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Management
of a two-plant metal fabricator with annual sales around $110
million was struggling with how to fix problems of poor
delivery reliability, high inventory levels, poor quality and
low morale. To make matters worse, the company had recently
become unprofitable. Traditional approaches of working more
overtime, increasing quality control efforts, and expediting
work to satisfy the most vocal customers were exacerbating the
problems rather than providing the relief hoped for. Customers
and owners alike were losing patience.
Clearly
it was time for a change, but to what wasn't clear. After
reviewing the operations in depth the culprit was discovered:
the operating system, meaning the way product was planned and
produced.
The
old operating system was a legacy of a time when competition
was virtually non-existent and long lead times were the norm.
This "leisurely" pace of manufacturing had allowed
machine efficiency to be the primary focus. Customers had been
willing to wait in exchange for low prices. Times had changed
but the company had not.
New
management saw the need to convert the existing operating
system to one more responsive to customers. That meant
increasing the flexibility with which production and material
requirements could be changed, rescheduled, and/or
reengineered, based on changes in the customer's orders. To
accomplish this, a visual shop floor control system along with
a sequenced master scheduling system with provisions for
resequencing was to be implemented in both manufacturing
facilities. The goal was to create discipline and order that
would enable flexibility, reliability, productivity, and
inventory management to improve. A corollary objective was to
reduce scrap generation as a result of improved handling and
less crowding.
The
cost to implement the new system had to be considered. The
whole process of development, training, and implementation
would take four months, plus another two months to refine and
seat the sustainability of such a big undertaking. What with
training time, some diminished production, some more overtime,
and some outside help to facilitate the development of shop
floor control processes and I.T. support needed by the master
scheduling system, the cost per plant was estimated to be a
little under $1.1 million dollars. Included in this was the
impact flushing out the work-in-process inventory that had
supported a four week manufacturing cycle time if the
manufacturing cycle time was reduced.
There
were benefits expected as a result of the operating system
change. Goals were established to determine the success of the
implementation. These included:
1)
A 10% improvement in productivity with a stretch goal of 15%,
as measured by total labor hours worked per pounds shipped
(history of mix and products shipped was very stable.
2)
A 25% reduction in the value of Work-in-Process inventory with
no increase in raw materials or finished goods. The stretch
goal was a 70% reduction.
3)
On-time deliveries to customer request date exceeding 90%
(current levels were below 35%). The stretch goal was to
eliminate lead times all together and give scheduling
authority to the customer.
4)
A quality measure was developed to reflect doing it right the
first time. First pass yields were currently less than 50%.
The goal was to achieve first pass yields of 75% with a
stretch of 90%.
The
ultimate test of the value of this costly overhaul would be
the company's return to profitability. However, coming up with
the right measure wasn't easy. Profitability as a percentage
of sales was important but could be affected by a number of
other factors, such as price changes. Plus, inventory
reductions wouldn't directly show up on the income statement
but had a significant impact on the balance sheet and cash.
An
improvement in gross margin was decided as the key measure.
Since labor represented 15% of sales, the average labor cost
per plant was in excess of $8.4 million annually; a 10%
improvement would add $840,000 to the gross profit. In
addition, the targeted improvement in first pass yield was
calculated to reduce material costs by 2%. Since material
equaled 48% of sales, a 2% reduction amounted to an extra
$528,000 of gross profit annually. No attempt was made to
quantify the value of meeting customer deliveries. Placing a
value for having fewer inventories was also problematic. There
was value but it didn't translate well to gross margin for
people on the shop floor. However, they could relate to faster
cycle times. So the performance measure used was manufacturing
cycle time, with a goal to eliminate at least one week from
the current four weeks. The stretch was to eliminate 3 weeks.
It was determined that eliminating a day of manufacturing
cycle time would reduce interest expense by $4035 based on the
cost of carrying inventory at 10% in annual interest for the
cash to fund it. Thus, a one week reduction was worth an
additional $28,245 annually. This would be added to the
improvements in gross profits for an overall operating return
calculation.
Consequently,
the determination was that investing $1.1 million dollars at
each plant would generate a significant return in a fairly
short period of time. In fact, the productivity gain was over
11% within two months of launch and first pass yield increased
to 90% within the first few weeks. Equally important,
Work-in-Process inventory was reduced significantly when the
manufacturing cycle time was reduced from 4 weeks to 1 week
immediately upon launch. Actual costs were slightly under
$800,000 for each plant. The payback was under seven months.
In
summary, what appeared to be an expensive undertaking at first
(spending over a million dollars per plant) turned into a huge
savings. Traditional methods of quantifying the benefits
worked and were able to demonstrate the value of a better
alternative. For those of you contemplating your next move,
consider the total picture when determining whether it's
better to keep doing what you're doing or taking a new
approach. Your decision may mean the difference between
survival and failure.
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