Now that we have insight into how to analyze and what to analyze, time has come for some… indoctrination. How can one mould analytical thinkers and analytical companies? We address the issue of culture and embedding the analytical twist into corporate mentalities.
For authors Thomas Davenport, Jeanne Harris and Robert Morison (for author bios click here), possessing the analytical DELTA is only half the battle. (Click here for box explaining the DELTA elements: Data – Enterprise – Leadership – Targets – Analysts). The other half is making sure that your company espouses an analytical mindset; that it develops what we might call the ‘cerebellum analyticus’, or analytical brain. At this stage of refinement, the analytics are so developed that they can make decisions for the company automatically.
For the authors, this indoctrination benefits from three steps:
- Step 1 is to embed analytics in the business processes
- Step 2 is to build an analytical culture
- Step 3 is to review your business comprehensively
Analytics as parsley
For companies to embed analytics in their daily work processes – as the short-order cook sprinkles parsley on his dishes – the authors first suggest a bit of triage: separate the artisanal analysis from the industrial stuff.
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An example will help clarify. An insurer confronting 10,000 claims each day will first identify all the run-of-the-mill claims (say broken windows or winter flus) and handle those industrially, with no or little human input. That is automated analytics. Evil tongues can be heard whispering that is what banks might have been doing with mortgages….
Alarm bells in the process – for example for that fishy-smelling third-time-in-the same-month claim – can divert some of the analysis to expert, non-machine help. That is automated with override.
Some complex forms of analysis are unsuited to automation. These may be unusually complex, or unprecedented, or multi-disciplinary cases. For example in medical processes, analytics may help provide background options or scenarios, but the doctor will need her skills and experience to conclude. (Click here for box on the stages of analytical evolution)
Build analytical culture
What does it take for an organization to be analytical? For the authors, the key is the proper mindset, or culture. And that culture depends on people having the right analytical stuff.
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Rather than explain these seven key traits in detail (go to pages 137 to 139 of the book for that), one can simplify somewhat by talking of the two sides of the analytical brain. Some traits are linked to seeking analytical solutions on an ongoing basis. Other traits are analytico-skeptical, i.e. knowing when analysis might have shortcomings. For the authors, being pragmatic about when to use and when to shun analytics is also key to being a top performer.
Review business comprehensively
Because companies are living entities, whose nature and needs change over time, so does the analytical requirement. This is why the authors recommend reviewing one’s business comprehensively for new analytical needs. A bit like a full medical check-up every few years…
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The periodic comprehensive business review needs to cover the business and its periphery: strategy, business model, customers and partners, analytical targets, competition, technology and data, and so on. An important insight here concerns the artificial intelligence of analytics: good analytics in Year 1 may need adapting in Year 3. Competitive pressures will have changed, and other internal factors may mean that the analytical musculature of a company needs toning or trimming.
A fine example provided by the authors to illustrate this ‘moving target’ allegory is that of Progressive and Allstate insurance companies. Allstate went from three different price points for its policies to four hundred in a matter of years, reflecting the finer analysis and better yield management techniques.
Even more drastically, the appearance of the Internet and its marketing tools has meant revisiting the analytics to take those new tools into account.
So as we come to a conclusion, where do we stand on Analytics? It is part of the manager’s toolkit. It is priceless in certain applications, namely areas with high volumes of decisions that can be simulated. But it also has its shortcomings, and should not be taken as the panacea for all management problems. In that way, it is like sel de Guérande (fancy French sea salt) when cooking: one of the elements in the mix. Not to be forgotten, but not to be overplayed.
By Chris Fodor, published December 2010.
Our next book will be “Power: Why some people have it – and others don’t” by Jeffrey Pfeffer. First installment will appear on December 15.
Jeanne G. Harris is executive research fellow and a senior executive at Accenture’s Institute for High Performance in Chicago. She leads the Institute’s global research agenda in the areas of information, technology and analytics. She is the coauthor (with Tom Davenport) of Competing on Analytics: The New Science of Winning. During her 33 years at Accenture, Jeanne has consulted a wide variety of organizations in many different industries worldwide. She has led Accenture’s business intelligence, analytics, performance management, knowledge management and data warehousing consulting practices. She has worked extensively with clients seeking to improve their managerial information, decision-making, analytical, and information management capabilities. Jeanne has authored numerous book chapters and articles in leading management publications, including Harvard Business Review, MIT Sloan Management Review, California Management Review, and CIO.
Tom Davenport is the President’s Distinguished Professor in Information Technology and Management at Babson College, and the Research Director of the International Institute for Analytics. Tom has written, coauthored, or edited twelve other books, including the best selling Competing on Analytics: The New Science of Winning (with Jeanne Harris). He also authored the first books on business process reengineering and achieving value from enterprise systems, and the best seller, Working Knowledge (with Larry Prusak), on knowledge management. He has written more than one hundred articles for such publications as Harvard Business Review, MIT Sloan Management Review, California Management Review, the Financial Times, and many other publications. Tom has also been a columnist for CIO, InformationWeek, and Darwin magazines.
Robert Morison is a business researcher, writer, thought leader, speaker and management consultant. He has been leading breakthrough research at the intersection of business, technology and human asset management for more than 20 years, working with more than 300 major organizations and writing or editing more than 150 research reports and management guides on topics ranging from workforce management and business innovation to business process reengineering, collaborative business models, and business analytics. He is coauthor of Workforce Crisis: How to Beat the Coming Shortage of Skills and Talent (Harvard Business Press, 2006), and three Harvard Business Review articles, one of which received a McKinsey Award as best article of 2004. He has recently been a commentator on workforce issues on Nightly Business Report on PBS. He has held research and business services management positions with The Concours Group, CSC Index, and General Electric Information Services Company.
How analytical is your organization? Here is how the authors characterized the level of analytical abilities in their previous work, Competing on Analytics.
Stage 1 – Analytically impaired
The organization lacks one or several of the prerequisites for serious analytical work, such as data, analytical skills, or senior management interest
Stage 2 – Localized analytics
There are pockets of analytical activity within the organization, but they are not coordinated or focused on strategic targets
Stage 3 – Analytical aspirations
The organization envisions a more analytical future, has established analytical capabilities, and has a few significant initiatives under way, but progress is slow – often because some critical DELTA factor has been too difficult to implement.
Stage 4 – Analytical companies
The organization has the needed human and technological resources, applies analytics regularly, and realizes benefits across the business. But its strategic focus is not grounded in analytics, and it hasn’t turned analytics to competitive advantage.
Stage 5 – Analytical competitors
The organization routinely uses analytics as a distinctive business capability. It takes an enterprise-wide approach, has committed and involved leadership and has achieved large-scale results. It portrays itself both internally and externally as an analytical competitor.