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What is Technical Debt?
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Sreelatha Yelesam
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There is no single definition of technical debt. It is essentially any system in our list of applications that is slowing down our ability to deliver change and innovate quickly. Also, part of that general definition is that technical debt represents any system where the cost to maintain it starts to exceed its value. CIOs say they divert as much as 20 percent of their new technology budgets to resolving tech debt issues. It also represents as much as 40 percent of their entire technology estate according to a recent McKinsey Survey.

Watch the video to learn about Technical Debt. There is a summary below.

We found a Techolution client that was spending $62 M a year on legacy support cost, which is potentially reaching the point where most incoming revenue is being funneled to mainframe support. That’s far from unusual with a huge percentage of Fortune 500 companies across finance, insurance, healthcare and retail sectors along with the government sector using legacy mainframes and other technical debt generators. The government alone spent over 80 percent of its $90 B 2019 IT budget on operation and maintenance of legacy systems according to a recent U.S. Government Accountability Office report.

Many of these legacy mainframes are running Cobol, which is over 60 years old. This has led to an additional problem of technical debt where engineers with the experience and knowledge to run these systems are dwindling or unavailable in many parts of the world. Many engineers with this expertise are at retirement age. And Cobol is just one example of a legacy business programming language or legacy system that is no longer being widely taught or of interest to the new crop of engineers. This puts those businesses in a bind about what to do next and how to modernize to meet current business and customer needs.

These legacy systems that carry technical debt are costly to replace and often not deemed worth the business disruption that would cause. The problem is that they are causing major bottlenecks to crucial modernization that affects application development and overall IT and OT improvements that keep the business competitive and innovative.

A primary example is how data analytics is driving everything from product innovation and customer service to digital twins, operational intelligence, IoT, computer vision, BI, and predictive analytics overall. If your data is inaccessible in a legacy mainframe that technical debt is preventing you from doing all the necessary crucial actions that come from predictive analytics.

Technical debt may be the biggest roadblock that businesses have to stay competitive and meeting customer needs through digital transformation driving cost reductions, business growth and innovative products, services and customer experiences. Technical debt brings a host of connected challenges that can include:

  • Lack of system architecture integration
  • Skyrocketing business costs for maintenance
  • Holding back digital transformation
  • Internal and external skill-availability gaps
  • Organizational capacity fulfillment and growth bottlenecks
  • Project backlogs
  • Reactive rather than proactive business decisions from lack of cohesive predictive analytics environments
  • Slow application development
  • Inability to meet changing customer product, service and user experience demands
  • Inability to maximize use of cloud environments for business and bottom-line effectiveness and innovation

This technical debt is increasing faster than your adoption is increasing, so it’s creating this bottleneck in there, and we need to get past that. It’s such a crippling aspect of everyone’s digital transformations that it’s extremely important that we rise above it. To learn more about technical debt, let’s set up a call and talk about how to cost-effectively and efficiently overcome it to unlock real world business potential.