Enterprise Master Plan: Next‐Generation Planning With Activity‐Based Costing

• Author: Alan Dybvig,Jeff Karrenbauer,John Miller
• Published date: 01 May 2015
• Date: 01 May 2015
• DOI: http://doi.org/10.1002/jcaf.22053

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© 2015 Wiley Periodicals, Inc.

Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/jcaf.22053

This article was originally published in Volume 25, Number 4 of The Journal of Corporate Accounting and Finance.

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Alan Dybvig, Jeff Karrenbauer, and John Miller

Imagine relaxing the assumption of a fixed sales

forecast to solve for the optimum level of sales and

marketing spending that will provide the maxi-

mum profit and return on investment. This article

and case study explains how. © 2015 Wiley Periodicals, Inc.

E nterprise Master Plan: Next-Generation

Planning With Activity-Based Costing

Ten years ago the

Consortium of

Advanced Man-

agement International

(CAM-I), an acknowl-

edged leader in

activity-based costing,

published The Closed

Loop , 1 one of the first books

on activity-based planning and

budgeting (ABPB). Since that

time, most activity-based cost-

ing (ABC) software providers

have added additional capabil-

ity and application for ABPB.

Starting with a fixed sales fore-

cast and sales/marketing spend,

almost all of the operating

data required for the ABPB is

readily available in most ABC

models.

What’s been missing is the

ability to optimize a plan based

on a level of sales and market-

ing spending that will provide

both the maximum profit

and return on investment. No

longer is that true. The next

generation is enterprise master

planning (EMP), where both

the optimized forecast and sup-

ply chain are solved simultane-

ously to maximize profitability

and the return on investment,

as illustrated in the graphic

representation set forth in

Exhibit 1.

There are five factors neces-

sary for developing a maximally

profitable annual plan:

1. The forecast must be vari-

able in the driver-based

plan model.

2. The supply chain must be

variable in the driver-based

plan model.

3. The objective function

(i.e., what you’re trying

to optimize) must be

profit.

4. The solver must be pre-

scriptive (“what is the best

X? ”) and not scenario anal-

ysis (“What will happen if

we do X? ”).

5. The model must be solved

simultaneously to develop

an EMP that incorporates

all five factors.

Specifically,

the EMP is created

using modeling

software that inte-

grates three plan-

ning techniques, all

of which have been

commercially avail-

able for decades:

1. Supply chain network

design

2. Activity-based costing

3. Marketing-mix modeling

The supply chain software

relaxes the assumption of a fixed

supply chain, uses profit as the

objective function, and has a

prescriptive solver. ABC models

provide the data for the cost

functions in an EMP by which

the assumption of a fixed sup-

ply chain are relaxed. ABC cost

functions are more conveniently

developed than those tradi-

tionally developed and are the

reason the case study example

could be developed as described

below. Finally, the assumption

of a fixed sales (units) forecast

is relaxed by response functions

developed in traditional market-

ing-mix modeling software.