J
John Iwuozor
Guest
Real-time decisioning is using data and analytics to make decisions in real time. Let’s get into the challenges and best practices you need to know.
Data is everywhere—big data, structured data, real-time data, you name it. In fact, approximately 328.77 million terabytes of data are created daily. Put into perspective, that’s equivalent to storing about 82.2 billion HD video files every single day.
Overwhelming data is constantly generated from IoT applications to mobile devices, but how do we make sense of this data? How do we leverage this opportunity to accurately analyze present information to make better decisions?
Fortunately, there’s advanced tooling that helps to extract valuable decisions from these data. The term is “real-time decisioning” and it works by receiving huge batches of live data, interpreting it and making the best decision in that context.
Today’s world requires the ability to make quick, well-informed decisions as a crucial factor for success. This will help prevent fraudulent transactions, comply with evolving regulations and result in better personalization. In this article, we’ll take a better look at relevant use cases of real-time decisioning and how Progress Corticon.js, a low-code digital decisioning platform, can help businesses make complex real-time decisions with ease.
Real-time decisioning is the process of using data and analytics to make decisions in real time. This is done via advanced algorithms and ML techniques which enable it to act within milliseconds and allow businesses to make instantaneous intelligent decisions. Talk about being able to respond quickly to changing market decisions, customer needs and personalized experiences.
Some industries have pinpointed the need to convert raw data into actionable insights immediately after collection to supply their businesses with prompt responses. This is especially important for industries where the margin between real-time and near real-time data can be a significant differentiating factor.
Real-time decisioning has many practical applications in various industries, from healthcare to finance to customer service. By analyzing data in real time:
Besides, this article presents a study that suggests that companies that prioritize real-time decision-making are more likely to thrive in today’s competitive market. That’s because they can quickly adapt to changes in customer behavior and market trends, and provide personalized experiences that meet the evolving needs of their customers.
Real-time decisioning depends on three major factors: time, data and model. For each factor, there are the corresponding challenges. Companies fail to manage the complexity of decision-making across multiple channels and touchpoints and struggle to balance the need for speed with the need for precision in decision-making. Concerns about the quality, relevance and accuracy of the involved data raise dust in different scenarios because the topic is quite subjective. Compliance with regulations and ethical considerations is also a thing.
So, how do we overcome these challenges? Here are some noteworthy practices and solutions:
Know what, when, why and how decisions must be made. This allows you to be aligned with your overall business strategy and ensure relevance in the finished process.
Data quality is a priority but this can be subjective. You need to choose the right data stream and ensure it falls in place with your objectives and goals. You need to put into consideration the accuracy, completeness and consistency of data. For example, financial industries rely on accurate data on market trends, stock prices and other financial indicators. This data must be reliable and free from error or biases. This requires a robust data management strategy that includes data cleansing, validation and integration. The right data = the right decisions = the right VALUE.
This simply means that businesses should be able to trace the decision back to the data and analytics used to make it and provide a clear explanation of how the decision was reached. This holds water in regulated industries, where transparency and accountability are really critical.
According to Gartner, operational decisions are usually structured and repetitive. These operational decisions are those that are made on a day-to-day basis to keep the business running smoothly. To make them near-real-time, businesses may need to implement new software tools, data types and process designs.
You need to optimize real-time decision-making by continuously monitoring and adjusting the rules and analytics that govern the process. By tracking the outcomes of these evaluations, you can ensure that your models are functioning correctly. You may also need to deploy workflows and track key metrics to maintain the automation process. Check out our best practices for assigning business rules to automation.
It’s not enough to follow the above-listed best practices—businesses must invest in the technology and infrastructure necessary to support real-time decisioning. Progress Corticon turns out to be an optimal digital decisioning platform that falls into this category by helping customers in creating agile and responsive business systems. This section presents some use cases of how Progress Corticon.js has been implemented to help multiple industries make better decisions with their data.
Progress Corticon.js allows financial services to identify and automate decisions, separate business rules from application code and energize core business processes. By automating operational decisions, financial services can improve performance in customer acquisition, time-to-market, time-to-quote and loan processing times. Empowering non-IT users to create, test and deploy rules in minutes for core operations, risk management, credit decisions, front office operations and ecommerce can lead to a more agile business that can move at the digital speed the marketplace demands.
Real-time decisioning using Progress Corticon.js can be a game changer for healthcare applications that contain complex rules based on regulations, new studies, protocols, and demographics. Automating business rules can lead to faster product delivery, reduced development cycles by up to 90%, and rapid scalability to accommodate growth. Key targets for automated business rules include personalizing patient plans, improving patient outcomes, reducing administrative requirements, increasing patient care quality, improving patient diagnosis accuracy and reducing healthcare costs.
