How to Deliver Fast wtih a Large Team of UX Designers, Data Scientists, Software Developers and QA2/20/2019 One of the biggest challenges of modern software creation is having multiple team members — product managers, UX designers, data scientists, software developers, QA — working in parallel rather than sequentially. The world would be a much simpler place if the Product Manager completed a detailed requirements definition, then handed it off to data scientists who prototyped and refined their algorithms, then handed off to UX designers to create the full design, who then handed it off to development to build, who then handed off to QA for testing.
Unfortunately this is not the world we live in. Every software initiative is a race to getting value into the hands of users, and building sequentially is not an option. Moreover, teams are continually learning and need the ability to iterate. Product managers keep getting fresh market intel that needs to be injected into the product, data scientists keep making breakthroughs in the predictive algorithm’s accuracy, designers keep refining based on user feedback. The name of the game is agile, iterative, and mass parallelization of teams. But how do leaders run all of these very different teams that depend on each other in parallel, and still deliver to market fast?
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Have you ever been involved in a “blue sky” brainstorming session, where teams are encouraged to put aside current constraints and dream up new innovations? In software, this is most common approach to innovation, and if done right, produces some results.
But an article by Uri Neren, founder of The World Database of Innovation initiative, announcing the complete opposite: the number one key to innovation is not the blue sky approach, but an approach involving constraint, scarcity, and closed-world thinking. |