Friday, June 22, 2012

BIG DATA Spurs Economic Growth


This is exactly what I mean when I tell institutional owners to Googlize the data associated with the procurement of facilities & infrastructure so you can leverage it in operations & maintenance!

Manufacturing Money Ball

The article is well worth the read.  Below is a quote outlining principals leaders in the built industry would do well to consider carefully.


The manufacturing equivalent of Beane’s strategy is (i) to find hidden data—and specifically real time data at both aggregate and granular levels; (ii) to apply advanced computational methods to mine that data; (iii) to understand the multivariable data’s interconnectedness; and then (iv) to optimize traditional manufacturing processes accordingly. Linda Onnen, Global Marketing Director of GE Intelligent Platforms, told me recently by phone that Big Data allows for precisely the sort of multivariable analysis required to identify those links and then analyze them to generate actionable intelligence.
A manufacturer’s ability to achieve these goals depends on the same two variables that Beane and DePodesta used to evaluate talent and turn around a franchise: good information and analytics that lead to actionable intelligence. Gartner writes:
The quality of the[se] outcomes is strongly linked to the quality of the data being collected and the manner in which it is stored, analyzed, visualized, and converted into meaningful and valuable sustainable business intelligence (BI).
The multivariable analysis to which Onnen refers depends on at least three factors:
  1. Data transparency that allows data from different manufacturing functions to be integrated. This allows executives to form a holistic view of the processes never before possible.
  2. Process visibility that allows managers to see how processes unfold as they happen, which allows for real-time adjustments.
  3. Data visualization. As analytics are applied to Big Data, the output must be analyzed mathematically and represented visually so as to allow end users such as plant managers to actually see the hidden data and its value. This is especially important in light of the fact that the data is dynamic in real time.
Multivariable analysis allows organizations to see both their informational assets and shortcomings.

Welcome to the Collaborative Revolution!
James L. Salmon, Esq.
Collaborative Construction
300 Pike Street
Cincinnati, Ohio 45202
Summary of Services and James L. Salmon's CV
Office 513-721-5672
Fax 513-562-4388
Cell 512-630-4446
JamesLSalmon@gmailcom
Collaborative Construction Website
Sustainable Land Development International

1 comment:

marklouis983 said...

Very nice post. thank you so much sharing this Post. mark louis