Staying demand driven 2

SUPPLY CHAIN MANAGEMENT
Becoming
Demand Driven
How to Change from Push and
Promote to Position and Pull
PART 2 OF 3
No v emb e r 2 0 1 3 I S T R AT E G I C F I N A N C E 37
By Debra Smith, CPA, and Chad Smith
The first article in our series stressed three key points:
1. The way to drive return on investment (ROI) has everything to do with
protecting and increasing the flow of relevant information and materials
through a company.
2. Supply chains have changed dramatically in the last two decades—
becoming nonlinear, complex systems. The rules and the math governing
complex systems are different from the rules governing linear systems.
3. The current focus of people and systems on unit cost minimization has
little or no connection to driving ROI. It distorts the picture, fails to produce
relevant information to drive decisions and actions, and introduces self-inflicted
forms of variability that contribute to the bullwhip effect. This unit
cost emphasis is typically called push and promote.

The push-and-promote mode of operation must
change, and the old rules based on cost-centric efficiency
must go. Companies must embrace the new position-and-
pull mode of operation and adopt flow-centric effi-ciency
rules that protect and maximize the flow of
relevant materials and information. Position and pull
aligns resources and efforts with actual market and cus-tomer
requirements to successfully manage the more
variable, volatile, and complex environment of today. To
get to position and pull, companies must become
Demand Driven.
How to Become Demand Driven
Becoming Demand Driven essentially is forcing a change
from the conventional supply- and cost-centric model to
a flow- and demand-pull-centric model. Going from
push and promote to position and pull involves five steps:
1. Accept the New Normal,
2. Embrace flow and its implications for ROI,
3. Design an operational model for flow,
4. Bring the Demand Driven model to the organization,
and
5. Use smart metrics to operate and sustain the Demand
Driven operating model.
We covered Steps 1 and 2 in Part 1, and here we’ll dive
deeper into Steps 2 and 3.
Step 1: Accept the New Normal
As we discussed in our first article, volatility and variabil-ity
are magnitudes greater than the supply chains our
current tools and rules were developed to manage. Our
conventional set of rules, tools, and metrics (based on
linear assumptions) fail to provide relevant information
for operational planning and execution in these new cir-cumstances.
Companies have a choice. They can accept
these new circumstances and adjust accordingly, or they
can face an increasingly uphill battle and be left behind in
a hypercompetitive landscape.
Step 2: Embrace Flow and Its Implications
for ROI
We also previously discussed George Plossl’s first law of
manufacturing:
All benefits will be directly related to the speed of flow
of information and materials.
The New Normal, however, has created the need for a
very important caveat to this law: The information and
materials must be relevant to the market/customer
expectation—actual demand pull. When the flow of rele-vant
information and materials speeds up or is protected,
revenue opportunities are maximized or protected, inven-tory
is minimized, and unnecessary expenses are elimi-nated.
Thus a company’s success in relation to ROI is
determined by its ability to manage time and flow from a
systemic perspective: Minimum investment and cost are
an outcome of flow, and an efficient system protects and
promotes flow. All rules, tactics, tools, and metrics must
be aligned to the speed of flow as well as identify and
remove whatever blocks flow. The one thing most process
improvement philosophies agree on is that the No. 1 enemy
of flow is variability. The accumulation, transference, and
amplification of variability—not any single discrete
process’s variability—are what kill system flow.
In addition, we explained system variability and exposed
the conventional cost-centric efficiency strategy as one of
the major sources of variation in today’s supply chains. Its
rules, tools, and metrics inject directly competitive tactics
and modes of operation with a flow-centric efficiency
strategy’s rules, tools, and metrics. Attempting to satisfy the
opposing rules, tactics, metrics, and actions between the
two constantly flips an organization between competing
and opposing modes of operation. This management oscil-lation
is actually self-induced variation and represents a
huge opportunity to improve flow performance and ROI.
Why? Because it’s under our direct control!
Part of understanding why a change is required is to
know and quantify what opportunities are currently
being missed by continuing in the status quo. It’s possible
to quantify the gap between the cost-centric world of
push and promote and the flow-centric world of position
and pull. The formula in Figure 1 expresses the gap
between the strategies and the importance of relevant
information. It quantifies the potential system improve-ment
or degradation in moving from one world to the
other with the following points:
Visibility is defined as relevant information for
decision making.