Policy underwriting and claims processing involve a significant amount of decision-making, which is often done manually or programmed into apps. Changing or modifying rules can take weeks, impacting business performance. Progress Corticon.js allows subject matter experts to collaborate safely with IT specialists in business projects, automating and adapting to changing business imperatives. It can also monitor business outcomes over time and optimize underwriting rules where business performance needs improvement, manage high volume and ensure accuracy, and remove unnecessary manual steps in processes with recurring decisions to speed up processes, reduce costs, and increase customer satisfaction.
Progress Corticon can be a valuable tool for the public sector to meet the expectations of constituents while dealing with complex policies and regulations. It can speed up the implementation of legislation, regulations, rules and policies; improve the accuracy and speed of benefits eligibility and delivery; consolidate redundant tasks; and enable information-sharing across programs. By automating operational decisions and intelligent citizen interactions, Progress Corticon can help the public sector serve the needs of the public while protecting its programs from risk and fraud, oftentimes in the face of static or shrinking resources.
Progress Corticon.js can be a game-changer for the software industry, especially for companies that prioritize low-code app development. With Corticon.js, software companies can implement complex business logic rules without any coding, which can significantly reduce development time and improve productivity.
CASE STUDY: Build.One, an international leader in low-code/no-code application development, faced challenges in implementing complex UI logic without any coding. However, with Progress Corticon.js, they were able to implement even complex UI logic without any coding. They integrated Corticon.js into their core development platform, Build.One.SWAT!, which allows customers to create mission-critical business web applications with sophisticated screens based on elaborate logic to guide users through their journey and prevent them from making data entry mistakes. By adding Corticon.js, Build.One’s customers could design highly personalized user experiences without any lines of code as the company estimates that its customers can save 90% of their previous UI logic development time with Corticon.js. Read more here.
If you are looking to accelerate time to market while elevating web UI logic, Progress Corticon.js can be the best solution for you. With Corticon.js, you can implement even complex UI logic without any coding, which can significantly reduce development time and improve productivity.
With Corticon.js, developers can easily integrate business rules into their JavaScript applications, allowing for real-time decision-making. This software extends the gold standard in rules automation to the bleeding edge of innovation, allowing better decisions to be made earlier in the process. By abstracting rules from applications, domain experts can author and orchestrate rules, and Corticon.js can deploy them. Try out Corticon.js now.
Try Corticon.js
Continue reading...
Data is everywhere—big data, structured data, real-time data, you name it. In fact, approximately 328.77 million terabytes of data are created daily. Put into perspective, that’s equivalent to storing about 82.2 billion HD video files every single day.
Overwhelming data is constantly generated from IoT applications to mobile devices, but how do we make sense of this data? How do we leverage this opportunity to accurately analyze present information to make better decisions?
Fortunately, there’s advanced tooling that helps to extract valuable decisions from these data. The term is “real-time decisioning” and it works by receiving huge batches of live data, interpreting it and making the best decision in that context.
Today’s world requires the ability to make quick, well-informed decisions as a crucial factor for success. This will help prevent fraudulent transactions, comply with evolving regulations and result in better personalization. In this article, we’ll take a better look at relevant use cases of real-time decisioning and how Progress Corticon.js, a low-code digital decisioning platform, can help businesses make complex real-time decisions with ease.
What is Real-Time Decisioning?
Real-time decisioning is the process of using data and analytics to make decisions in real time. This is done via advanced algorithms and ML techniques which enable it to act within milliseconds and allow businesses to make instantaneous intelligent decisions. Talk about being able to respond quickly to changing market decisions, customer needs and personalized experiences.
Why is Real-Time Decisioning Important?
Some industries have pinpointed the need to convert raw data into actionable insights immediately after collection to supply their businesses with prompt responses. This is especially important for industries where the margin between real-time and near real-time data can be a significant differentiating factor.
Real-time decisioning has many practical applications in various industries, from healthcare to finance to customer service. By analyzing data in real time:
- Banks can detect and prevent fraud
- Doctors can easily detect and fix anomalies in patient’s health
- Retailers can offer personalized product recommendations or provide targeted marketing messages
Besides, this article presents a study that suggests that companies that prioritize real-time decision-making are more likely to thrive in today’s competitive market. That’s because they can quickly adapt to changes in customer behavior and market trends, and provide personalized experiences that meet the evolving needs of their customers.
Challenges and Best Practices for Real-Time Decisioning
Real-time decisioning depends on three major factors: time, data and model. For each factor, there are the corresponding challenges. Companies fail to manage the complexity of decision-making across multiple channels and touchpoints and struggle to balance the need for speed with the need for precision in decision-making. Concerns about the quality, relevance and accuracy of the involved data raise dust in different scenarios because the topic is quite subjective. Compliance with regulations and ethical considerations is also a thing.
So, how do we overcome these challenges? Here are some noteworthy practices and solutions:
1. Have Clear Objectives
Know what, when, why and how decisions must be made. This allows you to be aligned with your overall business strategy and ensure relevance in the finished process.
