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Your Business, Competing on Analytics

Business analytics is the practice of monitoring and analyzing historical data from different sources and perspectives, and summarizing the data into useful knowledge that can be used to increase revenue, cut costs, or both.    The most forward thinking companies leverage their CRM and transactional data to compete on business analytics in ways that are incredibly compelling.
Successful data mining and business analytics solutions have shown to substantially improve a company's awareness of opportunities to drive sales and reduce cost.  Justifying a business analytics project however can be challenging because often times the results cannot be anticipated, in the same way you could expect ROI from a line-of-business application investment.  After all, business analytics wouldn’t be needed in the first place if we already knew what the results are!    While most business analytics solutions share a similar approach, tools and methods, each business analytics initiative has its own requirements and challenges that are unique to a particular set of data, and unique to specific business needs.

Popular Business and Monitoring Analytics Applications

Sales & Marketing Analytics (CRM)
Sales Analytics is the prototypical case of applying monitoring analytics solutions to address practical business needs. It is easy to recognize Sales Analytics being used by Amazon.com, eBay and other companies to 'predict' which products you might like to purchase, based on the products you are currently viewing.
An analytic algorithm can be devised to indicate similar products that other customers have purchased and are therefore more likely to sell in combination.  Showing combinations of products that have been purchased together is likely to increase sales and customer satisfaction.  Another example of Sales Analytics is customer segmentation and classification to target specific advertising or promotions.
Predictive Analytics
Predictive Analytics is used to analyze risk, forecast events, and monitor other conventional types of business analytics.   Predictive analytics encompasses a variety of techniques from statistics and data mining that analyze current and historical data, in an attempt to predict future events by identifying patterns and trends in the data.
For example, for investment managers, predictive models can exploit patterns in historical and transactional data to identify potential risks and investment opportunities.  Predictive Models can capture relationships among many factors to allow assessment of risk or potential associated with a particular set of investment conditions, guiding the purchase and sales process.  Predictive analytics are also used heavily in insurance, telecommunications, retail, travel, healthcare and pharmaceutical industries.
Healthcare Analytics
The medical and pharmaceutical fields actively use business analytics to provide clues as to who might get sick, and the types of diseases certain patients are susceptible to based upon empirical (evidence-based) data on which diseases tend to occur together, or attact a particular demographic.   Healthcare analysts use business analytics to help predict which drugs are likely to work, and to determine the potential negative affects when used in combination.   Consultants also use Healthcare Analytics to predict influenza outbreaks, and which vaccines are likely to work best.
Financial & Insurance Analytics
Financial and insurance companies use business analytics extensively to detect fraud, as well as look for new demographic trends. Insurance Analysts attempt to predict catastrophic weather patterns so that they know to set higher premiums on high-risk areas.  One of the most well-known monitoring analytics applications is credit scores that are used to rank-order individuals by their likelihood of making future credit payments on time.  The less likely an individual is to make payments on time, the more they are worth in terms of late fees, and hence the more money the financial institution is willing to pay to get their business!
Web Analytics
Web Analytics, including Google Analytics, Yahoo! Web Analytics and MSN Analytics, and many others, are becoming the most pervasive uses of monitoring analytics. Perhaps you are here on our site because of the advanced analytic techniques that PCA uses to attract the right visitors! If you are interested in Web Analytics, Relational Database Applications, Smart Client Applications or Data Analytics, then it’s working!
The goal of Web Analytics is to optimize web site content and meta-data for particular keywords and topics to support both SEO (organic) and PPC (paid ads), so that your web site will attract only the right type of visitor interested in purchasing your product or services. Effective Web Analytics does not look to attract the most visitors, but rather aims to attract more visitors that convert into sales for your company.

Practical Limitations

As your SQL database grows in size and complexity, the ability to derive meaningful business intelligence using traditional SQL Server Reporting Services queries can become complex, time-consuming and sometimes nearly unmanageable.   This is because many valid, business-critical questions are either: difficult to formulate in a SQL query (For example, "Find all customer records that are similar to this customer's problem."), or, the question can be formed in a query but take extraordinary amounts of time and processing power to execute, and is therefore impractical.    In fact, gathering and maintaining huge amounts of data without the ability to extract meaningful intelligence will lead you further away from a return on your investment.