Evaluation of Business Process Re-Engineering of SSNIT (Benefits Payment)
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Date
2008-08-19
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Abstract
The Ghanaian social security scheme has been administered by the Social Security & National Insurance Trust (SSNIT) since July 1965. The three minimum contingencies provided for under the SSNIT scheme included Invalidity, Old-age and Survivors' benefit types. Until 1991 when this was converted into a pension scheme, only lump sum benefits were paid. The time for processing and payment of benefits to claimants by the SSNIT was alleged to be too long and this tended to inconvenience customers thus creating claimant dissatisfaction and complaints. Questions were asked regarding competitiveness, efficiency and effectiveness of SSNIT operations. In a bid to address this allegation, there was an attempt at re-engineering the SSNIT benefits processes. The questions asked created some concern for the researcher leading to the study of evaluating the Business Process Re-engineering of SSNIT regarding Benefits Processing with the primary aim of analyzing volume of work / output in time and resources used to reduce customer waiting time. Random sampling from strata was used for data collection and analysis. Findings were shown in bar and pie charts. Major findings pointed to the fact that although the SSNIT held national pension data and funds, processes employed in the administration of the scheme were more manual than automated. As a result, payments of benefits of all the three types were delayed thus SSNIT could not achieve the 23 days limit as stated in the medium term strategic plan document for the current year. Commitment to the re-engineering project did not seem to be strong and this may affect the ultimate goal of paying benefits in 14 days by the year 2010. Technology was found to be available and full process automation was seen to be the panacea that would enhance the operations of the SSNIT so as to bring efficiency, effectiveness and customer satisfaction.
Description
A Thesis submitted to the Department of Information Systems and
Decision Sciences,
Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirements for the degree of Master of Business Administration, 2008