Hurwitz & Associates conducted an online survey on advanced analytics in January 2011. Over 160 companies across a range of industries and company size participated in the survey. The goal of the survey was to understand how companies are using advanced analytics today and what their plans are for the future. Specific topics included:
- Motivation for advanced analytics
- Use cases for advanced analytics
- Kinds of users of advanced analytics
- Challenges with advanced analytics
- Benefits of the technology
- Experiences with BI and advanced analytics
- Plans for using advanced analytics
What is advanced analytics ?
Advanced analytics provides algorithms for complex analysis of either structured or unstructured data. It includes sophisticated statistical models, machine learning, neural networks, text analytics, and other advanced data mining techniques. Among its many use cases, it can be deployed to find patterns in data, prediction, optimization, forecasting, and for complex event processing. Examples include predicting churn, identifying fraud, market basket analysis, and analyzing social media for brand management. Advanced analytics does not include database query and reporting and OLAP cubes.
Many early adopters of this technology have used predictive analytics as part of their marketing efforts. However, the diversity of use cases for predictive analytics is growing. In addition to marketing related analytics for use in areas such as market basket analysis, promotional mix, consumer behavior analysis, brand loyalty, churn analysis, companies are using the technology in new and innovative ways. For example, there are newer industry use cases emerging including reliability assessment (i.e. predicting failure in machines), situational awareness, behavior (defense), investment analysis, fraud identification (insurance, finance), predicting disabilities from claims (insurance), and finding patterns in health related data (medical)
The two charts below illustrate several key findings from the survey on how companies use advanced analytics and who within the organization is using this technology.
• Figure 1 indicates that the top uses for advanced analytics include finding patterns in data and building predictive models.
• Figure 2 illustrates that users of advanced analytics in many organizations have expanded from statisticians and other highly technical staff to include business analysts and other business users. Many vendors anticipated this shift to business users and enhanced their offerings by adding new user interfaces, for example, which suggest or dictate what model should be used, given a certain set of data.
Other highlights include:
• Survey participants have seen a huge business benefit from advanced analytics. In fact, over 40% of the respondents who had implemented advanced analytics believed it had increased their company’s top-line revenue. Only 2% of respondents stated that advanced analytics provided little or no value to their company.
• Regardless of company size, the vast majority of respondents expected the number of users of advanced analytics in their companies to increase over the next six to 12 months. In fact, over 50% of respondents currently using the technology expected the number of users to increase over this time period.
The final report will be published in March 2011. Stay tuned!
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