You're no match for contenders if your business data is tied up in knots.
Optimization is the linchpin of most viable competitive strategies. Rather than try to satisfy every consumer, companies adopting these strategies focus on optimal customersthose with the highest level of profitability and lifetime value. Instead of receiving goods and services whenever they happen to arrive, companies attempt to optimize supply chains to minimize disruptions and in-process inventory. Rather than make adjustments after the fact, they accurately predict which measures will yield optimal results. And they don't throw money at the problem, but seek to maximize their use of capital.
For proponents of optimization, taking business as it comes is not the way to go. On the contrary, optimization strategies require extensive data on the state of the business environment and the company's place within it. They also call for extensive analysis of the data to model that environment, predict the consequences of alternative actions, and guide executive decision-making. Moreover, these strategies require analysts and decision-makers who understand the value of analytics and know how best to apply them to enhance performance. Companies that strive to optimize their business performance using this data-intensive approach are competing based on analytics and analytical capabilities.
Sadly, the majority of companies pursuing optimization have failed to deliver the analytical capabilities necessary to make their strategies succeed. Although most large organizations, and many small ones, have business-intelligence (BI) tools in place, these are typically marginal to the success of the business and are managed at the departmental level. However valuable such tools may otherwise be, they're invisible to senior executives, customers, and shareholders, and they don't propel the competitive strategy.
Of course, a few businesses within financial servicesparticularly financial-investment and trading firmshave competed on analytics for decades. What's new is the spread of analytical competition enterprisewide, to companies in a variety of other industriesincluding consumer finance, retail, and travel and entertainment. For these organizations, analytics are becoming a primary competitive weapon. They use analytical tools to change the game, or to perform substantially better in the existing one.
When I studied 32 companies that were at least somewhat focused on analytics and BI, I found them at various stages of analytical orientation (see chart). The percentages of companies at each of these stages are by no means representative of any larger population; I intentionally sought out companies at the higher end of the analytical spectrum. I found five stages of analytical competition:
Stage 1Major barriers. Companies in this category have some desire to become more analytical, but lack the will and skill required. They face substantial barriers, both organizational and technical, and are still focused on putting basic, integrated transaction functionality in place. As a result, they're not yet on the path to becoming analytical competitors. Because I interviewed only companies that want to compete on analytics, I found only two at this stagebut such organizations probably constitute the majority of large businesses.
Stage 2Local activity. Companies at this juncture have made substantial progress in becoming more analytical, but their efforts have been primarily localthat is, limited to particular functions or units, such as marketing. The BI activities of these companies have produced economic benefits, but not enough to affect the company's competitive strategy. I found six of these companies in my survey. What they primarily lacked was a vision of analytical competition that came from senior executives.
Stage 3Vision not yet realized. Companies in this group grasp the value and promise of analytical competition, but are a long way from succeeding with it. I found seven businesses at this stage. Some have only recently articulated the vision and aren't yet implementing it. Others have very high levels of functional or business-unit autonomy, making it difficult to mount a cohesive approach to analytics across the enterprise. One multiline insurance company, for example, had a CEO with a vision of using data, analytics, and a strong customer orientation. But the company had only recently begun to expand its analytical orientation beyond the traditional quantitative actuarial function, and there was little cooperation across the life and property-and-casualty business units.
Stage 4Almost there. To qualify for Stage 4, companies must have the vision and be close to achieving it. Six of the companies I visited fell into this group. Some had only recently adopted an enterprisewide approach to analytical competition, and had yet to fully realize it in terms of marshaling the necessary resources. Others were competing in terms of analytics as well as other factors, such as maintaining strong personal relationships with customers. Only a small degree of added emphasis on analytical capability would place these companies at the top level.
Stage 5Analytical competitors. This top rank describes companies that have embarked upon analytical competition as their primary dimension of strategy. I was able to identify 11 of them: Apex Management Group, a health-care actuarial firm; Barclays Consumer Finance; Capital One; Harrah's; Marriott; Owens & Minor; Progressive; Wal-Mart; an unnamed consumer-products company; and two sports teams, the Boston Red Sox and the New England Patriots. Exhibiting all the attributes of analytical competitors described above, these businesses are highly successful within their industries and attribute their good fortune at least in part to their analytical strategies. Barclays, for example, says its analytically oriented information-based customer management strategy let it increase revenue per active account by 25% while reducing delinquent accounts by 23%.
These Stage 5 companies are committed to their analytical strategies from the bottom up, even to the level of the CEO. "We use database marketing and decision-science-based analytical tools to widen the gap between us and casino operators who base their customer incentives more on intuition than evidence," says Harrah's CEO Gary Loveman. (See the related article, Analytics @ Work.)
Amazon.com, to take another example, uses extensive analytics to predict which products will be successful, as well as to wring every bit of efficiency out of its supply chain. "For every leader in the company, not just for me, there are decisions that can be made by analysis," says Amazon CEO Jeff Bezos. "These are the best kinds of decisions. They're fact-based decisions."
But CEOs aren't the only executives who need to be involved in analytical competition. CIOs also have an important role to play. They can't single-handedly change the company's strategy or culture to emphasize analytics, but their work makes analytical competition a real possibility. Potential CIO-focused initiatives include fostering an analytical culture, building specialized analytical skills, establishing close relationships between analysts and decision-makers, and creating an analytical architecture.
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