SPOTLIGHT on
SUPPLY MANAGEmENT
Challenged by Complexity?
Quantify It!
By Khalid Khan
Khalid Khan is a
vice president
in A.T. Kearney’s
Procurement and
Analytic Solutions
group. Based in
Chicago, he can
be reached at
khalid.khan@
atkearney.com
80
Complexity is a fact of
business life today. It
cannot be eliminated,
but it must be managed. Firms that know
how to manage complexity are typically
their industry’s leaders.
What do these companies know that others
have yet to learn? Managing complexity requires
fundamentally changing two things: the way
companies collaborate across the organization
and how data is used to make decisions.
Complexity optimization is an innovative,
practical way to break out of the complexity
death spiral, using key predictors of customer
purchasing behavior to monetize the cost or
value of introducing a new product or service.
By linking top-line drivers such as innovation
and customer preferences to complexity, the operational impact of complexity can be measured in
dollars. Rather than merely reducing SKUs, simplifying processes, and rationalizing the manufacturing footprint, the focus is on customers and
collaborative decision-making. We have developed
a toolkit that can optimize the value of complexity across all elements of the value chain. The
toolkit has the four pillars described below:
1. Focus on Customers First. Failing to
understand what consumers value can damage
a company’s competitive position. Alternatively,
supporting the wrong variety can significantly
increase the cost-to-serve. Complexity optimization uses key predictors of purchasing behavior
to quantify the value or cost of a new product.
A.T. Kearney’s SKU Customer Switching
Matrix evaluates switching propensity across products and the relative ease of converting customers
from one product to another. It can help determine how to migrate the right customers over
to the right products. At a minimum, the matrix
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July/August 2012
reveals ways to work with sales organizations
to align customer preferences with operational
capabilities. Time and again, the matrix has pinpointed ways to free up manufacturing capacity
for new products.
Switching matrices can be as simple or sophisticated as necessary. For example, the matrix in
Exhibit 1 identifies product attributes that can
encourage or discourage customers from switching products. For the high-end performance films
depicted, width and length matter most to customers. However, they could be encouraged to
switch products if the price is right or if significant capital investments are made to create the
right product.
Companies are reluctant to delist SKUs for
fear of conceding market share to their competitors. For example, consumer packaged goods
(CPG) companies can make more informed decisions about SKU variety by examining purchasing
predictors such as the category’s expandable consumption index (the measure of item trips made
per item buyer), market share, and all-commodity volume (ACV) penetration for its products and
its competitors. Such quantitative analysis shows
that reducing the SKU count for a product in a
category with low expandable consumption and
high ACV within a market will have less of a revenue impact than one with high expandable consumption and low competitor ACV.
2. Determine Costs of Complexity
Drivers. Companies that fail to understand the
tradeoffs between what customers want and the
price they are willing to pay will see their costto-serve soar. Every uninformed decision will
cripple a company’s operational ability to support
market objectives—driving up costs, straining
logistics, and compromising service and quality.
Without an accurate measure of a new product’s costs, decisions will most likely be flawed.
However, there are not very many alternatives.
www.scmr.com
SPOTLIGHT on
SUPPLY MANAGEmENT (continued)
sounding the alarm about losing customers. To build consensus, monetize the consequences of complexity—quantifying
the tradeoffs or costs of inaction. This changes the debate
from one centered on emotion or gut instinct to one of collective action grounded in data-driven analysis.
Companies can develop “what-if” scenarios using
advanced optimization techniques that enable informed
decisions that assess the tradeoffs between value and
costs. These decisions will have a direct impact on the
supply chain—from suppliers to the configuration of production lines to the customization offered to customers.
4. Institutionalize the Approach. The secret to dealing
with complexity is to resist the knee-jerk reaction to eliminate
it so it can be forgotten. Companies need to understand what
drives it and how it evolves. Shift from a project mindset to a
process mindset, and you will not only change the culture but
also provide everyone with the tools to sustainably manage
complexity. This ensures that everyone views complexity and
all of its implications—good and bad—as an ongoing effort
rather than just another program that will soon be forgotten.
Most information technology (IT) environments do not
capture or structure the data for an accurate analysis. To
calculate the full costs, data needs to be pulled from across
fragmented IT systems—and there is no one place to find
this information. Financial and accounting systems are
also not designed to support cross-functional complexity
management efforts.
We solve this problem using a multi-cube. Made up of
a spend cube, production cube, and sales cube, this model
shows the costs associated with complexity and the impact
on profits. The cubes consolidate data from across the supply chain into functional data storage areas linked by business rules to enable multidimensional slicing and dicing.
The multi-cube can be used to generate specific value chain
hypotheses and identify ways to improve. Data can be analyzed at any level over any combination of dimensions. Just
imagine what you can do with visibility into revenues, costs,
and margins at the SKU level across the supply chain.
3. Leverage Advanced Optimization. How well
complexity is managed is a measure of a company’s ability
to synchronize the upstream market product portfolio with
the downstream supply chain. Making the right tradeoffs
between what a customer wants and the price he or she
is willing to pay requires quantifying the costs of complexity across a range of areas including sourcing, operations,
transportation, and distribution. Actively managing complexity can boost earnings before interest and taxes (EBIT)
by 3 percent to 5 percent across the entire value chain.
But managing complexity is not easy. Various stakeholders share the impact of complexity but do not always agree
on how to tackle the problem. We have yet to meet a supply
chain executive who, in attempting to wring complexity from
the product portfolio, has not run up against the head of sales
The Path Forward
Our complexity optimization toolkit will become your organization’s analytic backbone and decision nerve center—if
the data is properly organized by the types of decisions to
be made rather than the types of systems used. Properly
used, the toolkit can yield immediate impact and growing
advantage. Research and development gets the cost data it
needs to develop viable products, marketing gets solid customer data for predictive modeling, and the executive team
has operational performance data at its fingertips to develop
as many scenarios as necessary. Never again will you look at
complexity, scratch your head, and wonder what to do.
EXHIBIT 1
Product Attribute Customer Switching Matrix
Product Attribute
Width
Length
Little/Low Resistance —1
Switching Propensity
Customers are willing to switch to higher widths
3.7
Customers are willing to switch generally within
+/- X% of length
3.5
Reluctant/Unwilling —4
Pricing incentives could convince customer to
switch over
Significant CAPEX investments needed by customer
Automation and safety requirements must be considered
Packaging
Customers are willing to switch within the same
packaging category
Formulation
As long as product characteristics do not change
standardizing on formulation is acceptable
Thickness
Color
Customers are willing to stack smaller gauge sheets
Standard colors are generally pushed in this market
and are not specifically requested by customer
www.scmr.com 2.7
1.7
1.2
1.0
Limitations on customer logistics capabilities hamper
switching on this dimension
Some customers may be willing to switch through
coordination and negotiations
Automation and process capabilities at customer
manufacturing determine the acceptability of stacking
Customers will not be willing to switch between
different colors
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