Gut instincts may be fine when making one's picks in the weekend football pool, but a recent survey indicates that more and more business executives plan to use analytics to help them with future corporate decisions.

According to an Accenture survey of executives working at U.S. companies with annual revenues of $500 million or more, 68 percent believe their company has to improve their analytical capabilities to remain competitive, and more than seven in 10 say their company is working to increase its future dependence on business analytics. Similarly, nearly three quarters of these executives believe the executive leadership of their company is committed to business analytics and has a corporate strategy and distinctive capability supported by it.

The Opportunity

Analytics provide a growing opportunity for businesses due to both market and business drivers. The software that drives data applications today is more sophisticated, easier to use and more readily available. Plus, savvy managers realize the business benefits in turning to data analysis, which combines traditional BI with real-time or predictive modeling to develop new opportunities that can differentiate them from the competition.

Studies show that maturing analytics capabilities help organizations achieve high performance by maximizing the valu

e from data through smart analysis and resulting insights. Sound integration between analytics and technical concepts like SOA can reinvent how business and public service agencies operate.

High performance IT organizations use analytics to begin to predict and influence customer behavior, product uptake, supply chains and market behavior in ways that impact the bottom line. More specifically, they can:

  • Generate customer insights. This involves modeling customer behavior, identifying the most profitable customer segments, tracking loyalty and honing cross- and up sell strategies. 
  • Accelerate product innovation. This allows an organization to correlate market opportunity, customer requirements, R&D and service data to develop more effective products, understand market gaps and maximize the cross-sell potential of new offerings.
  • Optimize the supply chain. This entails identifying key metrics for efficient planning in order to create accurate demand forecasts, optimize inventory and warehouse procurement, and create the best pricing.
  • Understand financial performance. As a result, the organization can pinpoint the true drivers of positive financial performance to translate competitive knowledge into actionable strategies for maximizing revenues.

As an example, consider financial institutions, which often suffer from multiple versions of the truth as a result of data generated, collected and presented inconsistently and in piecemeal fashion. Through analytics, banking CEOs can now visualize how different value drivers link with the bank's objectives through a strategy map. Banks can then measure metrics such as sales, operational efficiency and/or customer satisfaction, which they view as vital to their strategic goals, and CEOs can translate these goals into more concrete targets for individual subunits and monitor the actual data coming in against those targets.
Similarly, analytics can help executives quickly assess the state of their workforce, thereby forecasting potential future gaps and shortcomings. This provides a fact-based approach that will allow them to drill down to find more detailed information and uncover the cause of problems that will allow them to keep the workforce enabled, motivated and focused. This means improved executive decision-making that results from the ability to track and focus HR initiatives, and lower costs and IT/HR reporting workloads.

The bottom-line benefits can be significant. Yankee Group, an independent technology research and consulting firm, estimates that organizations can realize up to a 20 percent profit improvement by using price management and profit optimization solutions that are available through business analytics.

Survey Reveals Challenges

While executives are aware of the opportunity afforded by business analytics, many note a gap between where they are today and where they hope to be tomorrow. According to our survey, 60 percent of business decisions are currently based on analytics and 40 percent on judgment (when good data is not available, when there is no past data and/or when there are subjective/qualitative factors).

Institutional hindrances apparently need to be addressed to improve business analytics capabilities. The survey found that 39 percent view IT capabilities as a major challenge and 27 percent perceive an inability to share these capabilities across organizations within the company. In fact, only 40 percent claim to have an enterprise-wide analytical capability.

Challenges need to be resolved before many organizations can begin to use analytical capabilities effectively. This starts with the need to move many companies from a silo approach to more inclusive information management programs that work across the entire organization.

It is not only about infrastructure investments. Many businesses also face an HR challenge. According to the survey, 23 percent listed "insufficient quantitative skills in employees" as a main challenge, and 36 percent report that their company "faces a shortage of analytic talent."

Our research has also found significant differences between the practices of high performance businesses and those of other companies when it comes to analytics. For example, high performance businesses:

  • Are five times more likely to use analytics than lower performers. Additionally, while 70 percent of high performers identify analytics as significant decision support, only 23 percent of lower performers do.
  • Use analytics to support key opportunities, such as identifying their most profitable customers and offering them the right price, accelerating product innovation, optimizing supply chains and finding the true drivers of financial performance.
  • Put abundant time and effort into developing information-driven organizations and improving the leveraging of knowledge gained through analytics to drive their business-improvement initiatives.

Analytics Capabilities

Accenture has defined six kinds of analytics capabilities:

Real-time decision-making. Instant feedback allows organizations to capitalize on opportunities earlier and in a more targeted fashion. An example is the work Accenture did with the Shenzhen tax bureau in China, where innovative services such as "Easy Tax" provided taxpayers with online, phone, text messaging and kiosk access to their tax matters at any time of the day.

Predictive monitoring. The combination of structured and unstructured data can give an organization a clearer view of customer preferences and existing and future maintenance of corporate assets, as well as present certain assumptions about future activities. An example is the practices of the coaching staff and management of the New England Patriots football team, which has become a dynasty in the NFL by focusing on predictive monitoring techniques that employ data around players and performance.

Text mining. This allows lawyers, regulators and executives to view email as a major source of evidence and facts. As an example, the U.K. police analysts in local municipalities have learned that the right data can tell them which juveniles are most likely to become hardened criminals as adults, creating opportunities for early intervention.

Sentiment monitoring. Organizations use this to help track fluctuations in their brand image and gauge customer opinions on the Internet. The tool searches through a set of preselected sites for opinions that are relevant and uses a language analyzer to categorize each one as positive, negative or neutral in order to build a picture of prevailing opinion. This fosters awareness of thoughts and ideas that organizations would either spend hours compiling under normal circumstances or perhaps never hear at all from traditional market research channels.

Voice mining. Organizations are using this tool to determine how to handle calls more efficiently. For example, a call center's voice mining can be applied to train staff to better handle customer queries and issues. Emotion detection and talk analysis can help evaluate a customer experience issue.

Video analysis. Accenture Labs has developed a Visual Shelf Monitoring prototype that leverages cameras located through a retail store and sophisticated object-recognition technology to monitor product placement on store shelves. When it detects a stock-out, for example, an alert is automatically generated and the store can rectify the situation immediately, thereby maximizing sales.

Companies with enterprise-wide business analytics have a strong competitive advantage over those who are still relying on gut instincts to make their decisions. The existing challenges notwithstanding, business leaders are now viewing analytical capabilities as a powerful differentiator, one that promises a range of significant business benefits that will impact the bottom line.

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