Variability is defined as the summation of the differ-ences
between what we plan to have happen and what
happens.
Flow is the rate at which a system converts material to
product required by a customer.
Cash velocity is the rate of net cash generation; sales
dollars minus truly variable costs (also known as
throughput dollars or contribution margin) minus
period operating expense.
Net profit/investment is, of course, the equation for
ROI.
38 S T R AT E G I C F I N A N C E I No v emb e r 2 0 1 3

Figure 1: The Gap Formula Between Flow-Centric and Cost-Centric Strategies
A change in visibility causes a change in variability, and
that in turn causes a change in flow and ultimately ROI.
This formula starts at what makes information rele-vant,
not at flow. If we don’t fundamentally grasp how to
generate and use relevant information, then we can’t
operate to flow. Moreover, if we’re actively blocked from
generating or using relevant information, then even if
people understand there’s a problem, they will be power-less
to do anything about it. The core problem plaguing
most supply chains today is the inability to generate and
use relevant information to drive ROI.
Step 3: Design an Operational Model for Flow
The Demand Driven operating model is the positioning
part of position and pull. To get the positioning right,
two things are required:
Identification and placement of decoupling and con-trol
points, and
Consideration of how to protect those decoupling and
control points from the effects of variation.
Decoupling Points
If return is related directly to our ability to protect and pro-mote
flow and if variability is the biggest enemy to system
flow, then we have to design a system that breaks the vari-ability
accumulation chain. This is called a decoupling point.
Decoupling point—the location in the product structure
or distribution network where strategic inventory is placed
to create independence between processes or entities. Selec-tion
of decoupling points is a strategic decision that deter-mines
customer lead times and inventory investment. (See
APICS Dictionary, 14th edition, APICS The Association
for Operations Management, 2013, p. 43.)
Decoupling points represent a place to disconnect the
events happening on one side from the events happening
on the other side. They delineate the boundaries of at least
two independently planned and managed horizons and
are most commonly associated with stock positions. As a
stock position, they allow demand to accumulate (the
stock position drains) but allow the customers represented
by those demand signals to be serviced on demand with-out
incurring the lead-time penalty of the processes in
front of the decoupling point. Where to strategically place
decoupling points depends on careful consideration of the
six factors in Table 1.
We’ll use the example of an equipment manufacturer
to demonstrate the decoupling point considerations. The
longest lead time for raw stock in the component bill of
materials (BOM) is four weeks; commonly used compo-nents
typically take three weeks to manufacture; and the
Table 1: The Six Decoupling Point Positioning Factors
Visibility Variability Flow Cash Velocity
Net Profit
Investment ( ) ROI
Plossl’s First Law of Manufacturing and the Demand Core Problem Area Driven Model
Customer Tolerance Time The amount of time potential customers are willing to wait for delivery of a good or a service.
Market Potential Lead Time The lead time that will allow an increase of price or the capture of additional business through either
existing or new customer channels.
Demand Variability The potential for swings and spikes in demand that could overwhelm resources (capacity, stock, cash, etc.).
Supply Variability The potential for and severity of disruptions in sources of supply and/or specific suppliers. This can also be
referred to as supply continuity variability.
Inventory Leverage Flexibility The places in the integrated BOM structure (the Matrix BOM) or the distribution network that leave a com-pany
with the most available options and the best lead-time compression to meet the business needs.
Critical Operation Protection The minimization of disruption passed to critical resources or control points.
(Taken from the third edition of Orlicky’s Material Requirements Planning by Carol Ptak and Chad Smith, McGraw-Hill Professional, 2011, p. 392)

SHEAR
Figure 3: The Same System with Decoupling Points
SHEAR
LEAD TIME = 3 WEEKS LEAD TIME = 1 WEEK
OUTSOURCE
OPERATION
LEAD TIME =
4 WEEKS
time to assemble, paint, and configure an end item is one
week, for a total eight weeks’ lead time.
