Building a Digital Analytics Organization

When I first started writing my new book “Building a Digital Analytics Organization” I did it because I knew there was a right way and wrong way to maximize the creation of economic value from using digital data, analytics, and research to help people make better decisions about planning, performance, and strategy.  And no one had written about the topic before. The right way and the wrong way to compete and succeed with digital analytics were nuanced and different depending on the nature and culture of the company.  In fact the laughable MBA adage “it depends” is certainly truest when creating analytical competency in companies of any size.  What consultants can rarely tell you — because few have actually built, reengineered, or evolved over the long-term analytics teams in globally distributed organizations is — that the theory about how to do “web analytics” you read as best practice guru advice from “thought leaders” may not actually work for or be relevant to your business, and the professors of “it depends” theories are mostly making excuses. Everything always depends on everything else, so what is the decision to be made based on the dependence and the data?

The book Building a Digital Analytics Organization contains my ideas and thoughts from actually having done digital analytics in complex, and sometimes uncomfortable, executive roles for brands you probably heard about.  And a lot of private consulting for companies you definitely heard about that I’m under NDA not to talk about.  And from meeting smart folks like Jacques Warren, I learned a lot about how the best international consultants approach a business issue and help their clients make money and do even better competing in their industries.

That’s why when Jacques told me he pre-ordered my book, I was psyched that it would appeal to the “smart guys” like him.  I’m also pleased that after sending it to folks for review, I got some excellent reviews, which I noted in the book, from Thomas Davenport (who wrote the Foreword), Avinash Kaushik, Justin Cutroni, Bryan Eisenberg, Rand Schulman, Andrews Edwards, and some of the CEO’s of the most innovative companies in digital analytics today – from Raj Aggarwal at Localytics to Larry Freed at Foresee Results to Julio Gomez, who founded and is the real Gomez behind the Gomezbot (for those who look at user agent strings of robotic traffic).  Here’s what Thomas Davenport said:

 “A rigorous, professional approach to digital analytics requires the types of management approaches that are laid out in this book… Judah Phillips has been an advocate of these serious disciplines for a long time, but now the world is ready to adopt them–and the book comes along just in time… and this one is distinctive in a number of ways and brings into the digital analytics space a sophistication in both data management and data analysis that is not often found….”

Now that I’m all done with this book, I’m pleased Building a Digital Analytics Organization has been publicly released and is now available.  The book defines what digital analytics is:

Digital Analytics is a set of business and technical activities that define, create, collect, verify or transform digital data into reporting, research, analyses, recommendations, optimization, predictions, and optimizations.

I then cover a wide range of topics from the reasons why digital analytics is important to today’s economy.  Then I introduce my concept called the Analytics Value Chain, which encapsulates 9 P’s of digital analytics (from process to production to prediction to profit and so on) and then I go where few have gone into explanations of useful quantitative analytical methods and techniques to use on digital data, and to business approaches for extending digital analytics to work with other teams, like market research and competitive intelligence. I also discuss how data and analysis can be used for testing, targeting, and automation in the future economy, which I call The Analytical Economy – in the context of protecting consumer data and privacy.

To give you some idea of what I write about in the book consider the following guidance below on the macro steps to building a competency in analytics, which is just a short glimpse of some of the simpler content in my nearly 400 page book, Building a Digital Analytics Organization, in which I hope Jacques and you will find value in your world if you choose to read it:

  1. Understand the Pain Points and Business Concerns. Speak with stakeholders and business people to determine the current business concerns, challenges and areas on which to concentrate with analytics.
  2. Determine the Investment Required. When necessary to invest, the digital analytics leadership should quickly make that determinations and propose investment.
  3. Orient the Business and Technology.  After understanding the business pain and challenge, the investment or technology to apply, you next need to communicate your plans to create your digital analytics team.
  4. Manage for Process and Scale. Given the world of “big data” and “data science” resources are hard to find and expensive when you do, thus you should begin to plan for scale and process to yield an improved future state of your team.
  5. Handle the Data. Big data just keeps coming and getting bigger. The digital analytics team will need to keep their systems and tools in parity and alignment with the influx of ever-changing data.
  6. Get the Most from the Team.  By applying strong leadership and motivational skills, the team’s leaders should strive to get the most from their teams.
  7. Get the Most from Technology. By alignment and team-building across functions, the analytics leader must maximize working relationships and team equity with IT.
  8. Get the Most from Vendors. By partnering with vendors and ensuring good relations (i.e. don’t always just beat up vendors), you can get the most from your vendor.
  9. Produce and Communicate Analysis. Critical to the perception of success is the analytics team that produces regularly occurring analysis and communicates it to stakeholders. Producing data is meaningless unless people tell other people about it who can use it.
  10. Change the Business. Through the insightful analysis and recommendations, the analytics team must work across the business to improve it by creating value.

(Editor’s note: If you wish to purchase the book at Amazon)