in more or less dramatic ways; relational
frequencies such as line graphs show data
that is diverging or converging and are used
to report changes over time. Each type of
graph produces a specific impact and should
be considered based on the purpose of shar-
ing the data (Boudette, City and Murnane).
Once soft data are collected, triangulated
and purposefully displayed, the process of
identifying root causes can begin. This pro-
cess, when implemented with teams patient
enough to forgo the first or second suggested
causes, opting instead for deeper probing,
can unearth real root causes.
Identifying root causes
Examining purposefully presented soft
data can lead to root causes often missed by
asking the wrong questions, not asking any
questions, focusing on the wrong data, look-
ing at the right data the wrong way, or blind-
ness. The root cause is the deepest underly-
ing cause of positive and negative symptoms
within any process that, if resolved, would
result in elimination, or substantial reduc-
tion of the symptom (Preuss, 2003).
22
Leadership
A cause is likely to be a root cause when:
• You run into a dead-end asking what
caused the proposed root cause.
• There is consensus on the root cause.
• The cause makes sense and provides
clarity to the problem.
• If addressed, there is realistic hope that
the problem can be reduced or prevented in
the future (Ward, Frey, Fisher, 2012).
Dealing with root causes of many school-
related issues may not be easy because ef-
fectively responding often requires shifting
mindsets, changes in behaviors, facing ugly
truths, seemingly giving up status or control,
organizational and even paradigm shifts.
All of which may be difficult to accomplish.
Unlike hard data that provides a snapshot
of a point in time, soft data can provide in-
sight into why or how such hard data find-
ings exist. When acquired using methods
that ensure validity and reliability and when
displayed in engaging ways, root causes
of student performance can be identified
and addressed. This can ultimately lead to
extraordinary outcomes for students and
teachers alike.
Resources
• Boudette, K.P., City, E.A., Murnane,
R.J. (2007). “Data Wise: A step-by-step
guide to using assessment results to improve
teaching and learning.” Cambridge Massa-
chusetts: Harvard Education Press.
• James-Ward, C., Frey, N. and Fisher,
D. (2012, October). “Root cause analysis.”
Principal Leadership, 13(2), 59-61.
• James-Ward, C., Fisher, D., Frey, N.,
and Lapp, D. (2013). “Using data to focus
instructional improvement.” Alexandria,
VA: ASCD.
• Preuss, P. (2003). “School leader’s guide
to root cause analysis: Using data to dissolve
problems.” Larchmont, NY: Eye On Educa-
tion.
Cheryl James-Ward, Ed.D is a professor
at San Diego State University in the
Department of Educational Leadership
and chief of academic innovation for e3
Civic High School in San Diego, rated
by CNNMoney as one of the top most
innovative schools in the nation.