How and why making decisions based on “huge, noisy, messy data” requires business analytics
Although business analytics can probably be traced back at least to Frederick Winslow Taylor’s initiatives in the early-19th century, most of what I know about the subject was provided by Tom Davenport, notably in Competing on Analytics: The New Science of Winning (2007), co-authored with Jeanne Harris, and Analytics at Work: Smarter Decisions, Better Results (2010), co-authored with Harris and Robert Morison. Curiously, Gert Laursen and Jesper Thorlund do not mention Davenport and his work, nor do they provide a bibliography.
As I began to read this book, Anne Milley’s comments in the Foreword caught my eye: “How we make decisions using huge, noisy, messy data requires business analytics…It starts with an analytical view of data – what are we measuring and are you measuring what matters?…[Laursen and Thorlund ask] ‘What are you doing with your data? How are people in your organization armed to make better decisions using the data, processes, and analytical methods available?’”
This is precisely what Davenport has in mind in his latest book, Judgment Calls, in which he and co-author Brooke Manville offer “an antidote for the Great Man theory of decision making and organizational performance”: organizational judgment. That is, “the collective capacity to make good calls and wise moves when the need for them exceeds the scope of any single leader’s direct control.”
Here’s how Laursen and Thorlund define business analytics (BA): “Delivering the right decision support to the right people at the right time. In our definition, we have chosen the term decision support, because business analytics gives you, the business user, data, information, or knowledge, which you can choose to act upon or not.”
The “decision support” to which they refer is the infrastructure that Davenport and Manville recommend when stressing the importance of collective judgment based on widely shared data but I think that Laursen and Thorlund have more, much more in mind than an inclusive, collaborative decision-making process.
It seems to me that their primary objective is to help their reader understand BA information systems in terms of three elements: technological “which could be anything from papyrus scrolls and yellow sticky notes to cleaver heads with good memories”; human competencies; and “specific business processes that make use of the information or new knowledge.”
These are among the major business subjects and related issues that Laursen and Thorlund examine with rigor and eloquence:
o What their BA model is and what it can help to achieve
o BA initiatives: strategies and tactics
o Establishing and strengthening the BA infrastructure
o BA as a “holistic and hierarchical discipline”
o BA viewed as an active, collaborative support process
o Strategy and BA: Four Scenarios BA and prioritization
o BA and customer relations
o Information dissemination at various functional levels (see Exhibit 3.1 on Page 44)
o Optimization of business processes
o BA at the analytical and data warehouse levels
o Source system options and how each can be used effectively
o What a business intelligence competency center is and what it can help to achieve
o Assessment and prioritization of BA projects.
What many (most?) managers may now view as “technical issues” or even as “information issues” are really business issues. In many (most?) organizations, there can be as many as 5-15 different BA initiatives in progress at the same time. This fragmentation of focus and effort preclude “delivering the right decision support to the right people at the right time.” Obviously, what is needed is a holistic approach “that stretches across the entire organization.” Organizations can thus “move away from the static retrospective reporting results toward factual real-time information and analytical knowledge to drive individuals and process.”
In this context, enterprise architecture is the strategy and BA (as Gert Laursen and Jesper Thorlund define it) is the ultimate objective.
Those who share my high regard for this book are urged to check out the aforementioned books by Davenport and Harris as well as Evan Stubbs’s The Value of Business Analytics: Identifying the Path to Profitability. Also, Thomas Koulopoulos’ Cloud Surfing: A New Way to Think About Risk, Innovation, Scale, and Success and Jean-Paul Isson and Jesse Harriott’s Advanced Business Analytics: Creating Business Value from Your Data, to be published by John Wiley & Sons (October, 2012).