Attempt all the problems.

Section-A

problem1) There are 5 steps for implementation of BPR in any company. Describe any 3 steps in details.

problem2) Total quality management (TQM) and BPR should start from top management in any organisation, Describe how TQM and BPR must be implemented in any organisation at each functional level.

problem3) After the world war ended in 1945, Japanese Companies stared dominating western world after 1960, by “  Rigorous practice  of Kaizen philosophy” There are many  features of Kaizen. describe any five features of Kaizen in details.

problem4) describe qualities of a CHANGE LEADER

Section-B

Case Study

Reject Rate Reduction at the Reserve Bank of India

The National Clearing Cell (NCC), Madras, is the division of Reserve Bank of India, responsible for cheque-clearing operations in Madras area. Cheque clearing has been computerized since 1987 and involves running cheque on high-speed reader-sorter system (HSRSS) driven by the mainframe computer. The cheques, customers deposit in their banks, that are drawn on other banks, arc presented to the Clearing Cell, that captures data on the HSRSS, sorts cheques on the basis  of the drawee bank and branch code and prints out a number of reports, including clearing settlement.

The HSRSS reads Magnetic Ink Character Recognition (MICR) code on band at the bottom of the check. The first fields on MlCR line (serial, route. account. transaction codes) arc preprinted, and amount field is encoded after customer presents cheques to the bank. Cheques which are improperly encoded or of poor quality are rejected by HSRSS, they should be manually sorted and their data is manually entered. Banks get back their cheques in two lots, one fully sorted by branch and transaction code by HSRSS, and the other that still should be sorted by branch and transaction code by the bank.

The quality of whole operation hinges on reject rate of HSRSS, and this most important quality parameter  was found to be very high, say around 10 percent. The banks complained that they were receiving  too many rejected cheques  and  were left with lot of tedious, labor-intensive, and costly work to do after the NCC process was complete The manual handling of rejected cheques meant possible errors in  both data entry and sorting, that often resulted in reconciliation differences among banks. Also, the banks pay a penalty on every item, if their reject rate exceeds 3 percent.

The controlling authorities pointed out several times to manager of NCC Mr. Srinivasan, that the reject rate was too high and that customers were unhappy that the benefits of shifting to computerized processing had not been realized. Srinivasan describeed to his authorities that high reject rate of cheques  at Madras was due to peculiarity of cheques  presented there and pointed out high proportion of bank drafts from other places. In short, the blame was shifted elsewhere.

After about a year of this, the manager decided to look inward to try to improve performance, and choose one of his shifts-in-charge Kaza  Sudhakar, to do the job. It was felt that high reject rate was due to poor tuning of HSRSS equipment The engineers fine-tuned the equipment and cleaned the entire operations area to eliminate all traces of dust This reduced reject rate by only I percent. The NCC then issued a series of instruction- to the bank to help them improve the encoding of their cheques, but this did not help much.

NCC then embarked upon project to inspect all of the cheques presented by the banks and to separate and repair the bad cheques This reduced the reject rate by 2 percent. But at a tremendous time and labour cost. This approach was abandoned and it was decided to review where NCC had gone wrong

The clerks receiving cheques pointed out about process shortfall at the banks, where the cheques arc encoded. This meant that the solution will have to involve nearly 800 branches of 50 banks in and around Madras. But the potential benefits were great, so the NCC decided to go ahead. Five officers were allotted 10 banks each, with the assignment to train the banks' encoding staff. The first two months of the project produced negligible results, but as more and more banks were trained, the reject rate fell to 4.5 percent!

The banks were advised to continue training on ongoing basis, and to train every new operator, and to designate the officer to make sure that only quality cheques are presented to NCC. The banks were also invited to visit clearing facilities so they can understand the significance of encoding to the entire clearing operation. Though these steps had resulted in dramatic improvement, the reject rate still exceeded the international standard of 3 percent.

The NCC team once again reviewed the process with people from banks who pointed out that most of their cheques had five fields pre-printed on them: the banks merely encoded the amount field. The banks felt they were paying for the poor quality of the pre-printing done by cheques printers.

The printers were invited to NCC and asked to send proof batch of 100 cheques before printing a run, which often numbered in the millions. The NCC promised to run proof batch on HSRSS and deliver the report to the printer within half an hour. Some agreed to proof- reading their cheques, others did not. Subsequent, study showed that banks whose printers had proofed their cheques had a reject rate of less than 1percent: This shifted the balance in favour of checking proof batches, and soon all of the printers were doing so the overall reject rate for the clearing operation was now around 2 percent that proudly measured up to any international standard.

The benefits of this improvement were many. NCC manpower devoted to manual entry and sorting can be dramatically reduced and re-deployed to other areas in need of personnel. The banks were happy to receive almost all their cheques fully sorted by HSRSS and reconciliation differences among bank were reduced to negligible levels. Banks also can redeploy their manual sorting and reconciliation staff that had tremendous financial implication for them.

Srinivasan initiated measures to standardize all procedures that enabled achievement of low reject rates The staff was even rotated to see, if the standards can be met independent of personnel, and this was accomplished. Regular meetings were arranged with banks to solicit feedback on clearing operations and to elicit suggestions for further improvement

NCC’s quality project became truly total in dimension involving thousands of employees in 800 bank branches in Madras. It had full support of the top management and the newly empowered operation staff. One lesson taken from the project was that no operation can be improved just by tuning up equipment until the people connected with operation are also tuned up (trained). The improvement has to be continuous, without accepting defeat at any stage. Perhaps the most important lesson is that a project, when started, aimed solely at better customer service, ended up producing substantial cost savings, without a conscious effort in that direction .

Case problem: 

How many different approaches to quality Improvement were attempted by the National clearing cell? Which were the most effective and why?