Achieving excellence starts with accurately diagnosing the health of a company’s
supply chain. It’s not possible to improve performance without first getting
a good read on what it is. Only then can a company identify, manage, and eliminate
any tradeoffs it may be making in its supply chain performance, and catapult
itself to excellence.
But while it’s a commonly accepted adage that “You can’t manage what you can’t
measure,” most companies still struggle with their measurement programs. First,
measurement requires resources that, for many companies, are in short supply.
Second, it can be difficult to access the metrics, and the resources that have
the best access to the numbers are typically the busiest resources. Finally,
there’s the question of what to measure. There are hundreds, if not thousands,
of possible metrics to collect. Which are the ones that matter? And what should
be done with them once they’re collected?
This complexity is compounded by the fact that, while traditional measurement
focuses solely on operational performance indicators such as cycle times and
inventory levels, companies also need to bring into the equation what we refer
to as enablers – the application technologies and best practices that enable
performance. Benchmarking these enablers is critical to having actionable information
by going beyond the question of how a company is performing as it is. Why is
a company at its current performance levels? What impact are technologies and
best practices having on its performance? What are the best-in-class companies
All Metrics Are Not Equal
What’s needed is a way to focus the effort and bring structure to the chaos
so that assessment and diagnosis can be done quickly, efficiently, and with
a minimum of resources. Rather than being undertaken as a massive project with
dedicated resources, this would allow companies to evaluate their performance
on an ongoing basis and correct problems before they become deep rooted.
AMR Research’s three-tiered Hierarchy of Supply Chain Metrics (see Figure 1)
is designed to solve this problem and take supply chain management to the next
level. Figure 1 provides a structure that allows increasing granularity of focus,
with each tier serving a different purpose and aimed at a different goal. At
the highest level is the small number of key metrics that provide a clear, concise,
aggregated view to quickly assess what’s going on in the supply chain. Subsequent
levels in the hierarchy provide a diagnostic tool that supports effective root-cause
analysis and allows highly efficient corrective action.
Top Tier: Executive Assessment
The top level of the hierarchy provides a quick assessment of the overall health
of a company’s supply chain and the high level trade-offs a company might be
making. At this level are three key metrics: demand forecast accuracy (DFA),
perfect order fulfillment (POF), and supply chain management (SCM) total cost.
Findings from AMR’s benchmarking research to date highlight the importance
of the demand forecast accuracy metric. Analysis of our data reveals that demand
forecast accuracy has a direct impact on and drives perfect order fulfillment
performance, a key indicator of customer responsiveness which measures the ability
of a company to deliver an order that is accurate, complete, on time, and in
perfect condition. The strong correlation in the data suggests that improving
demand forecast accuracy could yield dramatic improvements in perfect order
At the same time, many companies compensate for poor demand visibility by throwing
money at the problem. Rather than incur the unwanted stockouts which are a typical
result of low demand visibility and which would erode their perfect order rating,
they keep extra buffer inventory on hand, driving up their costs. Other companies
are willing to sacrifice customer responsiveness to keep their costs low. Either
way, the tradeoff between cost on the one hand, and service on the other, is
the most typical tradeoff companies make.
Therefore, while demand forecast accuracy and the perfect order are critical
metrics that indicate the responsiveness of a company’s supply chain, a balanced
assessment of the health of the supply chain must also include supply chain
management costs. By looking at these three metrics, a company can quickly assess
any tradeoff it may be making between cost and service and whether or not the
tradeoff is consistent with its business strategy.
Midlevel: Beginning the Diagnosis
The next critical metric is a company’s cash-to-cash cycle time. This measures
how well a company is managing its cash flow, from the time it pays its suppliers
until the time payment is received from its customers. By highlighting any potential
imbalance between supplier and customer payment times, this metric often reveals
immediate opportunities to take some cash off the table. The cash-to-cash cycle
time also includes the bellwether inventory metric, which can contribute to
high cost and/or a low perfect order.
ConsumerCo, a $1 billion manufacturer of household goods, is a company that
has traditionally been focused on being the low-cost provider in its market.
