4 Tactics to Improve Sprint Predictability in Big Data Analytics Projects

Taking on a full-scale agile transformation is never easy for any waterfall-based engineering organization. Adopting the agile ceremonies is relatively quick and easy — training is a few days, coaching a few weeks — but the mindset changes needed to make agile truly valuable are usually measured in years. When you add in the complexities and scale of big data, the challenges of an extremely diverse set of technologies and languages, the uncertainties inherent in analytics research, and the conservative, date-obsessed approach favored by traditional telecom customers, you get a perfect storm of difficulty!

Where We Fit Comparative To Agile’s Sweet Spot

4 Tactics to Decrease Unknowns (and Increase Predictability)

In our engineering organization, there are 4 primary methods we use to decrease the unknowns and get more consistent sprint output:

Fearless and forever curious — a life-long learner, explorer, cat-herder, and engineer, leading software projects for some of the world’s coolest companies.