How to to develop a data strategy
Big data is the new reality across industries. Whether you work in finance, healthcare, marketing, manufacturing, or another sector, a strong data strategy can give your organization an edge.
However, creating and implementing an effective strategy requires specialized skills. Read on to learn how to develop a data strategy for your organization.
What is a data strategy?
A data strategy is a comprehensive plan that outlines your organization's data practices. It details data analytics and management processes, defines data responsibilities by role, and organizes the technology that manages your data.
Executives, entrepreneurs, and business leaders can benefit from learning to develop a data strategy that aligns with their organizational goals.
Data strategies go beyond describing processes; they offer a long-term vision for using, storing, and protecting data. You must have both technology and strategic leadership skills to create a data strategy tailored to your organization's unique needs.
Why is it important to have a data strategy?
Having an organization-specific data strategy can help you in the following ways:
- Operational efficiency: A clear data strategy improves efficiency, allowing organizations to optimize their processes and make data-driven decisions faster.
- Scalability: Growing organizations can implement data strategies and build clearer data architecture to scale their operations.
- Data security: Implementing a data strategy can improve data security, reduce risk, and improve customer satisfaction.
Steps to develop a data strategy
The right data strategy can help an organization improve decision-making, reduce data privacy risks, and accomplish long-term objectives. Explore some steps you can take to create a data strategy tailored for your company's needs.
1. Define your data goals and objectives
Developing a data strategy starts with a clear definition of your goals and objectives.
First, determine your organization's data stakeholders. This group can include anyone who manages, collects, or utilizes data, plus executives. You'll need their buy-in to implement a data strategy successfully.
Next, get specific about your goals. Does your organization need to improve data quality or accessibility? Are you hoping to boost efficiency or strengthen security? Creating specific, measurable goals can help you plan and assess the effectiveness of your strategy.
Finally, align your data strategy with long-term business goals. This can improve buy-in and demonstrate the value of a new data strategy.
2. Determine your data landscape
Before developing a new data strategy, you'll need to complete a thorough audit of your organization's data landscape.
This audit should assess the current state of data processes and workflows in order to identify gaps or areas for improvement. For example, data silos can prevent organizations from leveraging their data, and over-securing data can create unnecessary barriers.
During a data systems audit, you will take inventory of your organization's data sources, collection and storage methods, and current tools or systems. Be sure to also provide an overview of your data architecture and infrastructure.
3. Establish a data governance framework
With a comprehensive view of your current data landscape, you can begin to create a data governance framework. This framework should include data management strategies, storage policies, and privacy standards. It should also assign responsibility for data quality, management, and reporting within the organization.
A strong data governance framework can help your organization comply with data regulations and protect the integrity of its data. For example, a framework may allow you to implement compliance measures around data protection. It's also an important step that demonstrates your commitment to transparency both internally and to customers or clients.
4. Develop a data reporting process
How will your organization analyze data, and what steps can you take to ensure the quality of your data management practices? A data reporting process can help answer these questions.
Consider your data cleaning and validation standards to ensure that your organization produces high-quality data. Basing these standards on data science best practices can empower team members to draw actionable insights from raw data.
Your reporting process may also incorporate data decision-making, data accessibility, and stakeholder reporting standards. It can be helpful to list the data tools and technologies that your organization will use to collect, analyze, and visualize data.
5. Implement your data strategy
Once you've created a data strategy that includes standards and an established organizational structure, it's time to implement it. The implementation stage should include a roadmap with milestones, a budget, and expected outcomes for each stage.
When deploying a new strategy, you'll also need to consider the training needs of stakeholders. The rollout should encourage a culture of responsible data handling, with transparent processes for different stages of the data lifecycle.
6. Monitor and measure the performance of your data strategy
Once your data strategy is in place, you'll regularly assess its operations to identify areas for improvement. Measure performance against key performance indicators and goals to assess the data strategy's contribution to organizational priorities.
You can also collect internal and external user feedback to improve data management practices. Scheduled reviews and audits can help your strategy stay up-to-date and adapt to new technologies or changing organizational needs.
The results of these performance measurements can create a roadmap for updating your data strategy.
Put your data strategy into motion
The best data strategies share key characteristics, including a clear vision, measurable metrics, and delegated responsibilities.
As you're developing your strategy, prioritize clarity and persuasiveness. Organizing your strategy into a cohesive document and incorporating feedback phases can improve your launch.
Stakeholders who review the data strategy should see the benefits of your approach and how it aligns with organizational objectives.
If you're charged with building or implementing a data strategy, developing your data analysis, data management, cybersecurity, and data science skills can increase your confidence and effectiveness. Executive Education programs from edX can help you upskill in these areas.