This column takes a look at a new book, The CDO Journey, by Peter Aiken, Todd Harbour, Kathy Walter, Ed Kelly, and Burt Walsh (Technics Publications 2020).
When I read a data book, my goal is to find at least ten important messages that can impact how I approach the topic. I hit my ten in The CDO Journey before the end of Chapter 2. I think this has to do somewhat with the relative newness of the Chief Data Officer (CDO) role, but more importantly, how this content is presented in the book.
The book was written by five authors, each with lots of experience in the field–probably combined easily over 100 years of experience in the data field. The book is not a how-to or a methodologies book–but rather a book on insights and advice from these five thought leaders. These best practices are presented in a very well-structured manner, where each chapter advances the reader in their knowledge of how to carry out the CDO role successfully.
Here is a brief synopsis of the first six chapters of The CDO Journey:
Chapter 1, Current Environment, describes data’s confounding characteristics, the current disagreement about CDO reporting structures, the need for adaptive planning, balanced implementation, and the specific must-invent new execution models.
Chapter 2, Data Maturity, introduces a CDO process improvement framework based on years of proven research. The Data Management Body of Knowledge (DMBOK) and Data Management Maturity Model (DMM) describe core concepts, techniques, and tactics for data leaders to use.
Chapter 3, Integration, is a plea to delay technology investments. The current technology-first approach has produced organizations that struggle to tame investments and made several consultancies very wealthy.
Chapter 4, Strategic Planning, describes the key roles required to sustain data and practice improvements beyond the current leader.
Chapter 5, Execution, describes issues CDOs will face while implementing solutions in their organizations.
Chapter 6, Formalization, describes some efforts in both federal and state governments that are noteworthy and deserving of attention. This section primarily describes work happening in the public area, but the outcome of these efforts will affect both the public and private sectors.
Three Ps and a T
Any organization wanting to set up a long-term sustainable data management initiative needs to address four critical elements at every step in their decision-making process. These elements reflect different perspectives of decision-making that affect the organization, the CDO, and the role’s success. These perspectives stand for the intersection of four powerful forces that affect virtually every aspect of CDO’s world.
The forces include policy, people, process, and technology (P3T). The first P is POLICY, the rules defining how the organization controls its data and what laws are right for its legal, ethical, and moral use. PEOPLE, the second P, describes a professionalized workforce that understands the value of data and that can work across the organization by effectively using data to the benefit of the organization. The third component, PROCESS, not only provides a structure for reviewing and acting on requests for data access and improvement, but also describe how organizations orchestrate activities to use and exploit data advantages. Processes also name decision owners under certain circumstances. The last part, TECHNOLOGY, refers to the computing environments in use by organizations to collect and process data.
The P3T construct explicitly reminds us that the most unpredictable and challenging consideration is PEOPLE. People are the glue binding all the components. It takes people to make sure that everything works in concert. Unfortunately, however, people can also easily derail any process, platform, or policy that you work to create.
A primary lesson, here, is that not every problem has a technology-based solution. We rarely see organizations that would not receive help from a balance of P3T in their solution. What organizations must do is focus data strategy on those business outcomes that help the organization exploit data across the entire digital landscape—from acquisition to final disposition, creating value in the form of innovation, customer engagement, and growth. These characteristics combine to guide the organization’s data governance program. Putting it another way: your data strategy needs to be 1) actionable and support a valid and useable organizational strategy and 2) easily understood by everyone in the organization, including business and IT.