According to Information Week’s 2012 Business Intelligence, Analytics, and Information Management Survey, if there’s one dominant trend in BI and information management, “it’s the meteoric rise of analytics, particularly advanced statistical and predictive analytics.”
For the third consecutive year, “survey respondents rate advanced analytics as the most compelling among a dozen leading-edge technologies.”
The report speculates that the high-priority status of analytics is closely related to the rising interest in big data as a tool for mitigating risk, predicting customer behavior, and developing new product or service offerings.
So it’s not surprising that “advanced data visualization capabilities” and “embedded BI” closely followed “advanced analytics” in the survey ranking.
After all – easy access and effective delivery are key factors for getting the most out of analytics.
Data can offer a peek into business conditions weeks or months out, if you have the right predictive analytical tools.
The old practice of following the money–using lagging financial indicators to guide a company’s decisions–is giving way to the forward-looking approach of following the data.
Name a business scenario, and you can likely apply advanced analytic techniques to make better, more preemptive decisions rather than react to failures later. That’s the key contrast with what’s now disparagingly dubbed “rear-view mirror BI.”
Today many businesspeople don’t really know what predictive modeling, forecasting, design of experiments or mathematical optimization mean or do, but over the next 10 years, use of these powerful techniques will have to become mainstream, just as financial analysis and computers have, if businesses want to thrive in a highly competitive and regulated marketplace.
Business intelligence has long been associated with activities that explore and extrapolate on historical data. Summary statistics, queries, reports, and even threshold-triggered alerts and low-latency dashboards based on historical information are rear-view mirror. They provide a picture of where you’ve been.
The use of analytics that include statistics is a skill that is gaining mainstream value due to the increasingly thinner margin for decision error. There’s a requirement to gain insights and inferences from the treasure chest of raw transactional data that so many organizations have now stored (and are continuing to store) in a digital format. Organizations are drowning in data but starving for information.
Advanced analytics applies statistical and predictive algorithms to come up with calculated, predictive measures, scores, and models.
It shows where you’re headed. Advanced Analytics a game changing opportunity.
In closing let me share with you some comments from Tom Davenport:
There is always risk when decisions are made based on intuition, gut feel, flawed and misleading data or internal politics. In his popular book, Competing on Analytics: The New Science of Winning, he makes the case that increasingly, the primary source of attaining a competitive advantage will be an organization’s competence in mastering all flavors of analytics. If your management team is analytics-impaired, then your organization is at risk.
