The Client is a multinational technological company and a provider of data for news, audio, video and other categories.
With social turmoil, the COVID pandemic and the accelerating pace of world events, more people constantly seek information online in real time. Leading websites rely on the Client not only for general data topics, but also for breaking news, progression of events, market trends and other timely information. This requires the Client to be agile and quick, able to scale and deliver flawless performance across numerous devices, locations, scenarios and languages.
When the Client approached Qualitest, filtering data maturity in English was considered high. However, in many other languages, as well as the dialects and variations of those languages in different countries (for example, French in France vs. French in Canada), the maturity was considered significantly lower.
To elevate the filtered data overall, the Client needed a scalable global program. Because data capabilities drive a large portion of the Client’s revenues, there was an urgent need to establish such a program quickly and be able to scale it significantly year over year.
To undertake this program, the Client wanted a Quality Engineering partner who:
Qualitest implemented an iterative process model, with three clear, well-defined phases.
To identify the right framework, Qualitest engineers/team leads undertook enterprise-level deep dives and fact-finding excursions into the Client’s existing production systems, documenting findings carefully to create a preliminary knowledge bank. The Qualitest teams gained a detailed understanding of the unique logic and tools required. During this phase, our teams began delivering projects across different countries supporting multiple languages and establishing a mutually agreed-upon SLA for the program as a whole.
Our engineers also took it upon themselves to master the understanding of some of the integrations between the data engine and other Client systems.
With this firm foundation in place, Qualitest began the scale-up, creating an operational engine to:
The outburst of COVID during this phase brought two unanticipated challenges: the “Great Resignation,” a global trend in which employees were leaving their jobs, and a significant shift in the way consumers used data, which necessitated rethinking many of the program’s basic assumptions. Through Qualitest’s internal rotation program, we were able to retain the vast majority of engineers and successfully scale the program up.
Currently the projects are in steady state, while the teams are showing continuous improvement month after month. Today we focus on improving a Qualitest delivery model known as 3-I:
The Qualitest team of engineers not only met all the Client’s stated goals within the allotted time frame, but also exceeded many of their targets.
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