Saturday, May 15, 2010

Competing on Analytics

@aleksb6 had a thought on #orgintelligence and asks where do concepts from "Competing on Analytics" fit in my model? Great question, and I immediately ordered a copy of the book from the library. The book has now arrived, so I can explore some answers.


Davenport and Harris (I shall call them DH) start by defining business intelligence as a set of techniques and processes that use data to understand and analyse business performance, from data access and reporting to analytics proper, together addressing a range (spectrum) of questions about an organization's business activities. They position analytics at the higher-value and more proactive end of this range (spectrum), and offer a graph that appears to correlate the degree of intelligence with competitive advantage (DH pp7-8).

Data Access and Reporting
Analytics
Standard reports - What happened? Statistical analysis - Why is this happening?
Ad hoc reports - How many, how often, where? Forecasting/extrapolation - What if these trends continue?
Query / drill-down - Where exactly is the problem? Predictive modelling - What will happen next
Alerts - What actions are needed? Optimization - What is the best that can happen?

However, intelligence is not just about asking clever questions, but includes a number of other capabilities described in the book including fact-based decision-making (DH pp 44-7) (sometimes known as evidence-based policy) and the capture of learning from organizational experiments (DH pp178-9).

The book is clearly tied to a software industry perspective on intelligence, understanding business intelligence as a collection of systems and services, and a chapter devoted to software technology is entitled "The Architecture of Business Intelligence" (Chapter 8). For my part, I might have wished that this chapter had been called "The Software Architecture of Business Intelligence", and that the wealth of material on introducing enhancing analytical capabilities (Chapter 6) and managing analytical people (Chapter 7) had been presented as "The Organizational Architecture of Business Intelligence".  Or even "The Architecture of Organizational Intelligence". But that's the book I'm writing, so I guess I shouldn't complain.

The authors clearly understand that it is not the possession but the use of this technology that is the critical differentiator. They identify four common characteristics of the most analytically sophisticated and successful firms (DH p23).
  1. Analytics supported a strategic, distinctive capability.
  2. The approach to and management of analytics was enterprise-wide.
  3. Senior management was committed to the use of analytics.
  4. The company made a significant strategic bet on analytics-based competition.
(As an aside here, I am always slightly sceptical about senior management commitment being a precondition for success, because I've generally seen it as a postcondition for success. When an initiative is successful, senior managers will appear from nowhere to take the credit.)

The book ends with an eloquent argument for analytical capability (p 186).
"Analytical competitors will continue to find ways to outperform their competitors. They'll get the best customers and charge them exactly the price that the customer is willing to pay for their product and service. They'll have the most efficient and effective marketing campaigns and promotions. Their customer service will excel, and their customers will be loyal in return. Their supply chains will be ultraefficient, and they'll have neither excess inventory nor stock-outs. They'll have the best people or the best players in the industry, and the employees will be evaluated and compensated based on their specific contributions. They'll understand what nonfinancial processes and factors drive their financial performance, and they'll be able to predict and diagnose problems before they become too problematic. They will make a lot of money, win a lot of games, or help solve the world's most pressing problems. They will continue to lead us into the future."
That covers part of my vision of organizational intelligence, but not all of it. This argument focuses too heavily on efficiency and not enough on disruptive innovation. An intelligent organization will need to be adept at analytics, but I don't think that's the whole story. And I can explain this in terms of the authors' own example.

The book opens with the story of Netflix. The company was founded in 1997, competing against established video rental companies like Blockbuster. "Pure folly, right?" the authors ask rhetorically, and then go on to attribute Netflix's success to the incorporation of analytics into its business operations (DH pp3 ff).

Okay, there is clearly a lot of intelligence in the way Netflix operates, but what equally interests me is the intelligence involved in creating Netflix in the first place. Obviously the authors don't regard the founding of Neflix as folly - in retrospect it was a very smart move indeed - but this kind of decision is not primarily based on the kind of analytics described in the book but involves a completely different kind of intelligence. Hence organizational intelligence is not just analytics.


Thomas H Davenport and Jeanne G Harris, Competing on Analytics, The New Science of Winning. Harvard Business School Press, 2007

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