2. Choose the Right Data
Data quality is a priority but this can be subjective. You need to choose the right data stream and ensure it falls in place with your objectives and goals. You need to put into consideration the accuracy, completeness and consistency of data. For example, financial industries rely on accurate data on market trends, stock prices and other financial indicators. This data must be reliable and free from error or biases. This requires a robust data management strategy that includes data cleansing, validation and integration. The right data = the right decisions = the right VALUE.
3. Keep the Process Transparent and Auditable
This simply means that businesses should be able to trace the decision back to the data and analytics used to make it and provide a clear explanation of how the decision was reached. This holds water in regulated industries, where transparency and accountability are really critical.
4. Make Slow Operational Decisions Real-Time
According to Gartner, operational decisions are usually structured and repetitive. These operational decisions are those that are made on a day-to-day basis to keep the business running smoothly. To make them near-real-time, businesses may need to implement new software tools, data types and process designs.
5. Continuously Track and Optimize
You need to optimize real-time decision-making by continuously monitoring and adjusting the rules and analytics that govern the process. By tracking the outcomes of these evaluations, you can ensure that your models are functioning correctly. You may also need to deploy workflows and track key metrics to maintain the automation process. Check out our best practices for assigning business rules to automation.
Use Cases of Real-Time Decisioning Using Progress Corticon.js
It’s not enough to follow the above-listed best practices—businesses must invest in the technology and infrastructure necessary to support real-time decisioning. Progress Corticon turns out to be an optimal digital decisioning platform that falls into this category by helping customers in creating agile and responsive business systems. This section presents some use cases of how Progress Corticon.js has been implemented to help multiple industries make better decisions with their data.
Financial Services
Progress Corticon.js allows financial services to identify and automate decisions, separate business rules from application code and energize core business processes. By automating operational decisions, financial services can improve performance in customer acquisition, time-to-market, time-to-quote and loan processing times. Empowering non-IT users to create, test and deploy rules in minutes for core operations, risk management, credit decisions, front office operations and ecommerce can lead to a more agile business that can move at the digital speed the marketplace demands.
Healthcare
Real-time decisioning using Progress Corticon.js can be a game changer for healthcare applications that contain complex rules based on regulations, new studies, protocols, and demographics. Automating business rules can lead to faster product delivery, reduced development cycles by up to 90%, and rapid scalability to accommodate growth. Key targets for automated business rules include personalizing patient plans, improving patient outcomes, reducing administrative requirements, increasing patient care quality, improving patient diagnosis accuracy and reducing healthcare costs.
Insurance
Policy underwriting and claims processing involve a significant amount of decision-making, which is often done manually or programmed into apps. Changing or modifying rules can take weeks, impacting business performance. Progress Corticon.js allows subject matter experts to collaborate safely with IT specialists in business projects, automating and adapting to changing business imperatives. It can also monitor business outcomes over time and optimize underwriting rules where business performance needs improvement, manage high volume and ensure accuracy, and remove unnecessary manual steps in processes with recurring decisions to speed up processes, reduce costs, and increase customer satisfaction.
Public Sector
Progress Corticon can be a valuable tool for the public sector to meet the expectations of constituents while dealing with complex policies and regulations. It can speed up the implementation of legislation, regulations, rules and policies; improve the accuracy and speed of benefits eligibility and delivery; consolidate redundant tasks; and enable information-sharing across programs. By automating operational decisions and intelligent citizen interactions, Progress Corticon can help the public sector serve the needs of the public while protecting its programs from risk and fraud, oftentimes in the face of static or shrinking resources.
Software
Progress Corticon.js can be a game-changer for the software industry, especially for companies that prioritize low-code app development. With Corticon.js, software companies can implement complex business logic rules without any coding, which can significantly reduce development time and improve productivity.
CASE STUDY: Build.One, an international leader in low-code/no-code application development, faced challenges in implementing complex UI logic without any coding. However, with Progress Corticon.js, they were able to implement even complex UI logic without any coding. They integrated Corticon.js into their core development platform, Build.One.SWAT!, which allows customers to create mission-critical business web applications with sophisticated screens based on elaborate logic to guide users through their journey and prevent them from making data entry mistakes. By adding Corticon.js, Build.One’s customers could design highly personalized user experiences without any lines of code as the company estimates that its customers can save 90% of their previous UI logic development time with Corticon.js. Read more here.
If you are looking to accelerate time to market while elevating web UI logic, Progress Corticon.js can be the best solution for you. With Corticon.js, you can implement even complex UI logic without any coding, which can significantly reduce development time and improve productivity.
Concluding Thoughts
With Corticon.js, developers can easily integrate business rules into their JavaScript applications, allowing for real-time decision-making. This software extends the gold standard in rules automation to the bleeding edge of innovation, allowing better decisions to be made earlier in the process. By abstracting rules from applications, domain experts can author and orchestrate rules, and Corticon.js can deploy them. Try out Corticon.js now.
Try Corticon.js
Continue reading...