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Friday 28 October 2011

DATA COLLECTION at MMDAs

 Why is effective data collection and storage functions important at your MMDAs?

Data collection is only useful if data are stored in a database that is easily accessible. When data are easily accessible, report writing can be improved and the analysis of issues in the dis­trict can be more holistic, taking into consideration indicators from various departments in the MMDA.
 Effective data management further optimizes the use of resources at the MMDA towards data collection, by avoiding the duplication of data collection activities, preventing the loss of valuable information through officer transfers, and maximizing the use of the data collected. 
Furthermore, having all the data both accessible and collated in a functional manner supports the allocation of resources to areas of greatest need and to strategic locations relative to existing resources.

What are the Benefits of Data Management?

So what do we derive, if we have an effective data management structure. The following are some of the benefits of data management
  •   Transparent, consistent and repeatable decision making processes
  •      A means of resolving community disagreements related to allocation of government resources
  •      Allocation of limited resources to areas of greatest need. 
  •       Use of data to support project/program proposals to development partners and GoG. 
  •      Efficient knowledge transfer between MMDA officers.
·         Facilitation of reporting by making information readily available and accessible when needed.

Barriers to Data Management

 We would love to conclude this post on data management with some of the challenges faced in developing a data base management structure in an MMDA context. It is our  desire that you would  be able to brainstorm and solve some of the under listed challenges  as  they come up. Please send us your feedback as and when these challenges are overcomed. We would be delighted to read from you. Some  common barriers to data management are: 
  1.     Unaware of what type of data is needed 
  2.    Inadequate IT and analysis skills 
  3.    Underutilisation of motivated individuals in the office
  4.    Human resource constraints

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