So other than confirming the obvious, the crux of this exercise is to realize that nothing actually guarantees the achievement of ideal average player lifetimes, retention rates, virality and ARPDAUs. The best a gaming company can really do is set up internal processes and pipelines, such as the ones below, that give it the best shot at producing a game with ideal metrics: Rapid prototyping and play testing: This is critical for quickly gauging the potential retention of a proposed game design before full-fledged work is to start on it. Many game designs are just not worth the effort of taking to fruition. Extensive A/B testing: Robust, extensive A/B testing throughout the life cycle of a game is very important because even minor bumps in analytics have a directly measurable effect on profitability. Pipeline for frequent updates: A reliable pipeline to deliver frequent content updates is a must-have in the bid to prolong average player lifetimes. Once a gaming company commits to a game, it needs to consistently perceive the game as a work-in-progress. Big-name gaming companies are already following the aforementioned fundamental tenets in their production pipeline – it’s more often the smaller studios which persist with informal methodologies. That’s bad practice because instead of facilitating the smaller studios to catch up, it exacerbates the gap between the big and small fish over time. As the mobile gaming market continues to spew riches for the foreseeable future, it is imperative that modern day game developers structure their entire operations around the fundamentals of data analytics instead of trying to fit a metrics-based veneer over introverted, blind game development. Their jobs are basically to create digital entertainment products that activate the maximum possible number of highly viral users on a daily basis for the longest sessions. Nothing more, nothing less.

We are moving away from the model in which learning is organized around stable, usually hierarchical institutions (schools, colleges, universities) that, for better and worse, have served as the main gateways to education and social mobility. Replacing that model is a new system in which learning is best conceived of as a flow, where learning resources are not scarce but widely available, opportunities for learning are abundant, and learners increasingly have the ability to autonomously dip into and out of continuous learning flows.