data_dynastyOver the years I’ve shared my thoughts on digital governance through various blog posts and presented on the topic multiple times at Omniture and Adobe Summits. I’ve discovered that “governance” is one of those loaded terms that can mean different things to many people. In some regard, I think there might be a negative halo effect associated with it due to a similar-looking but less popular word . . . government. Despite the six letters it shares, proper governance can definitely have a positive impact when it comes to running web analytics programs at mid-to-large companies.

I define digital governance as the oversight of all the essential organizational factors that contribute to the success of a data-driven, digital-focused organization. Although analytics technologies continue to evolve and the volume (and diversity) of data increases significantly each year, the fundamentals for establishing a winning web analytics program haven’t changed. What you needed to be successful five years ago is the same as what you need in 2013 and beyond. There may be new approaches and considerations, but the fundamentals are timeless.

As a former web analytics consultant who worked with large, multinational companies across a variety of different industries, I’ve seen the same set of challenges and mistakes re-appear over and over. That’s one of the unique benefits to being a consultant; you can step back and observe patterns across multiple firms that you could miss if you only observed your own company in action. However, seeing the same errors being repeated over and over can be a frustrating experience, especially when you know most of these businesses are investing heavily in digital and want to be successful with analytics.

bandaid_solutionIn order to help more companies overcome the challenges of establishing an effective digital analytics program, I identified a number of best practices that our consulting team had seen work at different organizations. However, I soon discovered the best practices were merely band-aid solutions unless the underlying root problems were addressed. What was really needed were some guiding principles or a framework for understanding what was causing otherwise successful organizations to struggle or fail when it came to analytics. While some of the existing web analytics maturity models were helpful, I still felt as though some key considerations were missing, under-emphasized, or misrepresented.

I set out to develop a new digital governance framework and maturity model that would offer an alternative perspective on the topic. As I was working on the new framework, I found a lot of the issues I encountered at different companies were often interconnected and multifaceted. However, in time I was able to untangle and organize the critical elements into six key focus areas for building a successful data-driven organization:

  • LEADERSHIP: Guidance and sponsorship from company leaders helps digital analytics to prosper within your company.
  • STRATEGY: A clear digital strategy enables your digital analytics group to align its measurement activities to the key priorities of your business and thrive as an integral part of your organization.
  • PEOPLE: Having the right talent and sufficient resources on your digital analytics team is crucial to your long-term, data-driven success.
  • PROCESS: To have an effective digital analytics program, it is important to develop internal best practices and well-defined processes.
  • TECHNOLOGY: The right technology plays a central role in fostering a data-driven organization.
  • ORGANIZATIONAL DYNAMICS: Different internal factors cannot be ignored when trying to cultivate a data-driven culture.


You probably noticed the familiar People, Process, and Technology mantra among the six factors. I’ve expanded it to include three other influential factors–Leadership, Strategy, and Organizational Dynamics–that can make or break your organization’s success with analytics. Each of these main categories can be further broken down into several key sub-elements, and that’s where you begin to see subtle differences between this framework and other maturity models.

As an example, the PEOPLE category has four subareas:  Resources (types of staff required, roles and responsibilities, etc.), Expertise (skills and knowledge requirements, training approach, etc.), Structure (team organization, ownership, etc.), and Community (internal support, best practice sharing, etc.). With the help of these sub-areas within the digital governance framework, you can pinpoint specific gaps or weak areas that need attention at your company.

After presenting these new concepts at the Adobe Summit for the past two years, I want to share this information more broadly with other digital analytics practitioners and data-driven executives. You can now you can download a free copy of a 15-page whitepaper on this new digital governance framework and maturity model. It takes an in-depth look at the different factors and sub-factors that are the building blocks of a best-in-class digital analytics program. If you’re a sports fan, I compare the parallels of building a championship team dynasty to that of creating a data-driven dynasty (if you’re not a sports fan, don’t worry—I don’t go too overboard on the sports analogies). My hope is that your company can use this new whitepaper as a strategic guide for generating an even better return on your digital analytics investments. Game on!


This is a good high level post and PDF on digital analytics governance.

Governance is still undervalued and needs more attention. It doesn't have the shiny ball glamour but it is a foundational element to success. Without it the shiny ball initiatives will continue to fall short of hype and expectations.