A high-level assessment of their supply chain performance revealed, as expected,
that they were strong on costs but weak on demand visibility and perfect order
fulfillment compared to their peers. Analysis at the second tier of the hierarchy
showed a lot of extra inventory. High inventories might be a result of excess
in any of the components of raw materials, work in process, or finished goods,
and each is a symptom of a different underlying problem. Clearly, the problem
with their order fulfillment wasn’t a lack of inventory, but more likely a result
of having the wrong inventory (related to their poor demand visibility) or lacking
visibility of available inventory.
Ground Level: Identifying Corrective Action
The ground level is where the detailed metrics reside. The clues identified
at the top two levels of the hierarchy allow a company to dive into only those
detailed metrics that are indicated as warranting attention. Analysis at this
level allows a company to identify and implement the specific interventions
that will address the root cause of any issues identified with the most efficient
and targeted use of resources.
Metrics at the ground level include supplier effectiveness indicators such
as the percent of supplier receipts that passed quality and on-time standards,
and the raw material inventories, purchasing operating costs, and direct material
costs that are often affected by and interact with supplier performance. Also
included here are additional metrics that indicate a company’s level of operational
effectiveness, including order cycle time, production schedule variance, plant
utilization, work in process, finished goods inventory, further SCM cost details,
details about the perfect order fulfillment total, and others.
ConsumerCo, as we saw earlier, had issues with low demand forecast accuracy,
below-par perfect order fulfillment capability, and high inventories. By identifying
these three issues at the top two levels of the hierarchy, they could direct
their attention only to the detailed metrics that are salient to solving those
problems. For example, at the ground level metrics they found that the high
inventories were actually a result of two components: ConsumerCo had higher-than-average
raw materials and higher-than-average finished goods inventories. On further
investigation, it turned out that the high raw material inventory was in turn
a result of poor supplier on-time performance, leading them to hold extra raw
material as a buffer. Knowing this, they could focus on the root cause of the
problem and, by revisiting service level agreements with their suppliers, correct
An analysis of their perfect order details helped illuminate the source of
the high finished goods inventory levels. The main culprit of their poor perfect
order performance turned out to be a high level of inaccurate shipments, rather
than stockouts. If they didn’t have the exact item that was requested by a customer,
their practice was to substitute something else. That meant that they had a
lot of unused finished goods inventory lying around, and unhappy customers who
received something other than what they asked for. The root cause of the problem
pointed to their poor demand visibility. Once they worked on correcting that,
finished goods inventory levels came down and customer satisfaction rose. They
were able to both reduce cost and improve service at the same time.
In identifying corrective actions to be taken to address the root cause of
issues that are uncovered, a solid understanding of where a company stands with
regard to application technology and best practice enablers becomes critical,
since these serve as important levers to help adjust performance.
For example, in addition to possibly revisiting the agreements it has with
its suppliers, ConsumerCo could also examine the extent of its connections with
suppliers. To what extent is it sharing forecasts with its suppliers, and how
does this compare to the average for its industry? Is it using electronic connections
to expedite purchase orders to suppliers to the extent possible? Similarly with
its customer relationships, are customers sharing forecasts with ConsumerCo
to the extent possible to help demand visibility? How does ConsumerCo’s use
of these enablers compare to its peers and, in particular, to the best-performing
Understanding how its investments in technologies and business processes compare
to others, coupled with how its performance compares to others, can also help
to highlight whether or not a company is effectively leveraging those investments.
For example, suppose a company has invested far ahead of others in its industry
in a comprehensive end-to-end supply chain system. Is it realizing above-par
performance in the areas supported by the system compared to its peers?
Using the Hierarchy of Supply Chain Metrics, with assessment at the top tier
followed by targeted root cause analysis at middle and ground levels, companies
can quickly and efficiently assess and diagnose the health of their supply chain.
Coupled with a clear view of their application technology and best practice
enablers, specific corrective actions can then be identified.
Rather than facing a morass of hundreds of metrics, the model allows companies
to start with just a few critical ones, and use what’s identified there to guide
attention only to those additional metrics that are needed. Bringing order to
the chaos, this approach allows companies to efficiently use scarce resources
to quickly and accurately uncover root cause issues, identify specific and targeted
corrective actions to address them, and regularly monitor progress to ensure
a continual momentum forward toward excellence.