The realisation of the benefits in the Data Strategy is dependent on the effective alignment of data governance and management combined with technology development and clear articulation of business needs. The objectives set out the intended end outcomes for the data strategy supported through the applied governance, technology and processes to achieve the data vision.
Organisations should be committed to continuously improving the quality of data, making the whole business more efficient by reducing information and knowledge gaps. Operational and project data are key sources of data organisations rely on to provide everyday service and therefore their integrity is essential to reduce compliance risk and costs.
Data improvement objectives
Improvement in data quality and its relevance help to:
- Improve overall insights, limiting the “garbage in, garbage out” conundrum.
- Improve trust in our data and information, improving informed decision making.
- Eliminate waste, streamlining processing and reducing errors.
- Reduce costs from extra processing due to inefficient data and gaps.
- Improve client experience through trusted and correct data.
- Keep our people safe, through accurate information in the situation.
Increasing operational efficiency
- By maximising the use of asset performance data.
- By reducing duplication of information.
Reducing risk of failing to meet our operational metrics
- By responding to operational incidents quickly.
- By making well-informed investment decisions.
Improving customer experience and perception
- By education with data within the community
- By providing customers with personalised information updates.