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Dealing with Data:
For years, the writers of columns like this one have been tantalizing data management (DM) and marketing professionals alike with visions of a future in which personalized, relevant, context-sensitive marketing messages are delivered electronically to specific individuals. The result of this nirvana would be a transformation in the relationship between providers and consumers - and in the commercial potential of those players who get it right.
Well, that future is beginning to happen. Its starting point lies in the wealth of customer transition data that consumer-facing businesses of all types now collect. To personalize the content and delivery of the messages, something else is needed: analytics. The enabler that is turning the data-rich present into future reality is the application of sophisticated real-time analytics to business intelligence drawn from accurate, timely and accessible transaction data.
Analytics has long been regarded by many as smart technology in need of a killer application to justify the investment; it is now shaking off that Cinderella status. Accenture's recent research study confirms that the message about the critical role of analytics in customer relationships is now getting across - and demonstrates the clear linkage between analytics-based decision-making and high performance.1
The study examined the role of enterprise systems in driving corporate value, focusing specifically on respondents' views and investment intentions around analytics. The survey of 450 executives in 371 organizations from 34 countries and 19 industries was then compared to the findings of a similar research program Accenture conducted in 2002.
Results confirm that the intervening four years have seen a dramatic increase in the importance of analytics to businesses of all types. Almost half of respondents believed their analytical capabilities were above average - a 150 percent increase since 2002. More significantly, higher-performing businesses were five times more likely to describe analytics as being a key element of their strategy. Two-thirds of high performers said they had significant decision-support/analytical capabilities, compared to less than a quarter of low performers.
Furthermore, our respondents said this investment in analytics is creating a competitive edge out in the marketplace. Fifty-three percent of our executive interviewees believed they were gaining a competitive advantage through distinctive capabilities enabled by analytics. And the use of analytics for decision-making was highlighted as the single biggest attribute for making organizations distinctive, cited by 89 percent.
People are investing in analytics. But what does this mean in practice? Picture the scene a couple of years from now. You walk into your local supermarket and slot your loyalty card into a little screen on the shopping cart. It immediately shows you a suggested personalized shopping list complete with today's prices. It even highlights the two-for-one offers on your favorite fair trade coffee and the special offer on creamy peanut butter.
Again, this sort of technology has been written about for years. The difference is that this intelligent shopping cart already exists - though currently it is circumnavigating an Accenture research laboratory in France rather than your nearest grocer. Eventually, this technology will come to a retail outlet near you.
Over the past decade, the massive commercial potential of delivering personalized offers electronically to consumers has been foreshadowed by the success of relevance marketing in driving high performance in the retail sector. For example, in 1995, the UK-based supermarket operator Tesco asked a relevance marketing specialist company called dunnhumby to help launch its new club card scheme - the rest is history. Tesco is now one of the world's biggest retailers, powered by a relevance marketing engine that has gone far beyond the traditional concept of building customer loyalty - and which has, in turn, helped to drive the company's expansion into home delivery, personal finance, telcoms and other areas.
Given this experience, it is hardly surprising that 89 percent of retailers are using BI processes, according to an Aberdeen Group research report in June 2006.2 But it would be wrong to think the benefits of analytics apply only to retailers. From financial services to airports, a growing number of organizations are applying analytics to raise their performance. Having cut costs and reduced headcount through more efficient processes, companies are increasingly turning to analytics to renew their focus on growth and differentiation. This means integrating, optimizing and analyzing their information to develop and support the distinctive capabilities that create and sustain competitive edge.
However, this is not easy. Rather than involving only a change in technology, it also requires a fundamental shift in corporate understanding and behavior toward the use of analytics-derived intelligence that is pervasive, real time and predictive. To help drive this shift, more companies are setting up centers of competence where their best and brightest analytics specialists team up to constantly innovate around a single view of the business. Consolidation of departmental data marts into enterprise-wide data warehouses also helps. When all these elements are combined with analytics, the result is that customer-facing employees end up using real-time analytics every moment of the day without even knowing what's under the hood.
As businesses build these capabilities, one of the biggest challenges they face is the quality of the underlying data - a problem that costs companies worldwide billions every year. In February 2005, the research firm Forrester said 30 percent of the respondents to its latest data warehousing technology survey had actually missed deadlines in closing financial books and related statutory reporting due to information and data quality issues.3
This is a scary statistic. Investing in sophisticated analytics while the underlying data remains dirty or inaccessible is a waste of money. Dirty data plus good analytics will simply produce bad information and poor outcomes.
A second major barrier to effective analytics is scarcity of people skills. Analytics remains a specialized area where the right individuals with the right capability can make a massive difference. In developed countries such as the U.S., these people are in increasingly short supply. More and more companies are responding by outsourcing their analytics function and/or looking at the high-skill environments of global delivery centers such as India, where skills more available.
Ultimately, consumer-facing businesses are now more serious and sophisticated about analytics than ever before. The question is no longer what benefits analytics can deliver for data management. It is when it can deliver them.
More information on this topic is available in the new book Competing on Analytics: The New Science of Winning by Thomas H. Davenport and Jeanne G. Harris, Harvard Business School Press, March 2007.
Shari Rogalski is the global director of Accenture's Business Intelligence practice, which specializes in data warehousing, enterprise reporting, performance management and analytical applications. She has more than 15 years of experience in the business intelligence and data warehousing fields. She can be reached at firstname.lastname@example.org.
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