Figures 2 and 3 depict the conceptual difference
between a system with no formal decoupling points and
one with formal decoupling points. The bucket icons in
Figure 3 represent the decoupling points. The lines run-ning
through the decoupling point icons represent the
indirect connections between the two independently
planned and managed sides of the decoupling point. In
our example, Sales and Marketing has determined that
offering one-week lead times would be a significant com-petitive
advantage. This requires the placement of decou-pling
points to ensure material is available to the
assembly, paint, and configure operations to meet the
agreed-to market strategy lead time of one week.
Decoupling lead time is important because:
1. Adding the longest path of decoupled lead times still
produces a similar lead-time number as the coupled sys-
LEAD TIME = 8 WEEKS
LASER
MACHINING
ASSEMBLY
WELD
CUSTOMER
PLATE
SAW
HEAT
TREAT
PAINT CONFIGURE
PURCHASED
COMPONENT
STOCKS
RAW
STOCKS
Figure 2: A System without Decoupling Points
LASER
MACHINING
ASSEMBLY
WELD
CUSTOMER
PLATE
SAW
HEAT
TREAT
PAINT CONFIGURE
PURCHASED
COMPONENT
STOCKS
RAW
STOCKS
= STRATEGIC DECOUPLING POINTS

tem, but the crucial difference is that the customer reli-ably
experiences a tremendously shorter lead time. This
can be a significant market advantage.
2. Decoupling has huge implications for planning. If
the planning lead time shrinks, then the forecast error
over the planning lead time also shrinks. The forecast
error rate grows exponentially as the planning horizon
lengthens, and forecast error is generally acknowledged as
the largest cause of the bullwhip effect in supply chains.
At this point it’s important to note that material
requirements planning (MRP) systems aren’t designed to
decouple. They are designed to make everything depen-dent.
This is one of the inherent and critical shortfalls of
modern planning systems that led to the development of
Demand Driven MRP (DDMRP) systems. The rules
behind DDMRP systems are documented thoroughly in
the third edition of Orlicky’s Material Requirements Plan-ning.
(You can obtain free white papers, videos, and pod-casts
on DDMRP at www.demanddrivenmrp.com.)
Control Points
Think of control points as places to transfer, impose, and
amplify control through a system. They often are placed
between decoupling points with the objective of better
controlling the lead-time zones between those points. A
shorter and less variable lead time results in less stock
required at the decoupling point (a working capital
reduction).
The 14th edition of the APICS Dictionary defines con-trol
points as “strategic locations in the logical product
structure for a product or family that simplify the plan-ning,
scheduling, and control functions. Control points
include gating operations, convergent points, divergent
points, constraints, and shipping points. Detailed sched-uling
instructions are planned, implemented, and moni-tored
at these locations”(p. 33).
Instead of attempting to control a complex system
through the scheduling, management, and measurement of
every minute of every resource, companies can assert and
maintain meaningful control over a group from a few
strategic places. An example might be security at an airport.
While surveillance is occurring everywhere, active control is
asserted at only a few points. From those few points, secu -
rity across hundreds of flights and tens of thousands of
Figure 4: Decoupled System with Control Points
SHEAR
LASER
MACHINING
ASSEMBLY
WELD
CUSTOMER
PLATE
SAW
HEAT
TREAT
PAINT CONFIGURE
PURCHASED
COMPONENT
STOCKS
RAW
STOCKS
= STRATEGIC DECOUPLING POINTS
C
C CONTROL POINT
C
C
OUTSOURCE
OPERATION
LEAD TIME =
4 WEEKS
C
C

people can be extended with minimal disruption.
Control points don’t decouple lead times; they seek to
better manage execution inside the lead-time horizons in
which they are directly involved. They are the first areas
to be scheduled based on a requested final completion
time (either the delivery to a customer or to a decoupling
point). The control point schedule then drives all other
resource and area schedules within that lead-time hori-zon.
This creates a staggering effect for material release
and scheduled completions (promise dates). In the
Theory of Constraints, control points are called drums
because they set the cadence of the system. In Lean, con-trol
points are often called pacesetters. Regardless of their
name, they are the key to managing complex systems and
greatly simplify planning, scheduling, and execution.
