Common Challenges in Fabric Buying
Fabric cost is one of the biggest cost factors of the garment manufacturing process trailed by labour cost. Manufacturers around the globe have been grappling with different fabric saving measures to make their garment cost more competitive in the current dynamics of the market.
With rising common minimum wages in developing worlds and emerging new manufacturing hubs in third world nations, manufacturers are looking for reliable solutions which can help them regulate and monitor the fabric consumption and purchase, and thus reduce the fabric cost.
Both fabric consumption (fabric used in the finished garment as well as all process losses and wastage) and purchase are interdependent factors. Generally, people see it as a linear relation i.e., more consumption meaning more purchase, but analysis of fabric uses pattern in factories will also tell you that this relation can be seen other way round as well, i.e., more buying is also leading to more consumption.
The vicious circle of unplanned buying and unregulated consumption leaves a manufacturer with diminishing profits and increasing deadstock as a cost burden to inventory.
What does correct buying mean?
From grocery buying to fabric buying, we face the same challenge! How much to buy?! Buy less and you end up with a short output. Buy more and accumulate excessive and expensive deadstock which will create a dent in your profits. So, we take it as obvious that we should buy only the amount which we will consume. Consumption can be in form of material that goes into the final product, and also the amount of material that will inevitably go into process loss due to various reasons.
What steps can be taken?
One can intuitively suggest that we should correct the process at buying end. It can easily be misunderstood that reduced buying will trickle down the manufacturing chain forcing cutting sewing, finishing washing/printing departments to take measures for reducing consumption. This might work in some factories, but it is more likely to remain ineffective if the consumption pattern remains the same. It may result in short shipment causing factories to fall back to old practices.
With shorter order quantities and frequent style changes, there is very little time available for the production line to adjust to constrained input pressure. There is hardly any time and resource available with the factory to keep order by order material utilisation tab in each department. Reports generated from ERP lack decision making intelligence and mostly they are just tables of data without any actionable item.
So, from where does the corrective action start? As we discussed earlier, correct buying and correct consumption are interdependent. Correct buying is the science of predicting future material consumption and wastage/process loss which must be considered and buying just the amount to fulfil it.
Predicting material consumption, current most common methods:
Nearly every buying unit in the garment industry has adopted a set of buying prediction templates. The most common of them all involves a generic marker ‘one-piece-from-each-size’ and the addition of some blanket buffer on top of it.
The problem with the above method is that all the size quantities get equal weightage in the consumption calculation. In cases when we have more quantity in smaller sizes, the above method will end up buying extra fabric and in cases where we have more pieces in larger sizes then buying becomes less.
So, our first learning for correct buying is each size quantity should get a weighted representation in consumption calculation.
The proper way to represent each size according to its quantity is by making a complete cut plan rather than making one single generic marker with one piece from each size.
Adding right buffers on marker consumption:
As commonly seen many factories around the globe add a blanket buffer on top of marker consumption to compensate for the process loss which occurs during manufacturing and storing goods.
There are many kinds of process losses like end loss, end-bit loss, ticket length shortage, part replacements, splicing wastage, fabric damages, testing and sampling losses, etc.
These losses are dependent on the product being made, fabric or material used, the quantity of output and mostly on material planning and production technique.
Due to the above variables each time an order is executed some process loss occur. This process loss changes per order vis-a-vis fabric. Ideally, if any factory can find the accurate value of process loss and uses it as a buffer on top of marker consumption then a better buying consumption can be achieved reducing the chances of overbuying or underbuying.
Before:
After:
Challenges:
Unavailability of complete size breakdown during the time of costing: The major challenge manufacturers usually face while making a complete cut plan to derive accurate marker consumptions is, during the time of costing they usually don’t have size wise breakdown of quantity. They only have the total booking quantity and number of sizes in which they might come.
For frequently running orders, this problem can be solved by looking into historical data of similar styles from the same buyer. Using matching filters, factories can see what the ratio of quantity in different sizes in past orders was. Using those ratios, the current quantity can be divided and used for marker making. The marker consumption hence achieved has been found much closer to actual production scenarios. Hence, they prove to help buy accurately.
It’s like the way we plan our Christmas dinner when we invite our friends and have no idea how much to cook. It will always be wise to look at how much they ate in the past.
Unavailability of correct buying buffers: Now it is a kind of challenge which can only be solved with discipline and coordination.
When generally asked in the factories whether they have a record of their process losses, they would admit recording it diligently through different paper forms and lay slips in hard copies. But there is seldom any system in place which can record, mine and report the process loss data accurately when required. They need a system that could filter data based on matching parameters and suggest what has been a historical process loss trend for a similar order in the past. So, in place of adding a blanket buffer of 5 per cent (let’s assume), a much closer figure of 4.6 per cent of 5.2 per cent can be used (Which might be the actual case). This can prevent overbuying (in case actual wastage is lesser than blanket buffers) or underbuying (If actual wastage is higher than blanket buffer per cent).
Conclusion:
Considering the size and buffer factors while estimating consumptions is key to correct buying. Idea is to get as close as possible to on-floor consumption. Historical data is the goldmine for fixing correct buying buffers. There are applications like IntelloCut and IntelloBuy which help users with correct buying with proper cut plans and historical buying buffers. Please visit coatsdigital.com for more details.
This article is written by Rahul Bhardwaj, Product Owner (GSD & SeamWorks) at Coats Digital.
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