Phil Simon’s new book, The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions (Wiley and SAS Business Series) is a bridge to better things. Analytics, big data, evidence-based management, lean entrepreneurship — these modern and not so modern terms point to valuable approaches for organizational decision-making. Our work and our tools continue to increase the volume, velocity, and variety of the data we have access to. Unfortunately, our personal skills are not adapting at the same pace as the data around us, and so, even though we do have better tools for working with data, the human side of this equation can still cause a gap. Data scientists and engineers will continue to be sought after hires for the near and mid-term future. The Visual Organization offers a visual language to help us make use of the data we have today, with, and sometimes without, the help of high-end data professionals. 

Definition of Data Visualization

The working definition in the book is: visualization, or dataviz, signifies the practice of representing data through visual and often interactive means. An individual dataviz represents information after it been abstracted in some schematic form. Finally, contemporary data visualization technologies are capable of incorporating what we now call Big data.

The Power of Visualization

Simon helps us find appropriate bridges between data and our organization’s decision making needs. Visualization generally opens evidence-based management to a much broader audience. Organizations like Walmart, Netflix, Amazon, and eBay live and die based on decisions made from their data and have teams of data scientists to help make this happen. Visualization opens some of these techniques to the rest of us.  With visualization, even small organizations can have the pulse of their customer interactions, for example, without over extending their resources. Growing organizations can push decisions to where they have the most value (generally closest to the customer), without teaching everyone how to interpret text-based regression results. Even as individual contributors, we can use visualization to improve our work. We may need to start small, but we can improve from being static users of “small data,” to interactive users of small or big data.

Four Levels of Visual Organization (From Chapter 6)

Netflix, the video subscription service, and host to one of the most visible open prize competitions around analytics, is an example of a level 4 company. Simon describes a presentation by Netflix’s Jeff Magnusson, manager of data platform architecture and Charles Smith, software engineer, shared three pieces of the Netflix data philosophy (quoting):

  • Data should be accessible, easy to discover, and easy to process for everyone.

  • Whether your dataset is large or small, being able to visualize it makes it easier to explain.

  • The longer you take to find the data, the less valuable it becomes.

Netflix may attack these goals using interactive/big data (and everything in between) — but any organization can gain by following the same three tenants. The value of The Visual Organization is that it provides methods and tools to help. 

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My review is based on an early copy of The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions (Wiley and SAS Business Series), which I received for free from Phil Simon. I do have several copies on order that I will share as guest speaker gifts in my classes. It’s that good, and it’s not bad that he kindly quotes me in Chapter 5.