Case Study

ATWSPL ‘TOPSPIN’ ERP implementation at Shri Bhagirathi Textile Ltd, [SBTL] Nagpur

A Case Study By Aviral S. Bajpai, ATWSPL

ATWSPL is in the last leg of implementing ‘TOPSPIN’ ERP at Shri Bhagirathi Textile Ltd, [SBTL] Nagpur. ATWSPL has immense pleasure to share few valuable experiences/information as under:

‘TOPSPIN’ ERP has made available real time flow of enterprise wide information related to yarn market, raw-materials, costing & production planning, production & quality controls, sales, power consumptions, HR and financial resources in an integrated manner in multi-user and multi-location environment at SBTL H.O. and Kalmeshwar, Mohali works.

‘TOPSPIN’ ERP has provided absolute managerial controls to SBTL management in terms of:
  • Cost
  • Production &
  • Quality

SBTL has achieved real strength in integrating their entire commercial activities along with technical activities [production, SQC, maintenance and engineering] to instantly produce techno-commercial MIS for deeper analytics. ATWSPL domain expertise has significantly contributed to generate this business intelligence through ‘TOPSPIN’ ERP and added radical values those will be continued to co-create with subsequent implementations.

SBTL is coordinating now with ATWSPL to achieve the best return over investments [ROI] considering the use of instant information available related to yarn lot wise, exact raw-materials mix, mixing cost, yarn quality details considering their end use, productivity details, logistics and corresponding contributions.

Regarding ROI, a brief study has revealed that SBTL maintained the policy not to dispatch yarns to the customer below the benchmarked Kgs. Extra few grams are allowed. This has resulted around Rs 35.00 laks per year and apparently no additional benefits are drawn from the customers who even do not know about this.

ATWSPL has advised to put electronic weighing machines in the packing department and design an interface to electronically prot data in ‘TOPSPIN’ ERP to precisely weigh accurate weight and work out the losses that can be prevented with immediate effects.

This alone has drastically affected the ROI against the investments made over ERP deployment.

‘TOPSPIN’ ERP information reservoir has now become so profound and comprehensive that every textile domain has been taken care off to explicitly define its business propensity.

No Indian or multinational organization has achieved this status so far in the spinning sector except the ATWSPL ‘TOPSPIN ERP’.


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 technologies.

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:
  • 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
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:
  • 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:

    Price estimation

    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.

    Delivery commitment

    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:

SNO Particular Unit Amount In [Rs]
1 Cotton yarn [raw-material to finished product] ratio 51.25%
2 Sale value of yarn 960000000.00
3 Cotton procurement cost 492000000.00
4 Cotton quantity purchased k.g. [approx] 8669603.524
5 Average cost of cotton procured / kg 56.75
6 Savings in cotton purchase / kg due to BI & BPM Rs. 0.50 / k.g.
7 Total Savings in a year 4334801.62

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