QASource Blog

As companies work to release new features and focus on marketing strategy, QA testing might fall a few spots on the priority list. But overlooking QA can negatively affect the product in many ways. Post-release bugs, security vulnerabilities and poor UX are just several consequences of bad testing. A consistently poor product can lead to lost customers, bad PR and a drop in revenue.

When companies are trying to run lean - increase efficiency and cut costs - they look for every opportunity to optimize the way teams work and produce. Though IT services have been outsourced for decades, many companies are still skeptical about outsourcing their QA services. Many decision makers still think of outsourced QA as “throwing it over the wall,” with limited interaction and collaboration between teams and deliverables that may or may not come back per the requirements. But there are plenty of reasons to believe in QA outsourcing. It helps product companies deliver high-quality products without breaking the budget, allows larger teams to scale resources up or down as needed, and frees up development teams to focus on value-adding features. (Click to tweet)

Product companies have it hard these days. From established organizations to scrappy startups, everyone’s focused on trimming the fat and running lean. This puts the onus on Dev and QA managers to deliver innovative, high-quality products using a constricted budget and limited resources. In turn, today’s recruiting process is about getting a lot of bang for a little buck.

From the early robotics of the 1950s to the advanced, algorithm-driven machine learning of today, AI has come a long way in a short amount of time. Though AI is still relatively young, QASource has found that AI's current and potential value to automated testing is massive. With the increasing complexity of applications, the lightning-fast speed of the software development lifecycle, and the highly competitive time to market across industries, engineers will take all the help they can get, whether it be from machines or other humans. So, why exactly is AI beneficial to automated testing services? Put simply, it allows the machine to learn and understand environments, perform “intelligent” actions, and improve itself automatically.

Market competition and an emphasis on great user experience drives innovation. And today, companies are innovating at breakneck speed. As product and service companies scale up their development teams to embark on new, attractive features and match the pace of their respective markets, they also scale up their QA teams to match the increased workload. Or do they?

Going to market with a perfectly functioning product is a great way to attract customers and cement relationships with them. And for many software product or service companies, that’s their goal. But many others are resistant to the idea of allocating budget toward the thorough QA testing required to achieve that goal. Their reasons range from “Our developers are smart, they can test their own code” to “We don’t know if QA will provide good ROI.” But, as the recent spike in data breaches and hacking has shown, an ounce of prevention is worth a pound of cure.

Today, it seems like we don't go a week without hearing about a high-profile hack or breach of customer data. As customers, we spread our information across a huge variety of applications, and we trust that no ill will come of it. The truth is, however, that we’re more vulnerable than ever, and the risk of a hack is made clearer to us everyday. We rationalize the situation, thinking, “Well, they must have people safeguarding my information, right?” Right — for the most part.

What happens when you can’t accurately measure the cost, effectiveness, and progress of a software testing project? A lot of less-than-ideal things. Projects can balloon in cost, creep in scope, fall in quality, or run on for what seems like forever. Without defined metrics attached to each QA project, they can get out of control -- and this scenario is a nightmare for both the product company and their team and the testing provider and their engineers.

One of the key challenges of working with an outsourced QA partner is aligning a new, offshore team with your product, procedures, and larger business objectives. Without the proper transfer of knowledge from the customer to the offshore team, engineers will be testing blindly. This leads to process slow-downs, inflated project budgets, and even lost contracts.