Uncover the Truly Maximum Profit Opportunity of a Prospective M&A Deal: Next Generation M&A Financial Analysis Capability

DOIhttp://doi.org/10.1002/jcaf.22118
Date01 January 2016
Published date01 January 2016
23
© 2016 Wiley Periodicals, Inc.
Published online in Wiley Online Library (wileyonlinelibrary.com).
DOI 10.1002/jcaf.22118
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Uncover the Truly Maximum Profit
Opportunity of a Prospective M&A
Deal: Next Generation M&A Financial
Analysis Capability
Alan Dybvig
This article is
divided into
five sections: (1)
Introduction; (2) The
Role of Analytics in
M&A Analyses; (3)
Review of the Three
M&A Financial
Analytics Relevant to
This Article; (4) Lim-
itations of Current
M&A Financial Ana-
lytics and How an
OIS Addresses Them;
and (5) Conclusions.
Finally, some possible
future articles are
discussed.
INTRODUCTION
This is the fourth
in a series of articles the author
has published in this journal
within the last 18 months. They
constitute a series describing
(1) what the basic optimized
income statement (OIS) value
proposition is, including its two
foundational structural ele-
ments; and (2) ways in which
an OIS can be applied. The
first OIS structural
element is that it is
activity based, which
is described in the
first two articles, and
the second is that it
is demand driven,
which is described in
the thirdarticle.1
Because OIS is
both activity based
and demand driven,
it can relax both
of the traditional
income statement
assumptions of a
fixed supply chain
and a fixed forecast.
This allows OIS’s
prescriptive solver
to answer the ques-
tion: “What is the
best possible outcome (X)?”
In OIS’s case, it is an income
statement containing (1) the
truly maximally profitable fore-
cast, (2) the optimally feasible
By integrating three analytic techniques already in
use, separately, for merger and acquisition (M&A)
financial analysis, it will be demonstrated that
an optimized income statement (OIS) represents
a “next generation” financial analysis capability
for M&A and private equity portfolio manage-
ment. The three techniques currently in use are
(1) mixed integer and linear math programming
(MILP) for least-cost supply chain design, (2)pre-
dictive analytics for sizing and allocating sales
and marketing expenditures more profitably, and
(3) activity-based costing (ABC). ABC data avail-
ability can substantially reduce the cost and time
required to implement the MILP portion of an OIS
model. It also improves the profitability of the M&A
analysis beyond that available with OIS analyses
conducted without ABC detail. © 2016 Wiley Periodicals, Inc.
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