Improving On-Time Delivery Through Focused System Improvement
1. VELOCITY—a powerful business approach combining speed with direction—consists of three pillars: Theory
of Constraints, the system architecture; Theory of Constraints Lean Six Sigma (TOCLSS), the focused improvement
process; and SDAIS (Strategy-Design-Activate-Improve-Sustain), the deployment framework.
Background
Although they had made significant
improvements, Republic still had a dark secret
they only whispered about—their on‐time
delivery percentage for make‐to‐order jobs. Prior
to their experience with AGI – Goldratt Institute,
they didnʹt even distinguish their work between
make‐to‐order and make‐to‐stock. On‐time
performance wasnʹt measured, since they only
made delivery promises when absolutely
required, and unfortunately, they had a mediocre
record of keeping them.
However, following their strategic analysis and
after activating a constraint‐based design of their
new operations management process, Republic
was more reliable and able to produce at a much
faster rate. Overall, they were turning their
products 22 days (36%) faster with little capital
investment. Their new design prioritized work
based on the number of days an item had been
waiting at a workstation, because their analysis
had revealed that many items were in queue up
to 30 days to become the next job, only to get
pushed back by a ʺhigherʺ priority. Therefore, to
reduce the queue time for work‐in‐process (WIP),
and consequently reduce the total volume of
WIP, they had established a scheduling priority
rule based exclusively on the number of days in
queue. They also used a drum buffer‐rope
decision process to gate the release of new work
to avoid adding more WIP than the system
constraints could handle. Activating this design
stabilized the system sufficiently to achieve
significant improvement (see Republic Industries
International: Part II—Understanding Throughput).
Even so, to be honest, their delivery performance
was still poor with only 69% of their jobs being
completed on time or early.
VELOCITY and Focused System
Improvement
Integral to the VELOCITY approach are cycles of
Focused System Improvement as organizations
continue to monitor performance and seek
ongoing positive impact on their strategic results.
Because their system design was sufficient to
stabilize their systemʹs performance, Republic
recognized they had to focus even more on work
scheduling. They still had problems determining
realistic delivery times for their clients. When
specific delivery dates were required to exploit
new opportunities, production scheduling was
nearly impossible to manage as they had little
control over when a job would be worked next.
Republicʹs Director of Supply Chain Management
Republic Industries International
Part III—Improving Delivery Performance
Established in 1911, Republic Industries International repairs and produces large metal compo‐
nents supporting customers in the industrial and mining sectors. They also provide engineering
services to develop unique solutions to meet customers’ needs. Based in Louisville, Kentucky,
Republic operates as a make‐to‐order and make‐to‐stock company with about 100 employees.
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was spending a great deal of time manually
updating queue lists as he attempted to manage
scheduling priorities.
Under pressure to resolve this issue, Republicʹs
scheduling committee modified their design to
use scheduled due dates as the determining
factor to manage job priorities. That approach
seemed reasonable—they believed all they
needed to do was advance a jobʹs due date to
move it up in priority on the daily work lists.
Activating this design change did relieve some
stress in scheduling; however, while the sequence
of completed jobsʹ may have changed, the overall
on‐time results did not. The same number of jobs
still ran late. Why didnʹt they achieve the
expected improvement?
Understanding the problem
In retrospect, the problems with using scheduled
due dates became pretty clear. Within their
system, the make‐to‐order jobs had unique work
flows. Some of them required lengthy external or
internal processes. Therefore, the greater amount
of work to be done resulted in longer lead times.
To simplify their scheduling, they had assigned
all the make‐to‐stock jobs a standardized lead
time sufficient to cover the expected work
required. So items with due dates further in the
future (based on longer lead times) might
initially sit for weeks, while items with earlier
due dates received priority. To work around the
disparity in lead times, on occasion, the
schedulers would use fake due dates to re‐
prioritize a job, resulting in tremendous
confusion about whether a job was actually late
or just ʺfakeʺ late. Essentially, the due dates in
their information system became more and more
fictional, and despite their scheduling emphasis,
they lacked credibility and meaning.
