Don't Let Technical Debt Bankrupt Your Data Foundation

Technical debt sounds like a term straight out of a show like Shark Tank or Mad Money.

The truth of the matter is that the Information Technology sector borrowed the idea from Finance. Technical debt is commonly described as efforts deferred for the purpose of meeting deadlines or goals. Eventually, those deferred efforts will need to be revisited and reworked for the final state product. It is a tradeoff between gaining short-term benefits, mainly expediting work, while sacrificing long-term value and overall efficiency.

According to recent research, IT departments are spending about 40% out of every $10 to address this issues. One of the more interesting aspects of technical debt is that it will most likely go unnoticed by the end user until it comes due. However, if the debt continues to mount and isn’t reconciled, the lingering damage could cause uncompromising harm to an organization’s data fabric.

How Does Technical Debt Cause Harm?

Almost every data & technology initiative has incurred technical debt at some point. With the pressures of on-time delivery, most teams find it easy to justify a shortcut or two. This is especially true if the debt appears light or easy to fix later on. Often, these initial estimates do not or cannot factor in the downstream impact of future refactoring. To avoid regrets, consider the harm that too much technical debt can cause:

  • Duplication of effort: Utilizing technical debt as an inexpensive way to accelerate growth can lead to eventual duplication of effort. Whole projects or models may need to be partially or completely reworked to satisfy future state needs. In the end, the business might end up with tools that appear to solve immediate problems but cause more critical issues later. 
  • Hindered long-term productivity: Technical debt might speed up immediate deliverables but slow down future projects, make business performance issues tougher to solve (through technology), and compromise the ability of the business to scale. When everything is a priority, and multiple projects suffer from technical debt, enterprises may never make it back to the future state vision.
  • Reliance on legacy software or hardware: Extending reliance on outdated tools and hardware that have trouble keeping up with today’s data influx, can lead to larger problems in the long term. Furthermore, reliance on legacy products can also leave your work force stuck with a skill set that has been rendered obsolete by industry standards.
  • Lost time: Accruing technical debt eventually results in necessary fixes, which never appear at convenient times. Forced fixes for urgent problems carry a high likelihood of stealing time from important work of other projects and in some cases result in missed deadlines.
How to Avoid Technical Debt

Most businesses cannot and probably should not entirely avoid technical debt. People and companies incur monetary debt to expand businesses, buy property, and deal with urgent expenses. Sometimes, debt offers a better solution than doing without the monetary boost. As mentioned on the logz.io blog, "...sometimes, technical debt represents the least bad option." Credit bureaus give their highest scores to entities that manage debt well and not those that avoid it entirely.

As with financial debt, consider these suggestions to reduce reliance on and improve management of technical debt:

  • Teams must weigh the pros and cons of their data platform performance in order to make informed, logical decisions. Especially in consideration of the business’ growth, data insights, and data integrity.
  • If the team decides to assume technical debt, they should also develop a plan to monitor it and develop a roadmap to address it as the project continues to move forward.
  • Scrum masters can help by coaching, defining goals, assigning responsibilities, developing a project plan, and work to execute it.
How Data Ideology Helps Manage Technical Debt

Almost every data & technology adoption encounters technical debt. Consciously or not, it gets added to nearly every project. At Data Ideology, experience has taught us to acknowledge this debt and develop a quick payoff strategy for the best, long-term results.

For some examples:

  • We manage technical debt with a Proof-of-Concept (POC) approach to data solutions. A POC approach establishes the best criterion to acknowledge, measure, and pay the debt before releasing any project into full-scale production.
  • We also enjoy success with Snowflake, a maintenance-free data management SaaS platform that prevents accruing technical debt and relieves IT from future burdens.

Regardless of the project's scope, these initiatives can maximize benefits and minimize costs. If Technical Debt is keeping your organization from fully realizing your data's power and value, drop us a line. Tell us about your project. We'll show you how we can help you wipe out your debt without going technically or financially bankrupt.

Written by Ian Coyle

Director of Business Development

Ian Coyle is the Director of Business Development at Data Ideology with more than 12 years of technical sales and account management experience.

Healthcare

Pitfalls to Avoid when implementing Health Information Exchange

In recent years, Health Information Exchange (HIE) capabilities have helped mobilize patient data allowing clinicians and healthcare managers to provide near real time diagnosis closing the gap on member care.
Strategy

Scrum Master Best Practices to Accelerate Data Projects

Scrum is a Delivery Framework, under the Agile umbrella, that can accelerate initiatives, breakdown data silos, and bring organizations together as a team to progress any project. Individuals certified in Scrum are known as Scrum Masters.
Healthcare

Surprise! Payers’ Data Struggles with the No Surprises Act

In late December of 2020, bi-partisan legislation known as the No Surprises Act was passed by the U.S. government. The main purpose of the bill is to eliminate surprise medical costs for out-of-network services.