Decisions without Data – what we can learn from Punxsutawney Phil

by | Feb 2, 2018 | Business Intelligence, Collaboration | 0 comments

It is that time of year again.  Punxsutawney Phil, that Prognosticator of Prognosticators, will emerge from his burrow and tell us if there will be 6 more weeks of winter or an early spring.  I personally have never fully understood how the shadow interpretation process was determined since one would think a clear, sunny day would be an indicator of nice weather ahead.  But I digress…

According to LiveScience, Phil is only correct about 39 percent of the time.  You would think after about 120 years of doing this he would be a bit more accurate.  Maybe he is just a little groggy from being awakened during his winter hibernation.  Or – maybe Phil should consider investing in a Business Intelligence solution to help provide more data for making better predictions.

Business Intelligence and Predictive Analytics

With the growing volumes and types of data, we need to leverage tools to allow us to effectively collect and interpret information to make decisions about our organizations.  Manually compiling and massaging data no longer scales in the fast-paced world of business today.  Computers have become faster and cheaper, and Business Intelligence (BI) tools have become cost effective and incredibly user friendly.

BI tools can also allow you to blend data from a variety of sources in order to have a complete picture.  For example, going back to our friend Phil, today he has limited information for decision making: do I see a shadow or not?  I wonder how his accuracy might increase if he had insight into the current temperature patterns, wind speed, wind chill, humidity, precipitation, etc.  A more holistic view of all of the data about the current conditions that he needs to know in order to do his job effectively.

Additionally, with interactive and easy-to-use software becoming more prevalent, predictive analytics is no longer just for mathematicians and statisticians.  These tools can now be leveraged by business analysts and other users throughout the organization to gain valuable insights.  Now, Phil would not only have access to the data discussed earlier for that point in time, but could use historical patterns of that data to predict out the next 6 weeks of weather.

These technologies are helping organizations both solve difficult problems and uncover new opportunities.  For example, in the world of cybersecurity predictive analytics are helping uncover behavioral anomalies in user actions and networking activity.  Organizations are leveraging this same technology to determine customer buying behaviors and promote cross-sell opportunities.  Manufacturing companies are using them to predict maintenance issues before they happen to reduce operational downtime.  The possibilities are endless!.

Being from Chicago, I hope this year’s prediction is an early Spring (and I hope it is accurate).  To learn more about how Business Intelligence can help your organization contact us at  We are happy to help!