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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.
SUPPLY CHAIN MANAGEMENT 
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 
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 39 
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)
SUPPLY CHAIN MANAGEMENT 
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- 
40 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 
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 
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 41 
SHEAR 
LASER 
MACHINING 
ASSEMBLY 
WELD 
CUSTOMER 
PLATE 
SAW 
HEAT 
TREAT 
PAINT CONFIGURE 
PURCHASED 
COMPONENT 
STOCKS 
RAW 
STOCKS 
LEAD TIME = 3 WEEKS LEAD TIME = 1 WEEK 
= STRATEGIC DECOUPLING POINTS 
C 
C CONTROL POINT 
C 
C 
OUTSOURCE 
OPERATION 
LEAD TIME = 
4 WEEKS 
C 
C
SUPPLY CHAIN MANAGEMENT 
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 
42 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 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 
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 43 
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
SUPPLY CHAIN MANAGEMENT 
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 
LEAD TIME = 3 WEEKS LEAD TIME = 1 WEEK 
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 
44 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
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. 
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 45

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Staying demand driven 2

  • 1. 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.
  • 2. SUPPLY CHAIN MANAGEMENT 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
  • 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 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 39 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)
  • 4. SUPPLY CHAIN MANAGEMENT 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- 40 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 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
  • 5. 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 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 41 SHEAR LASER MACHINING ASSEMBLY WELD CUSTOMER PLATE SAW HEAT TREAT PAINT CONFIGURE PURCHASED COMPONENT STOCKS RAW STOCKS LEAD TIME = 3 WEEKS LEAD TIME = 1 WEEK = STRATEGIC DECOUPLING POINTS C C CONTROL POINT C C OUTSOURCE OPERATION LEAD TIME = 4 WEEKS C C
  • 6. SUPPLY CHAIN MANAGEMENT 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 42 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
  • 7. 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 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 43 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
  • 8. SUPPLY CHAIN MANAGEMENT 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 LEAD TIME = 3 WEEKS LEAD TIME = 1 WEEK 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 44 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
  • 9. 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. 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 45