When choosing where to place a control point, a com-pany
should consider four things:
1. Points of Scarce Capacity determine the total system
output potential. The slowest resource—the most loaded
resource—limits or defines the system total capacity.
2. Exit and Entry Points are the boundaries of your
effective control. Carefully controlling that entry and exit
determines whether delays and gains are generated inside
or outside your system.
3. Common Points are points where product struc-tures
or manufacturing routings either come together
(converge) or deviate (diverge). One place controls many
things.
4. Points that Have Notorious Process Instability are
good candidates because a control point provides focus
and visibility to the resource and forces the organization
to bring it under control or plan for, manage, and block
the effect of its variability from being passed forward.
A Decoupling and Control Point Example
In some cases, certain subassemblies and/or materials
could have decoupling points, but not the end item. Fig-ure
3 depicts this situation because there is still signifi-cant
activity after the last decoupling points. In these
cases, a control point (maybe more than one) will be
established between those last decoupling points and
delivery to the customer.
Strategically placed decoupling and control points dra-matically
compress lead times to meet market require-ments
and/or opportunities and assert or impose control
throughout the system. Figure 4 illustrates the application
of the decoupling and control point position factors to
our example company.
The company has chosen two internal control points at
weld and machining. The rationale is that the vast major-ity
of manufactured products go through one of these
areas. Also, these points have a need for carefully man-aged
capacity because qualified and experienced welders
and machinists have been difficult to find. In addition,
there are three control points that qualify as exit and
entry points: to and from an outside plating operation
and to the customers (final shipment).
Protecting Decoupling and Control Points
We have to employ some form of dampening mechanism
at these decoupling and control points to absorb variabil-ity
so the points can achieve their intended purposes.
This dampening mechanism is called a buffer. The three
types of buffers to employ are stock, time, and capacity.
Demand Driven Stock Buffers
The stock buffers of DDMRP are placed at critical decou-pling
points to perform the following functions:
Shock absorption—Dampening both supply and
demand variability to significantly reduce or eliminate
the transfer of variability, which creates nervousness and
the bullwhip effect.
Lead-time compression—By decoupling supplying
lead times from the consumption side of the buffer, lead
times are instantly compressed.
Supply order generation—All relevant demand, sup-ply,
and on-hand information is combined at the buffer
to produce an “available stock” equation for supply order
generation. These buffers are the heart of a Demand Dri-ven
planning system.
The DDMRP available stock equation is relatively sim-ple
but foreign to conventional planning systems. It adds
open supply to on-hand and then subtracts qualified
sales-order demand. Qualified sales-order demand is lim-ited
to sales orders due today, due in the past, and future
qualified spikes. By including only sales orders, the fore-cast
and the error associated with it are decoupled from
the commitment of capital, materials, and capacity. This
equation is unique to Demand Driven MRP.
Stock buffers initially are sized through a combination
of factors, including an average rate of use, lead time,
variability, and order multiples. Then the buffers are
stratified into color zones (green, yellow, and red) for
easy priority determination in planning and execution.
Each zone has attributes that affect its relative size, and
the buffers dynamically adjust with market changes in
consumption or in advance of planned or known activity,
such as seasonality or promotions. Figure 5 illustrates the

Figure 5: Replenish men t Sto ck Buffer
TOO MUCH
GREEN
YELLOW
nature of these buffers.
Don’t confuse strategic replenishment buffers with
MRP’s safety stock. Safety stock does not decouple—it
seeks only to compensate for variability, assuming no
decoupling or lead-time compression (i.e., a longer plan-ning
horizon). This makes it an inefficient type of damp-ening
mechanism. Additionally, safety stock often has
mechanisms (such as order launches and expedites) that
can exacerbate the bullwhip effect. (An in-depth look at
the DDMRP buffers is available in a white paper by the
Demand Driven Institute at http://demanddriven
institute.com/buffers_paper.html.)
Demand Driven Time Buffers
Control points manage the activity between decoupling
points or between decoupling points and customers.
Their schedules pace all other resource and area sched-ules,
so protecting the control point schedules is crucial
for overall system stability and control. Demand Driven
time buffers are planned amounts of time inserted in the
product routing to cushion a control point schedule from
disruption. Time buffers are sized based on the reliability
of the string of resources feeding the control point. The
less reliable or more variable that string, the larger the
time buffer required to protect the control point.
