In these times of economic uncertainty, companies must adapt quickly to changes in the revenue stream and find ways to stay competitive and profitable, even with substantially reduced staff due to lower revenues. To gain competitive advantage, most companies are digging deeper into their volumes of data and turning to real-time analytics.
Let’s consider some real scenarios that companies face today:
• A high-tech company wants to develop a microchip that would perform advanced analytics in real time, to be used by the retail industry in digital signage. This microchip would decrease the cost of advanced analytics by millions of dollars and allow retail companies to conduct real-time marketing analytics campaigns.
• A social media company wants to use real-time advanced analytics to improve its click- through rate by 20% by matching targeted advertisements to users.
• A healthcare payer is losing membership due to layoffs among its client base, and its revenues are decreasing. The company needs to develop a comprehensive cost containment methodology in pharmacy benefits, radiology and other high-cost medical categories. To do this, it wants a real-time analytics system that can identify and proactively provide solutions to these problems and potentially replace some of its labor-intensive operations in the claims processing area.
• A casualty and property insurance company faces declining revenues due to the inability of policy holders to pay their premiums because of job loss. With pricing optimization a key product differentiator in the marketplace, the company wants to use analytics to increase profitability by identifying and providing potential solutions in high-cost areas by deploying an early warning system.
• An international consumer packaged goods company is experiencing decreased sales and wants to gain back market share by utilizing analytics in the areas of foresight, blind spots, portfolio optimization and consumer insights.