Customer experience transformation is a key initiative for any business that wants to position itself for the 21st century. Two important concepts involve updating and digitizing technology, and creating persistent customer relationships. According to Bain & Company, customer experience transformation starts with “… simplifying your core business and digitizing it where it matters.” McKinsey & Company writes that in any customer experience transformation, “… the voice of the customer can be used to identify upstream and cross-functional issues and address the root causes of problems.” In short, to see positive results, you need well-tested, high-quality digital assets that reflect ever-evolving customer needs and desires.
Testing is critical for organizations like NASA, the US Army, Northrop Grumman, BAE Systems, Lockheed Martin, MBDA, the UK’s Ministry of Defense and the Metropolitan and Scottish Police, where lives are on the line. As we've worked with customers like these over many years, we've noticed how much more testing is than just making sure the system works — it’s about ensuring we test for mission success and continuously optimize mission outcomes. Whether you're designing systems for command and control (C2); to provide support for complex police operations, such as hostage negotiations; or for shooting down an enemy missile, you should plan your testing and monitoring strategy to continuously test against the desired mission outcomes.
On May 21, 2018, Bank of America announced that it was rolling out its chatbot, Erica, to all its mobile customers. On the surface, the premise makes sense. It’s making the bank more relatable. It’s providing real-time customer support to people where artificial intelligence (AI) assistants like Siri and Alexa are becoming the norm. It doesn’t have the limitations that some phone-based IVRs have, and it aims to provide immediate assistance instead of making us wait for a human (we’ve all shouted “representative” or pressed zero dozens of times to get a real person). Erica is a great way for Bank of America to optimize the customer experience.
But let’s pull back the covers and ask some basic questions. How does Erica know the customer so well? How does Erica pull from different sources of information? How does Erica know what products and services to offer? What systems, both homegrown and third party, does Erica need to be effective?
Sometimes I feel as if I’m the Forrest Gump of quality assurance (QA). Since 1998, I’ve been through the beginning of automated integration testing and service virtualization through being a co-founder of Class I.Q. (now IBM Greenhat). I’ve been through the first phases of an automated testing center of excellence (ACOE). I’ve been there for the start of risk-based testing, and I’ve been a part of the transformation of QA from a somewhat necessary function to something that is now the core and chief concern of any company putting out quality software and apps.
Everything about software has changed—how it’s architected, developed and produced, what it does, what users want from it, and how often they expect new features. To keep up, organisations are turning to continuous delivery and DevOps. Yet product teams still do a lot of manual testing, which consumes a lot of time they don’t have, thanks to shrinking test windows. Incorporating automation into your testing approach is a great strategy, but figuring out where and how to start isn’t necessarily quick and easy.
We recently co-hosted a webinar with Bloor Research about the Future of Testing, and in it, we conducted an informal poll about artificial intelligence (AI) and testing. When we asked what everyone thought the biggest advantage was to incorporating AI into a test automation strategy, attendees overwhelmingly selected team productivity and efficiency.
The focus on artificial intelligence (AI) in general, in technology, and particularly in testing, is prompting organizations worldwide to take it seriously. It’s hard to ignore AI’s potential benefits, including improved productivity and efficiency, fewer defects, a better UX, and happy customers. And with DevOps and continuous delivery here to stay, staying relevant depends on keeping pace, which is why test automation is so critical.
For a while now (about 10 years), Dev and Ops have been trying to get along. After all, collaboration between the two creates fast feedback loops and gets high-quality software into users’ hands faster. But with a new space emerging, digital experience management, Dev and Ops need to make a new BFF—the business—to stay in sync.