Reputational Risk: How AI Helps Mitigate Damage to Your Brand

CEO

“It takes 20 years to build a reputation and five minutes to ruin it.” – Warren Buffett

Remaining competitive in your industry is challenging with a tarnished reputation. In today’s news cycle, reporting on an organization’s downward reputational spiral can be difficult to watch — especially when that impairment is the result of application downtime on the mainframe due to buggy software. 

Fortunately, the power of artificial intelligence is now being leveraged to reduce risk and improve developer productivity.

Minimize the Impact of Application Downtime on the Mainframe

Despite many experts believing mainframes will become obsolete in our ever-evolving world of technology, mainframe systems continue to be the core of many businesses, including 71% of the Fortune 500 and 92% or more of the world’s largest 100 banks, 10 largest insurance companies, and the U.S.’s 25 largest retailers

But when software running on a mainframe crashes or behaves in unintended ways, it can cost you more than just money. Most software crashes are the result of a bug, but since the original bug can be far removed from the code that actually triggered the crash, getting to the bottom of an issue can be a time-consuming endeavor — and that’s when your reputation can take a hit. If your mission-critical applications continuously experience downtime or crash because they are not well maintained, you’re likely to lose money, social capital and/or your market share. 

A 2019 IBM report revealed that unplanned downtime costs 35% more per minute than planned downtime, regardless of whether the downtime was caused by a bug in your application or hardware/operating environment issues. Consequently, reacting to an unexpected application crash can result in the loss of an incredible amount of time, employee productivity and money. Even worse, 41% of IT leaders surveyed indicated that the costliest aspect of downtime is its negative impact on corporate reputation. 

Why Code Maintenance Remains a Challenge

Despite powering many of our most trusted institutions, applications running on the mainframe frequently struggle to evolve fast enough to support your organization’s evolving demands. Complicating the issue, the expert developers who created and maintained your applications are retiring or moving on without a supporting workforce to replace them, creating a knowledge gap. 

When those experienced developers depart, the specialized industry and organizational domain knowledge enabling them to efficiently and effectively maintain and support your critical and complex mainframe applications walked out the door with them. Consequently, there is often a hesitation to fire or let these employees go — even if they have a big ego and are a cancer on your company culture — because they intimately know the code and can safely make updates that avoid downtime. Making matters worse, it can be difficult for new developers to quickly acquire the same application knowledge, whether through training, mentorship or on-the-job activities. 

For developers new to systems, the challenge is that complex mainframe applications often include millions of lines of interdependent code, slowing comprehension and making finding the precise source code that needs to be changed extremely difficult. Not only is making unpredictable and risky changes to an application potentially bad for your bottom line, but application-breaking changes can also have a sizable impact on your company’s image.

The Ramifications of a Damaged Reputation Due to Knowledge Loss

Your brand reputation is a priceless asset, so any harm needs to be immediately ameliorated to ensure there is not a dramatic, long-lasting negative effect on your company’s financial health. Ideally, the risks are mitigated long before they have to be ameliorated.

While the risk of this knowledge gap can be hard to calculate, there are myriad impacts: 

So, how can you leverage AI to help mitigate risk to your reputation resulting from a loss of mainframe application knowledge?

AI to the Rescue of Your Reputation

AI-powered tools know more about your business applications than every developer who ever passed through your doors, empowering your organization to avoid disaster, move faster to meet a market opportunity and improve culture with less risk.

AI tools that automate the identification of the specific lines of code that require attention enable you to let go of toxic employees and not lose any application knowledge. Relatedly, AI can improve developer efficiency, helping you save money by getting more done with less. From a regulatory point of view, utilizing AI can also ensure the change you made always stays intact, thereby mitigating regulatory compliance risk and always acing your audits. 

By reinterpreting what the computation represents and converting it into concepts, AI equips developers with the knowledge necessary to safely, efficiently and effectively make requisite changes to fix bugs, make updates and minimize unintended consequences. The AI is not performing analysis, it is working collaboratively with your developers to increase their efficiency and mitigate the reputational risk associated with a loss of domain knowledge.

Public and private companies of all sizes, across a wide range of industries, recognize that damage to a brand’s reputation is a top risk management priority. Leveraging AI to precisely make changes to code in minutes empowers organizations across industries to mitigate risks to their reputation — and ultimately boost the bottom line.


Written by Steve Brothers, President of Phase Change Software.

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