As a builder of cost estimation models, I am constantly look for new sources of data and new ideas and technologies focused on the analysis of this data.  For this reason I like to keep my finger on the pulse of what’s happening in the world of Big Data and Predictive Analytics.  Towards this goal I happened upon an interesting post the other day that I thought I might share.  While it has nothing to do with cost estimation or cost estimating models, it does shed some pretty interesting light on the ways that the technology around predictive analytics can be used to answer so many questions.

The title of the post is “Predictive Analytics – Rhinos, Elephants, Donkeys and Minority Report.” (  The post refers to a study published by the IEEE Computer Society that describes how data analysis and artificial intelligence algorithms were used to track activities of rhinos and poachers in an effort to create a safer environment for rhinos.   The author then goes on to describe how politicians and pollsters alike use their own predictive analytics processes to determine whether the elephants (Republicans) or donkeys (Democrats) will dominate in November of 2016.  Data analytics assist a campaign in countless ways: identification of potential donors, determination of the best ad campaigns based on demographics of specific regions, determination of where best to focus ‘get out the voter’ initiatives, etc.

Predictive analytics uses technology to process large amounts of data to inform good decisions.  Sounds a lot what a cost modeler (or cost model builder does).  I am certainly not suggesting that predictive analytics are necessary to model costs – cost modeling technology predates big data analytics by centuries.  What I am suggesting is that the cost modelers of the world start to look into technologies that will enable them to better understand more quantities and types of data, to better inform the cost estimates they are developing.  At PRICE Systems we are developing and using technology to support better cost estimates through using very cost focused analytics.