Scorecard and Metrics for Data Records Management
Quantification of 'data records and management' process is required to effectively manage one of the precious assets of a business and to efficiently utilize it to the maximum extent possible for the betterment of the organization.
This further goes into ensuring the authenticity, accuracy, security and integrity of the information. A holistic view helps in taking care of all the aspects, right from management's contribution to the system in place.
Some of the areas in which indicators can be framed are- Security, Quality, Efficiency and Implementation and Growth and learning. Security can be measured by using parameters like number of security systems, instances of leakages, retrieval methods and extent of compliance level.
This category is to ensure that management does not suffer due to loss of data.Quality can be built in the recording task via measures such as, rate at which internal data is retrieved, % increase in the number of users, inaccuracy index and % duplicity encountered.
Efficiency can be established and increased by using the KPIs like Deadline coverage index, Resolving ratio, % decrease in incidents when data leakage affected the operational effectiveness and % decrease in time experienced in gathering relevant data.
To grow and learn continuously, indicators that can be of help include- % of total workforce that is involved in the job of managing data, number of training sessions organized, number of guidance documents issued and % dip in time taken to correct the loss when data was mismanaged.
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What are the benefits of Data Records Management metric:
- Management of data records is about security and protection of information. So, it's quite reasonable to measure such KPIs as number of security measures taken or instances of information leakages.
- Manager soften measure costs required for data management and look for ways to minimize those costs.
- Decrease in information leakage instance will demonstrate efficiency of chosen approaches.
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More ideas on using Data Records Management KPI
Data records management covers a large number of aspects, some of which are 'taking care that all documents and data contained sources are in safe hands', 'content is easily accessible', 'right piece of information is obtained in complete and intact manner'.
One can maintain data records in useful fashion by bringing related and relevant technologies into use and arranging the data in understandable manner. It simplifies the operations to 'more than expected' levels as the benefits experienced (after appropriate data records management systems have been implemented) are multi-dimensional in nature.
Data are an important asset for the organization and if properly placed can provide it a strong enough support to help it spearhead its competitors. This is to say that data records are to be managed at any and every cost, if managers wish to take their operations to greater scale and heights.
However, one should note that management of strategies is another thing that needs to be supervised. A balanced scorecard serves the purpose in this direction by enabling the organizational workforce in measuring and calculating the steps taken for data management. By laying down a collection of metrics and indicators, tracking of record management is possible to a pretty detailed level.
More useful information for Management Evaluation
- Related metrics and KPIs for: Project Management, Product Launch, Operations, Risk Metrics, Change Management, Resource Management, Communication Measurements, Time Management, Cost Management, Knowledge management, Product Knowledge Management.
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Data Records Management Estimation Balanced Scorecard Screenshots
Metrics for Management Evaluation
This is the actual scorecard with Data Records Management Dashboard and performance indicators.
The performance indicators include: security perspective, number of security systems, instances of leakages, number of retrieval methods, degree of compliance level, quality perspective, retrieval rate of internal data, % increase in number of users, inaccuracy index, % duplicity detected, efficiency and implementation perspective, deadline coverage index, resolving ratio, % drop experienced in time to gather data, % decrease in the number of instances when data loss affected the operational effectiveness, growth and learning perspective, % decrease in time taken to correct the loss due to mismanagement of data, % of staff that is involved in data management tasks, number of training sessions arranged for the staff, number of guidance documents issued.
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