Figure 6 illustrates the concept of the time buffer. The
time buffer is in the middle and is the range bordered on
the top and bottom by boxes containing the words green,
yellow, and red. On the left side of the buffer is the flow of
work from preceding operations toward the buffer and is
represented by the shaded pentagonal figure pointed at
the buffer. The squiggly line represents the accumulated
variability in the flow of that work. On the right side of
the buffer is the control point, indicated by the shaded
box with a circle with a C inside it. The triangle with an S
inside it indicates the scheduled start of work for an
order at the control point.
In this example, the total buffer is nine hours of time.
Each zone has been set at duration of three hours. The
dotted lines that bisect the buffer from top to bottom
indicate each hour of each zone. With a nine-hour buffer,
work orders are scheduled to be in the buffer (buffer
entry schedule) nine hours before their scheduled start
time at the control point. With the existence of the vari-ability
in the preceding workflow, that will rarely happen.
When the buffer is sized properly, the majority of work
orders will arrive in the buffer sometime between the
buffer entry schedule and the scheduled start of work at
SCHEDULED START AT
CONTROL POINT
S C
STOCK OUT
RED
Figure 6: Time Buffer Protecting a Control Point
PROTECTED
CONTROL POINT
SCHEDULE
SCHEDULED ENTRY TO
BUFFER
GREEN YELLOW RED
GREEN YELLOW RED
EARLY
EARLY
9-HOUR BUFFER
LATE
LATE
WO 1595
WO 1781
WO 1626
WO 1601
WO 3279
WO 2001

the control point. In Figure 6 this is
depicted through the various lengths of
the arrows into the time buffer. These are
called buffer penetrations.
A buffer penetration occurs when
work isn’t in the buffer and available to
the control point any time after the
scheduled buffer entry time. In some
cases, work actually arrives early at the
buffer before the scheduled entry time.
The lengths of the buffer penetrations
determine the risk to the control point
schedule and whether action to expedite
is required in the preceding resources.
The longer the penetration, the larger the
risk to the control point schedule. The
key is that when the length of a penetra-tion
goes beyond the scheduled start of
Figure 7:
Capacity Buffers
OVER CAPACITY
R
Y
work at the control point, a late entry in the buffer will
be created. A late entry means that the control point
schedule has been compromised. Taking action to pre-vent
late entries keeps the control point and the system
stable, reliable, and on time. Because these buffers are
part of a system’s total lead-time equation, a company
can constantly strive to reduce them by identifying and
eliminating the major causes of buffer penetrations in
the red and late zones. We’ll discuss the importance of
collecting data about these penetrations
and their role in smart metrics in our
next article.
Demand Driven Capacity Buffers
Capacity buffers protect control and
decoupling points by giving resources in
the preceding workflow the surge capac -
ity to catch up with variability. The ability
to focus and then sprint and recover
allows stock and time buffers to be
reduced safely, thereby decreasing total
product lead time and required working
capital investment.
Figure 7 shows a resource’s load
requirements over 11 time periods. The
black bars are meant to convey load: the
longer the bars, the bigger the load. The
capacity buffer is the section stratified by R, Y, G (red,
yellow, green). The black bars in three of those time peri-ods
penetrate the buffer. The higher those bars go, the
closer a resource gets to being overloaded in that period.
A resource that’s consistently loaded to red or overloaded
is less responsive because it’s becoming capacity con-strained
and should be considered for control point sta-tus
or capacity upgrades. This protective capacity exists
today in every resource that isn’t capacity constrained.
