Success/Failure Case Study No.3
Problems for a Natural Resource Ministry's Scientific Information System
Case Study Author
The "Fisheries Scientific Information System" is part of its home Ministry's overall management information system.
The application was supposed to provide scientific information for decision-making on fisheries management and development activities. This arose because of a belief that natural resource management and development decisions should be firmly based on good quality statistical data and processed information, and that this would improve the quality of natural resource decision making. The application was primarily designed to support the Ministry's most senior level of decision making; especially the Minister and Directors General when they were dealing with policies, goal-setting and specific investment decisions. It was also designed to provide assistance to those fisheries scientific staff who were to actually operate the scientific information system.
Having an overall responsibility within the area of natural resources, the management and development of those resources (including fish stocks and the associated fishing industry) were two principal tasks of the Ministry. Both resource management and development were seen as highly sensitive areas, and some felt that sound scientific information should always be present to support decision making in these areas. It was intended that the scientific data produced would minimize subjectivity and personal judgement, and would also reduce associated problems such as the use of personal agendas, and the subjective biases that arise in decision making from individual cognitive styles.
The main stakeholders affected by this application were of two main types. Within the Ministry there were the fisheries researchers and, to some extent, the senior decision-making officials. External to the Ministry were the country's fishermen, actual or potential investors in the fishing industry, other external bodies seeking data and information, and other departments with interests in natural resources, livelihoods, trade and other related areas.
Impact: Costs and Benefits
The costs of implementing the scientific information system include significant direct financial costs: for hardware and software (covering purchase, installation, operation and maintenance) plus personnel salaries for all those involved from design to implementation to operation. There were also social/political costs that arose from a mounting clash of interests with other departments which sought to avoid the information the system produces, and also with the fishermen themselves who often sought to go in their own directions, regardless of any 'scientific' priorities. Moreover, there soon came work dissatisfaction on the part of the primary stakeholders (the scientists and researchers who developed and operated the information system) when senior officials failed to make use of the information that the system provided.
Evaluation: Failure or Success?
It has been largely unsuccessful. There have been some positives:
- the system does capture, process and store data that could be used at some point in the future;
- some useful decisions and actions were taken on the basis of information provided by the system;
- the primary users (scientists/researchers) were able to get hands-on experience in handling computerised fisheries data;
- some data was supplied to external users; and
- there has been some creation of fisheries knowledge, for example, in relation to types of fish stocks and relative abundance of different species.
However, there has also been the very significant negative that the main objective - of feeding statistical information into senior officials' decision making, and of thus changing the nature of that decision making - has not been achieved. Almost all decisions made by senior officials and senior committees are taken without regard to information provided by the system; instead, decisions are still made on the basis of gut feelings or personal priorities/objectives, and this has continued to lead to negative outcomes.
Enablers/Critical Success Factors
- User commitment . Strong commitment of the primary users (scientists and researchers) to the system.
- Donor assistance . Financial and technical assistance provided by aid donor agencies, especially at the early stages.
- Continuous training . Continuous training for involved staff.
- Poor leadership . Shortcomings on the part of senior officials: a lack of commitment to the system that included deliberate neglect and denial of the system's value, coupled with a level of arrogance about their own importance.
- Tough environment . A difficult operational context that included a harsh climate and a lack of infrastructure for research.
- Poor research . Both limited quality and limited numbers of researchers.
- Get senior commitment . Don't proceed, or don't expect resounding success, unless there is strong committment from senior officials.
- Ensure sustainability . Where donors have helped initiate an e-government system, there should be a clear commitment to, and a clear plan for, ongoing system sustainability.
- Processes as well as data need to change . eGovernment systems often produce new information (e.g. more logical statistical information) that differs from the information previously used for decision-making in government. The decision-makers must understand that they will have to change the way they make decisions, and they must then be willing to make that change. Without this, the information produced is going to be of little value.
Author Data Sources/Role : Application User/Participant Role
Outcome : Largely Unsuccessful. Reform : eAdministration (making strategic connections in government).
Sector : Economic Services (Livestock and Fisheries).
Region : East Africa. Start Date : 1995. Submission Date : July 2002