ATWSPL ‘TOPSPIN’ ERPr
A Case Study By Prem S Bajpai, CEO, ATWSPL, To Calculate ROI Based On Cotton Procurements
A 100% EOU manufacturing cotton yarn was selected for the application of BPM & BI capabilities having 30,000 spindles
with a turnover of around Rs.80.00 crores [price base FY 2005-2006]. Cotton fibre was the raw-materials and through
different stages of production, the fibre finally got converted in to cotton yarn that is packed and dispatched as
per the customer requirements. EOU manufacturer was equipped with the state of the art textile machinery and production
The EOU opted for’TOPSPIN’ industry specific ERP solution that clicked off with system requirement study by the ERP
vendor ATWSPL followed by an approved design and subsequently a RDBMS application with a multi-layered architecture
was installed for a multi location usage involving radio frequency dedicated connectivity for smooth data transfer
to a centralized server.
Cotton is a natural fiber and never produced in factory based controlled conditions. Hence, the cotton properties or
characteristics are entirely dependent on nature / climate i.e. soil, temperature, water and humidity. Depending on
these variables the fiber length, diameter and strength vary that determines the quality of fiber. As the quality and
price always have relevance different varieties of cotton fibers have different prices prevailing in the market designated
as ‘District / City’ [Area] wise cotton fiber prices.
ATWSPL after a careful study found that the raw-materials [fiber] consumption value is the highest variable cost. This business intelligence shifted attention to conclude the following facts and statistics:
The BI & BPM experience and capabilities were used to identify and re-engineer the working software that essentially consist the input provision for the followings:
- Cotton fiber quality highly contributes and determines the quality of yarn as compared to production process control.• Cotton fiber quality highly contributes and determines the quality of yarn as compared to production process control.
- The cotton - yarn [Raw-materials to finished product] cost ratio is around 52 % that means a little savings in the cotton purchase cost but without compromise in quality looking the EOU status of the manufacturer will impact drastic improvements in profits
Identification of fiber quality index [FQI] and lot wise grading.
There are various characteristics of cotton fiber e.g. micronaire, strength, length, uniformity ratio, short fiber etc. can be considered to arrive at a fiber quality index [FQI] and a grading system can be provided based on the historical and current data.
- Identification of yarn quality index [YQI] based on the observations like TPI, TM, imperfections, U% etc. to calculate [YQI]
Co-relation of FQI & YQI to identify and scientifically select correct cotton fiber variety that can deliver quality and cost benefits both.
In the statistical quality control module, provision for the inputs as well as programmed calculations were inbuilt to determine fiber quality index [FQI] and yarn quality index [YQI] and their co-relation can be easily established.
- Provision for production planning considering make to order [production concept] and order to make [marketing concept] conditions.
- Bill of materials [BOM] that can reveal the required fiber variety wise characteristics and quantity to ensure supply chain coordination.
- Production scheduling specifically in case of order to make conditions to maintain customer relationship.
- Strict quality control for monitoring deviations from budgeted norms [benchmark] to ensure CRM.
Time to market is always a constraint while marketing under extreme competitive conditions. This consist two elements from design & programming point of view. Namely:
A product wise inbuilt cost sheet to arrive at a price to be quoted is required to minimize time of offer submissions with the customer. The inbuilt cost sheet always helps to know profit margins. In case of exports, the price estimation must be based on INCOTERMS.
The offer submitted is never complete without delivery commitments. Hence, the software application should be able to consider production in process as well as future production plans as constraints. The marketing module was to be so tightly integrated with the production module that delivery committed can be fulfilled without fail to ensure CRM.
ATWSPL has come out with excellent business intelligence information pertaining to the area wise quality and price of
cotton fiber that ultimately govern the quality of yarn as per customer requirements.
The following table illustrates interesting information:
||Amount In [Rs]
||Cotton yarn [raw-material to finished product] ratio
||Sale value of yarn
||Cotton procurement cost
||Cotton quantity purchased k.g. [approx]
||Average cost of cotton procured / kg
||Savings in cotton purchase / kg due to BI & BPM
||Rs. 0.50 / k.g.
||Total Savings in a year
This can now be safely concluded that a small saving in the cost of raw-material procurement can introduce drastic improvements
in profits looking to the massive turnover.
Note: The Figures are based over FY 2005-2006. The above saving account for application of BI & BPM in raw-materials
procurements only and did not consider the impacts of improved CRM, quality, other functional areas and benefits of
automation and integration. Moreover, figures considered are indicative and not precisely accurate.
Such benefits are accrued for a year and ‘TOPSPIN’ ERP will continue to provide the same in ensuing years regularly.
If the turnover is more, resultantly, the benefits will also be more.
This helped the EOU manufacturer to not only make huge savings in raw-material procurements but identify the exact customer
requirement of yarn and there by identify and select a correct fiber to maintain customer relationship.
The EOU manufacturer invested Rs.60.00 lacs over the ERP project [license, hardware, network and connectivity] the payback
period was around 1.38 year that can be considered as an excellent capital investment.
Note: Cost figures are subject alert and recommended use