Written by Jonny Steiner

Online check-in might be one of the best innovations created in recent years. No one wants to head to the airport with any uncertainty surrounding their travel plans. Not only that, but they want to avoid long lines at all costs, and this is one simple way to accomplish that. It is perfect.

Except when it isn’t.

When a person waits for confirmation that they checked in successfully and doesn’t retrieve it, or the transaction times out, panic starts. Those rides to the airport are tense at best. Airlines are familiar with these scenarios; they can understand a person’s agony by having a defect potentially ground their travel plans before they ever leave the ground.

Customer centricity is all-encompassing these days, but these issues do not only affect travelers. Every second counts and passengers stuck with buggy app experiences lead to lost revenue. This is an unacceptable situation for both airlines and their passengers.

Through this, a powerful new tool is emerging. Predictive analytics are making it possible to utilize the vast amounts of data airlines generate to predict risk and uncover defects before they become a larger problem. Take, for example, ticketing systems that manage millions of bookings or flight operations software that ensures flights are properly staffed; even maintenance applications are essential to keep planes in the sky. As customers expect more features and development times to shrink, eliminating delays, quality issues, and cost overruns is more important than ever.

Software Delivery is Sometimes Turbulent

Software delivery challenges lead to choppy skies when it comes to software delivery. Delayed updates can ruin schedules, while inferior quality usually comes with security risks. Embracing efficient and robust capabilities is necessary to smooth out these issues. Otherwise, one of these challenges might make your organization bogged down.

  • Delays and Volatility: It is one thing to be stuck in an airport due to weather or unforeseen circumstances. However, getting stuck because of a software delay is unacceptable. A software update to an airline application can ruin schedules, causing delays, cancellations, and missed connections. This domino effect can ruin passengers’ short-term travel plans and damage an airline’s customer satisfaction and reputation. Delays requiring re-routing flights or reimbursing passengers can also cause substantial financial loss.
  • Poor Quality: Airlines operate in a highly regulated industry. Poor quality web and mobile applications are unconscionable. If a system crashes due to defects, it can ground an entire fleet, which is a logistical nightmare. If an app is not secure, a potential cyberattack can compromise passenger data and even jeopardize flight control systems. At a certain point, it becomes less about revenue and more about the safety of passengers and crew members.
  • General Chaos: Development costs can rise when the SDLC is rife with inefficient processes. Delays, rework, and the need for comprehensive testing are all factors in this. This is even more so when dealing with outdated software that needs more maintenance. The cost of these disruptions can be financial, of course, but they can also lead to service disruptions, which also have a financial number to them but take their toll on a business in other ways. Ultimately, streamlining the software delivery process is necessary to avoid these pitfalls.

Taking Control of Your Data

Organizations need a single pane of glass that gives them dynamic views across the SDLC toolchain. This helps any member from the individual/team view all the way to portfolio-level executive summaries.

An enterprise-grade and AI-powered cloud-based analytics solution helps organizations connect thousands of points to raise SDLC visibility. It will help align organizational tech functions with urgent business-critical needs.

Analytics tools like Digital.ai’s Intelligence solution automate data collection modeling and analysis from multiple sources and present the information in easy-to-read dashboards. Hundreds of analytics are available out of the box, and they correlate data from the solution and other vendor tools. The tool must also be scalable and flexible, allowing enterprises to expand to non-technical users and giving leaders and business users consistency in their decision-making.

Adding AI and machine learning algorithms can lessen manual work as AI enhances decision-making. These models will also do the grunt work, like finding connections and patterns in data that would take manual analytics teams hundreds of hours to check out and assemble. It enables software delivery teams to do more faster while reducing risk through the development process.

Furthermore, the Digital.ai Intelligence solution applies AI and ML algorithms to data sets to help teams assess alternatives, manage tradeoffs, and make data-driven decisions. The solution draws data from different sources, such as planning governance, development, and security, and Ops disseminates it in dynamic predictive intelligence dashboards.

These dashboards are divided into four different packages:

  • Flow Acceleration: Helps Agile DevSecOps teams take a more predictive approach to their software delivery.
  • Change Risk Prediction: Boosts UX with the ability to predict potential software change failures and proactively mitigate risk.
  • Quality Improvement: Predicts and eliminates defect leakage before it impacts business outcomes.
  • Service Management Process Optimization: Accelerates IT service delivery to reduce service disruptions and deliver value.

These dashboards will give airlines numerous advantages but can also leave some IT or business leaders indecisive about where to start. We respect a healthy dose of hesitation as these solutions and packages must be chosen and enabled with the proper use cases in mind.

Smooth Landings Abound

AI-powered predictive analytics bring peace of mind to the software delivery process. The days of missed release dates and panicked defect resolution are gone as Flow Acceleration guides DevSecOps teams with insights, ensuring releases are on time. Change Risk Prediction then works as a radar scanning code changes for issues and enables teams to mitigate them proactively. Defects will no longer impact operations as Quality Improvement inspects and unearths defects before they can cause any real damage. Processes will also become more powerful with Service Management Process Optimization streamlining service delivery.

It is not a dream either. Airlines worldwide are starting to see the benefits that AI can deliver in the form of cost-saving, efficiency, and enhanced safety and satisfaction. The future is brighter and smarter, and as AI and ML evolve, we are going to see:

  • More Personal Experiences: Travel will become a bespoke experience, with each aspect of the journey tailored to the passenger.
  • Predictive Maintenance: Anticipating and addressing web and mobile app issues before they arise will minimize downtime and keep applications stress-free.
  • Dynamic Allocation: Real-time data will help optimize resources to ensure a smooth operating app.

Surely That’s Not All

Delivering airline web and mobile apps is becoming less turbulent. Using AI-powered predictive insights, airlines can ensure a flawless experience for crew and passengers.

While we have explored the challenges inherent in delivering software with inefficient and outdated processes, the potential of AI-powered analytics overcomes that. Airlines must take control of their data with tools like Digital.ai Intelligence. It brings visibility, proactiveness, and preemption to the software delivery process and presents that data in user-friendly dashboards.

This is still the beginning as we see the future getting more precise and personalized. It emphasizes the need to embrace emerging technologies to help improve web and mobile app delivery. The power of AI and predictive analytics will help any airline fly toward a more profitable and prosperous future.


To learn more about the benefits of AI coding tools, watch the webinar “How to Make AI-Generated Code Secure, Private and Compliant.

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