Figure 8: Completed Demand Driven Design Model
SHEAR
LASER
LATHES
ASSEMBLY
WELD
PLATE
SAW
PAINT CONFIGURE
PURCHASED
COMPONENT
STOCKS
RAW
STOCKS
OUTSOURCE
OPERATION
C
C
HEAT
TREAT
C
C
C STOCK BUFFER
CONTROL POINT
TIME BUFFER
CAPACITY BUFFER
LEAD TIME =
4 WEEKS
CUSTOMER
F
C
G
CAPACITY BUFFER
TOTAL CAPACITY
1 2 3 4 5 6 7 8 9 10 11

But capacity buffers should not be used to improve unit
cost or to drive a particular resource’s utilization. In fact,
the entire notion of a capacity buffer flies in the face of
conventional costing policies. Capacity buffers require a
resource to maintain a bank of capacity to recover from
variability. This capacity can go unused. Exploring ways
to create revenue opportunity with unused capacity is
totally valid. What isn’t valid is encouraging a resource to
misuse its spare capacity to improve unit cost or resource
efficiencies by running unnecessarily. When that happens,
responsiveness goes down, and the stock and time buffers
are jeopardized, forcing them to increase to compensate.
The result is an increase in lead times and inventory lev-els
and a decrease in ROI.
Figure 8 illustrates the completed design for our exam-ple
company. Buffers have been inserted. The bucket
icons depicting strategically replenished stock buffers
have the green, yellow, and red stratification. The radial
green, yellow, and red icons represent time buffers in
front of the control points. The exit and entry points to
outsourced plating and to the customer also have time
buffers to protect their schedules. All resources that aren’t
control points (resources other than weld and lathes)
have capacity buffers, which are represented by a strati-fied
box in the top portion of the resource box. These
capacity buffers aren’t meant to convey that the organiza-tion
simply plans to invest in capacity everywhere. They
do mean that the company will commit to keeping more
capacity in those areas relative to the finitely scheduled
control points those areas feed.
Stock is an investment in both time and capacity. All
buffers are interdependent and, in some cases, can even
be interchangeable. Investments in stock, capacity, or
time are strategic only if they protect and deliver the
agreed-upon market strategy. The specific sizing, man-agement,
and measurement of these buffers, as well as the
importance of their role in smart metrics, are detailed in
our next article.
Operating Effectively
In a Demand Driven system, everyone’s actions are driven
to the same priority, and all objectives are focused on the
speed of flow of the right materials and information to
and through the decoupling and control points to meet
true market pull.
A properly constructed Demand Driven operating
model:
1. Aligns the operating model to market requirements
and potential,
2. Eliminates the variability and subsequent bullwhip
associated with forecast error,
3. Creates a realistic and executable schedule,
4. Dampens the impact of variability inherent in a
dependent event system on system flow,
5. Provides the framework for relevant information and
subsequent decision making to drive ROI in the right
direction,
6. Provides visibility and priority alignment for flow
across the organization, and
7. Injects no conflicting operational metrics at the tacti-cal
and execution level.
These seven outcomes are critical to being effective and
competitive in the New Normal. SF
Note: Part 3 of this series will focus on the last two steps of
becoming Demand Driven: bringing the Demand Driven
model to the organization and using smart metrics to
operate and sustain the Demand Driven operating model.
We also will share the results of companies who have suc-cessfully
shifted to this operating model. Sections of this
article are excerpted from Demand Driven Performance
by Debra and Chad Smith (McGraw-Hill Professional,
Hardcover, November 2013) with permission from
McGraw-Hill Professional.
Debra A. Smith, CPA, TOCICO certified, is a partner with
Constraints Management Group, LLC, a services and tech-nology
pull-based solutions provider. Her career spans pub-lic
accounting (Deloitte), management accounting (public
company financial executive), and academia (management
accounting professor). She served five years on the board of
directors of the Theory of Constraints International Certifi-cation
Organization, has been a keynote speaker on three
continents, is coauthor of The Theory of Constraints and
Its Implications for Management Accounting and author
of The Measurement Nightmare, and received the 1993
IMA/PW applied research grant. You can reach her at
dsmith@thoughtwarepeople.com.
Chad Smith is the coauthor of the third edition of Orlicky’s
Material Requirements Planning and the coauthor of
Demand Driven Performance—Using Smart Metrics. He is
the cofounder and managing partner of Constraints Manage-ment
Group (CMG) and a founding partner of the Demand
Driven Institute. Chad also serves as the program director of
the International Supply Chain Education Alliance’s Certified
Demand Driven Planner (CDDP) program. You can reach
him at csmith@thoughtwarepeople.com.

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