
Start with your goals and KPIs. Which business processes contribute to achieving those goals and KPIs, and which can be improved? Identify the data points that provide value, as well as the gaps, points of friction, and bottlenecks that negatively impact those goals and KPIs. Reimagine the process to be simpler, easier to develop, operate, and run in real time. 

Next, decipher the impact of taking instant action vs. delayed action. For example, identifying an opportunity and sending a notification later versus taking action instantly. Then, look at the streaming data and historical data available, that may be stored across distributed systems, to support this new real-time process. 

For example, the marketing team at BNP Paribas Bank was interested in boosting loan conversion rates. They decided the right time to offer a loan was when the customer needed money—such as when they tried to withdraw cash from an ATM and realized they were out of money. The result? BNP identifies an opportunity to give a customer a loan and will act instantly to deliver a real-time personalized offer via SMS text; the bank’s conversion rates soared 400%! This ROI illustrates the transformative power of stream processing.

With streaming data and real-time stream processing capabilities, IT leaders and architects can now enable real-time initiatives that are cost-effective, drive innovation, and lead to higher customer satisfaction, growth, and significant ROI.

2. Which delayed actions create negative experiences for customers?
Many executives answer this question by analyzing customer reviews, surveys, or employee feedback. For instance, airline executives focused on boosting loyalty and revenue probably want to improve business processes so miles earned by fliers are updated in their accounts immediately—not days or weeks later. In the past, however, leaders were limited in what they could do to address those negative experiences, given their existing processes and data architecture. 

With streaming data and real-time stream processing capabilities, IT leaders and architects can now enable real-time initiatives that are cost-effective, drive innovation, and lead to higher customer satisfaction, growth, and significant ROI. What delayed action do you have that could be erased or lessened with real-time stream processing capabilities?

3. What technical challenges keep you from identifying opportunities and taking action instantly?

You’re likely storing streaming data first, then analyzing it with business analysts, and then taking action later. What is the source of that data? Can you enrich it with important contextual information that you’re storing in other systems, identify an opportunity or threat and act on it, and then store it for further analysis later? For example, can you use streaming and stored data to automate suggested selling, offers, or special discounts to specific customers? Remember, you can always send the data to downstream systems for BI analysts to analyze later.

In many cases, there’s no need to rip and replace existing data architectures. You can layer in a unified real-time data platform for stream processing.

4. What contextual data should be combined with streaming data to identify opportunities and take instant action?
It’s well-known that the value of data erodes over time. Data in motion, streaming data, or real-time data can be of enormous value if it’s enriched with contextual data immediately, not later. To learn more about this, check out this conversation with Mike Gualtieri, VP and Principal Analyst at Forrester, who also just released ​The Streaming Data Platforms Landscape, Q3 2023.

One of our automotive customers stored streaming data from the car configuration application on its website. The application allowed shoppers to customize aspects of their dream car. This data remained in shopping carts—unused. Millions of individuals also requested quotes and expressed interest in vehicles daily. These potential customers had to wait because the company couldn’t perform real-time analysis of these requests, identify opportunities, instantly respond to questions, and address needs while people were on the website. 

Then, a data innovator within the automotive company had the great idea of enriching streaming data with contextual data from existing systems to enable automated actions, such as real-time answers and personalized offers to boost engagement and increase sales. 

5.What changes need to be made to our data architecture to support new requirements?
Identify the gaps, points of friction, and points of failure in your current data architecture. In many cases, there’s no need to rip and replace existing data architectures.  You can simply layer in a unified real-time data platform for stream processing. At the same time, evaluate which data would be helpful to enrich streaming data. It may be stored in different systems. Consider bringing this valuable contextual information into a fast data store to enrich your streaming data and accelerate business outcomes, optimize costs, and reduce risk.

Stream processing capabilities can be layered into existing architectures as a modern data layer that can identify opportunities and threats in streaming data and enable instant action. 

The Revenue of Action vs. The Cost of Inaction

Our customers have each gone through a similar opportunity sizing exercise to make sure they’re getting the most value out of their data today – and are on track to make the most of it tomorrow, too. 

If you start with the premise that real-time data is the catalyst for transformational change, you’ll see the steps necessary to update your data strategy to include streaming data and build a real-time data architecture. 

Innovative companies are already moving on this path. The cost of inaction will far outweigh the investment in time, energy, and infrastructure needed to lead in the real-time economy. 

In my recent DBTA article, I shared some Hazelcast customer results, including:

• 400% increase in conversion rates for BNP Paribas, 
• over $100 million in avoided losses annually for a top credit card issuer,
• 20x faster time-to-market for deploying business-critical applications, and
• 1,000s of payments processed per second.

What could instant action do for your business?

Contact Us.