Moreover, both this design and the previous
design had a common flaw—Republic never
seemed to know a job was in jeopardy of being
overdue until it was too late. They were using the
classic buffer management approach—Green,
Yellow, Red—to monitor a jobʹs progress
compared to its associated ʺtime‐to‐reliably
replenishʺ (TRR). However, as jobs neared
completion, their reports frequently showed their
status as `yellowʹ (needs review) or `redʹ (needs
intervention). With so many jobs needing
attention, the buffers failed to motivate the
proper actions. Supervisors were already too
busy responding to the daily crises of whichever
jobs, for whatever reasons, were the urgent fires
to be dealt with that day. By that point, they
could do little to achieve an on‐time delivery.
Instead, they focused their expediting efforts to
make items ʺless late.ʺ
Frequently their sales staff called asking when a
job would be finished, despite the job having a
specified due date. Research often found some of
those jobs stuck in queues despite their specific
efforts to reduce queue times! These failures to
deliver on time jeopardized all the gains of their
earlier improvements, especially if Republic
became known as an unreliable vendor. The need
was clear. Their next system improvement had to
focus on work priorities and scheduling to
reliably deliver on time.
Buffer Management and Scheduling
To improve performance in TOC‐based system
designs, managers use buffer management to
prioritize work, to know when to expedite, to
identify where capacity is insufficient, and to
adjust buffer sizes. Until this point, Republic had
only really used quantity buffers to protect some
inventory levels. When they described their latest
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problems, AGI proposed an evaluation of their
new generation (GEN2) buffer management
approach in their MANAGE Capability of the
SUPPLY CHAIN Suite®
. Although Republic
found the advanced concepts behind the ap‐
proach somewhat difficult to understand, they
found the logic of the approach to be very
compelling.
Republic translated their data to the format
required by AGIʹs software. Their Supply Chain
Management Director logged in to the MANAGE
Capability for the first time. For all its conceptual
complexity, he was initially underwhelmed that,
with just a few screens, it would be possible to
manage all of their operations. ʺYeah right,ʺ he
thought skeptically. He believed:
Republicʹs work is difficult to manage
because our constraint changes when we
have a significant change in our workload.
One large job can shift the constraint,
making all the previous scheduling work
obsolete. In addition, we work a variety of
scheduling shifts—eight in total. To
complicate things further, we typically do
not run out of machines, but rather
employees who can run specific machines.
We have a flexible work force and daily
tactical decisions determine where each
person works during a shift. Some
machines are ʺunmannedʺ for days waiting
for the first available skilled operator to
finish previous jobs. These factors,
combined with the variability of the jobs
themselves, contribute to our poor on‐time
performance.
Very shortly after activation, the new MANAGE
Capability was put to the test. With the economic
downturn, reduced demand forced Republic to
proactively seek more work. They succeeded in
being awarded a significant new job that was
atypical because it contained 70 more
components than other jobs in its throughput
range. And it had a must‐hit due date. The
director loaded their system with all the
necessary data. When he reviewed the
information provided by the MANAGE
Capability, in a job of more than 80 sub‐jobs, he
was amazed to see clearly that just two identical
sub‐jobs were key to the overall success. Previ‐
ously, he would never have been able to
determine the critical elements of a job this size.
To take all these sub‐jobs across the factors
discussed above was simply impractical. In the
past, Republic would have picked the most labor‐
intense sub‐job as their focus for monitoring. In
addition, because they didnʹt have a system
perspective, they would have started work as
early as they could on as many sub‐jobs as
possible. Their thinking was the earlier each sub‐
job was completed, the earlier they could proceed
to final assembly. Had they continued to use
their old logic, they would have had some parts
in WIP for an additional month and reduced the
current throughput of their constraint. In
addition, the new MANAGE Capability helped
him determine the best sequence for all these sub
jobs by providing detailed resource information.
By managing the critical sub‐jobs and the
production sequence, they completed this large
job on time using their resources in the most
effective way possible with little stress on other
operations.
Meanwhile, the Supply Chain Management
Director continued to upload all the other work
in their plant and rescheduled those jobs based
on the new system. The changes were significant
and fast. In the first week, they saw problems
that could be corrected before the job was late,
and they were able to successfully manage how
long a job would take by adjusting its associated
time buffer. For the first time, they controlled
