Data is being touted as the new oil. And yet data is all around us, whereas oil is only located in specific areas that can be hard to access. Insights are the rare commodity that data can provide. Perhaps it is therefore better stated that ‘insights can oil your business, should you be able to effectively harness your data’.
Unleashing the power of data-based decision making within an organisation has the potential to provide insights that identify what is working well and also what needs attention. In essence, it is the practice of using data smarter to drive performance. And yet many organisations are data-rich but insights-poor, meaning they are generating a lot of data but lack access, understanding and context of the data across the entire organisation to enable value to be created. Insights may be the new oil.
Accessing the right insights that give the evidence required to support critical decisions does not happen overnight. Often many organisations are making critical decisions based on minimal evidence from old and unqualified data. This problem is historically embedded in the perception that data is only a by-product of an activity, whereas today the value of data and the insights possible from it can make the difference between success and failure. Yet, the challenge remains in how to enable an organisation’s culture, processes and the inherent value placed on data so it is harnessed as an asset.
The use of a data strategy can improve an organisation’s ability to leverage digital technologies and tools to improve the capture, storage, management and access to data, thereby allowing that data to be turned into insights. Here are seven key areas to focus on in order to set an effective data strategy:
1. Define the guiding principles for enablement
- What are the four or five high level guiding principles on how data should be managed, treated and shared across the organisation?
- What are the business drivers that explain why the organisation needs to improve its data management practices?
- What is the strategic context of your data strategy – how does it interplay with organisational strategy, IT strategy, or other relevant government strategies and policies?
- What are the goals and objectives that the data strategy is aiming to achieve?
- Which current and planned initiatives may affect the enterprise data environment and architecture?
2. Determine what governance and processes will ensure ongoing quality and sustainability
- What is the data governance structure?
- Which groups will have what responsibilities and accountabilities for data?
- What is the approach to data quality management, aspects of data quality (accuracy, consistency, completeness and accessibility), data quality metrics and reporting?
- What are the relevant security policies, procedures, and responsibilities for the protection of sensitive data, data sovereignty, and data retention?
3. Set accountability guidelines and stakeholder expectations
- Who needs access to the organisation’s data and why?
- How does the organisation satisfy those needs?
- What policies are required for internal data access and data sharing platforms, as well as open data policy and platforms?
- How should your data be licensed, and where appropriate, how should your data be priced?
4. Catalogue what data is required and how it will be sourced
- How is reference data management and master data management identified and catalogued?
- What are the business cases for the use of data so that it provides value to the organisation, including data visualisation, data analytics, etc.?
- What metadata standards, data dictionaries, metadata management tools and processes apply?
5. Explore the concepts of standards, collaboration and reuse
- Are there any recognised data standards that should be followed to maximise data interoperability?
- What are the standard schemas, formats, naming conventions, definitions, minimum data requirements, and interchange standards?
- How will data be accessed and shared by users?
- What insights will different users want to draw from each data asset?
- How will data be maintained using data as an asset, investment in data sourcing, data maintenance and data updates?
- What is the five year investment plan for data assets?
6. Map the environment and infrastructure required
- What is the conceptual data model?
- What is the information architecture?
- What is the systems architecture and preferred platform?
7. Describe the necessary skills and capacity required to enable the strategy
- What people and skills does the organisation need to properly manage and extract value from its data?
- How will data skills be identified, developed or acquired?
- How will data knowledge be captured and shared?
GHD Digital assists our clients to manage their data in ways that provide insights that create lasting community benefit. We have a large team of data analysts, data scientists, and data strategists ready to turn your data into insights. We can assist by:
- Defining data governance and risk management strategies
- Conducting maturity assessments and recommendations for improving data management
- Developing data automation processes