What does it take to become a data-driven organization? "Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply ingrained data culture," says Carl Anderson, director of data science at the phenomenally successful Warby Parker. In his recent O'Reilly book Creating a Data-Driven Organization, he explains how to build the analytics value chain required for valuable, predictive business models: From data collection and analysis to insights and leadership that drive concrete actions. Follow Anderson @LeapingLlamas.
Practical advice, in a conversational style, is combined with references and examples from the management literature. The book is an excellent resource for real-world examples and highlights of current management research. The chapter on creating the right culture is a good reminder that leadership and transparency are must-haves.
Although the scope is quite ambitious, Anderson offers thoughtful organization, hitting the highlights without an overwhelmingly lengthy literature survey. My company, Ugly Research, is delighted to be cited in the decision-making chapter (page 196 in the hard copy, page 212 in the pdf download). As shown in the diagram, with PepperSlice we provide a way to present evidence to decision makers in the context of a specific 'action-outcome' prediction or particular decision step.
Devil's advocate point of view. Becoming 'data-driven' is context sensitive, no doubt. The author is Director of Data Science at Warby Parker, so unsurprisingly the emphasis is technologies that enable data-gathering for consumer marketing. While it does address several management and leadership issues, such as selling a data-driven idea internally, the book primarily addresses the perspective of someone no more than two or three degrees of freedom from the data; a senior executive working with an old-style C-Suite would likely need to take additional steps to fill the gaps.
The book isn't so much about how to make decisions, as about how to create an environment where decision makers are open to new ideas, and to testing those ideas with data-driven insights. Because without ideas and evidence, what's the point of a good decision process?