In the ever-evolving landscape of software development, particularly in the niche of insurance technology, one constant challenge is the balancing act between three key variables: cost(cheaper), speed (faster), and quality (better). The age-old adage suggests that you can only pick two out of the three. However, the reality is far more nuanced. In this blog, we'll delve into this trilemma and explore how to find the right balance, especially when developing SaaS products for insurance claims processing.
When you aim for a solution that is both cost-effective and quick to market, the quality often takes a hit. This could mean fewer features, less robust architecture, or limited scalability. In the insurance tech world, this might translate to a claims processing system that lacks advanced analytics or AI capabilities.
If you're looking to build a high-quality product on a budget, be prepared to invest a significant amount of time. Quality assurance, in-depth testing, and meticulous design are time-consuming. For insurance companies, this could mean waiting longer for a system that can handle complex claims scenarios or fraud detection.
If you want a top-notch production the shortest time possible, it's going to cost you. This often involves hiring more experienced developers or using more expensive tools and technologies. In the context of insurance, this could be a state-of-the-art claims processing system that uses machine learning algorithms but comes with a hefty price tag.
Not every feature in your software needs to be a masterpiece of engineering. Sometimes, "good enough" is truly good enough, especially if it's reliable. For instance, a basic but reliable feature for document uploading in an insurance claims system can be more valuable than a fancy, AI-driven feature that's prone to errors.
The importance of each variable—cheaper, faster, better—can change depending on the context. If you're developing a proof-of-concept or a minimum viable product (MVP), speed and cost may take precedence. On the other hand, if you're working on a core feature that handles sensitive insurance claims data, quality cannot be compromised.
At Evolution Global one of our approaches is to balance the trilemma through iterative development. Start with a basic, reliable (and thus cheaper and faster) version of the feature. Collect user feedback, especially from your customers, and then invest more time and resources to improve it (making it better). Our initial product, FileTrac, was built for one customer and then another customer with more features and so on. Now as we have moved into more advanced products, we have adjusted the concept of yes to everything and moved to features that create global value. We still have to balance the trilemma on a daily basis, but every wish, request, desire and need is measured against lessons learned, historical use and industry need. This gives us a unique opportunity to justify the trilemma on a feature-by-feature basis.
The trilemma of cheaper, faster, and better is not a zero-sum game. The real challenge lies in understanding the specific needs of your project, the expectations of your end-users, and the context in which your software will operate. In the insurance tech space, this means creating SaaS products that can efficiently process claims without sacrificing quality or breaking the bank.
By adopting a flexible, context-aware approach, it's possible to find a balance that offers real value. After all, in the complex world of insurance claims processing, sometimes the best solution is the one that is reliable, even if it's not the cheapest, fastest, or the best.