Armin Cruz on Nested
Metrics
A Framework to
Business Strategy
Armin Cruz is a Six Sigma Master Black Belt that specializes
in LEAN methodologies in the financial transactional industry. Armin Cruz received his MBB while serving as
a Vice President at Bank of America’s Process Excellence division. Armin currently serves as Director and Head
of Continuous Improvement for a public firm in the financial real estate and
property management industry. Armin Cruz earned his MBA from the University of
Phoenix, and his BA from the University of Texas at Dallas. Armin Cruz lives in north Texas with his
wife, three dogs and is anxiously awaiting his first baby boy in December.
Often times the process-centric executive faces two problems
simultaneously. First, one may face a
daunting and complex volume of business problems. Additionally, you, as the line of business executive
may have a lack of clarity in your reporting and data. To find a brief presentation on solving
business problems please search SlideShare for a presentation titled “4 Steps
to Solving Business Problems.”
Once you know how to solve the problem, the operational
excellence coach must consider the current reporting strategy. Many organizations experience two dimensions
of fallacies with data interpretation.
First, when organizations are heavily siloed and dependent upon their
own reporting the unit may experience a bias.
The second dimension is in the nested hierarchy, or better a lack
thereof. The metrics and reporting
system should (but often does not) have a nesting relationship in that one
metric should flow to a group of metrics.
Then the group rolls up to an indicator, the indicators to a Key
Performance Indicator (KPI). This way,
when you are at the top of the data model you know if you pull a lever what
actions to expect at the ground level.
This leads us to the data quality issue. Those familiar with statistical measures of
control and analysis may be familiar with the “signal to noise ratio” and the
value it brings to a line of business leader.
In order to facilitate strong business decisions the data presented
needs to possess a strong signal to noise ratio. This topic/concept is more complex than the
scope of this article, however, at a minimum reach out to a statistician or Six
Sigma Master Black Belt to perform a detailed analysis. This process driven expert will be able to
advise on a course of action to ensure this is a non-issue. In general, one way to calculate this is to
take the difference between the sample mean and the mean of the hypothesized
value divided by the standard deviation over the square root of the sample
size. The higher the numerator in relation
to the denominator the stronger the ratio, and the less noise you have in your
data.
For more information about this topic, please read my Slide Share
title “4 Steps to Solving Business Problems.”
You may also reach out to me on my personal website and request more
detailed information.
Point of Contact:
Name: Armin Cruz
Phone: (972) 333 – 9502
Email: armin.j.cruz@hotmail.com
Website: www.armincruz.us
SlideShare: www.slideshare.net/ArminCruz
Twitter: http://www.twitter.com/ArminJCruz
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