Data Strategy
Data is a valuable resource but often businesses find it challenging to unlock that value, due to the sheer amount of data available - as well as the challenges which come with collecting, organising, interpreting and activating it.
Research shows that 54% of organisations still struggle to provide stakeholders with data that can inform their decisions.
A data strategy can assist businesses with overcoming these challenges and accessing the value of their data while efficiently using their resources.
DATA STRATEGY
Unlocks the power of your data
Helps you to harness the volume of data, which is always increasing
Improves data management across the entire company
Assists with efficient resource allocation
Decision-Ready Data
Decision-Ready Data is critical to informing business decisions and deciding on strategic direction. However, research shows that although organisations have been building analytics and insight capabilities, over 54% of organisations still struggle to provide stakeholders with data that can actually inform their decisions.
Common Data Quality Challenges include:
Accuracy, comprehensiveness, completeness, centralisation, source of truth.
Common People, Process & Technology Limitations include:
Process design, platform/technology, capacity, agility/execution speed, lack of automation, analytical capability, organisation alignment, prioritisation.
A data strategy can assist businesses with overcoming these challenges and access the value of their data while efficiently using their resources.
Importance of having a Data Strategy
Data Strategy Helps Unlock the Power of Data
Volume of Data Is Increasing - 90% of the data in the world became available in the last 3 years.
Data Strategy Improves Data Management Across the Entire Organisation
Data Strategy Helps You Use Resources Efficiently
Data strategy is a central, integrated concept that articulates how data will enable and inspire business strategy.
Essential Data Strategy Principles
Integrating Data and Eliminating Silos
Makes data more accessible and fosters collaboration between different departments
Helps people get data more efficiently and can enable new data-driven projects
Streamlining Data Collection and Sharing
Having established procedures means you can collect more data more efficiently, and that the data you collect will likely be higher-quality
It also keeps your information consistent and well-organised, which makes it easier to use and helps you derive value from it
Setting Clear Goals and Objectives for Data Management and Use
Your goals will drive your data strategy and activities and help you improve how you handle data
Making Data More Visible and Accessible
It’s crucial that you find a way to store data so people can quickly find and access the information they need without having to create copies of it themselves.
Making Data More Actionable and Easily Shared
Putting your data in a consistent, usable format will reduce the number of steps employees need to take before they can use it and make it easy to share within the company
Establishing Clear Processes for Data Management – Data Governance Model
Data governance refers to setting rules and standards for how individuals and groups within an organisation manage data. The goal of data governance is to make data easier to access, use and share to achieve broach broader business goals
The key goals of a governance model should be clearly defined to ensure success:
⊹ Avoid siloed decision-making
⊹ Use synergies between business units to improve data assets
⊹ Provide business units with support and resources to prioritise data challenges resolution
⊹ Support the management of key initiatives across business units
Establishing Guidelines for Data Analysis and Application
Define guidelines for how employees should analyse and use data
