As data becomes increasingly available in organizations, the insights derived from it are not keeping pace. To maximize the potential of this data, businesses need to focus on creating a modern analytics environment that prioritizes both technology and the skills of their employees.
This is important regardless of the size of the organization, as a well-defined analytics strategy can lead to significant growth opportunities.
In this guide, we provide a step-by-step approach (drawing on our experience working with customers) to help your organization develop an effective analytics strategy roadmap.
What is an Analytics Strategy?
An analytics strategy is a plan for how an organization will use data and analytics to make better decisions and achieve its goals. Building an effective analytics strategy involves several key steps, including:
- Defining business goals and objectives
- Assessing data sources
- Determining the analytics needs of the organization
- Developing an analytics roadmap
- Monitoring and evaluating the progress of the analytics strategy
By following these steps, organizations can build an analytics strategy that helps them make data-driven decisions and achieve their business goals.
Step #1: Define your Goals
Defining business goals and objectives is the first step in building an analytics strategy. This involves identifying the key areas where the organization wants to use data and analytics to drive better outcomes.
For example, an organization might want to use analytics to improve customer retention, increase sales, or optimize marketing spending. Once the business goals and objectives have been defined, aligning the analytics strategy with those goals is important to ensure that it effectively supports the overall business objectives.
You can take a few different approaches to prioritize your business goals and objectives when developing an analytics strategy.
- Align With Company Strategy: first and foremost, it’s important to ensure that your business goals and objectives are aligned with the organization’s overall strategy. This will help ensure that the analytics strategy supports the company’s long-term goals and does not work at odds with broader strategies.
- Consider Impact: When prioritizing business goals and objectives, it’s also helpful to consider the potential impact of each goal. This might include time and dollar savings, revenue generated, or risk reduction. Goals that significantly impact the organization are likely to be higher priorities.
- Use a Prioritization Framework: Several frameworks are available to help prioritize business goals and objectives. One example is the MoSCoW method, which stands for Must-Have, Should-Have, Could-Have, and Won’t-Have. This framework allows you to prioritize goals based on their importance to the organization.
- Involve Stakeholders: It can be helpful to involve stakeholders in prioritizing business goals and objectives. This might include executives, employees, customers, and other key stakeholders. By gathering input from a diverse group of people, you can better understand the organization’s priorities as a whole.
Ultimately, the best way to prioritize business goals and objectives will depend on the specific needs and goals of your organization. By considering the impact of each goal, using a prioritization framework, and involving stakeholders, you can develop a prioritization strategy that works for your organization.
Step #2: Identify and Assess your Data Sources
Identifying data sources is the next step in building an analytics strategy. This involves identifying the data sources relevant to the business goals and objectives. These might include internal data sources such as sales, marketing, and customer data, as well as external data sources such as market research or industry data.
It’s essential to consider the quality and reliability of the data sources, as well as any potential issues with data privacy or security.
So what should you consider?
- Define Your Data Needs: First, clearly define your organization’s data needs. This might include the types of data you need to support your business goals and objectives and the specific questions you want to answer with that data.
- Inventory Your Data Sources: Next, take inventory of the data sources that are currently available to your organization. Examine your existing data sources, third-party data providers, and any other sources.
- Assess The Quality of Your Data: Once you have a list of your data sources, assess the quality of the data. Work with internal stakeholders to confirm the reliability and accuracy of the data, as well as any potential issues with data privacy or security.
- Identify Any Gaps: Based on your defined data needs and the available data sources, identify any gaps in your data. You should explicitly tie business objectives to specific data sources. Using this methodology, you can identify gaps in your business intelligence, analytics, and reporting.
- Determine How To Fill Gaps: Once you have identified any gaps in your data, determine how you can fill those gaps. You might need to build new data pipelines, purchase data from a third party, or simply transform your existing data to be more purposeful for business needs.
Step #3: Determine your Analytics Needs
Determining your organization’s analytics needs is another important component of building an analytics strategy. This involves identifying the specific types of analytics required to support the business goals and objectives. This might include dashboards, reports, predictive modeling, or real-time analysis. Tools like Tableau, Microsoft Power BI, and Sigma Computing can create interactive dashboards and reports.
So, how can you determine what exactly to create?
- Involve People: One of the most important considerations when determining analytics needs is understanding the needs and goals of the people using the analytics. Connect with stakeholders from different departments or teams and external customers or partners. By involving a diverse group of people in the process, you can get a better sense of the types of analytics that will be most useful and relevant to your organization.
- Review Business Processes: Another way to determine analytics needs is to review the organization’s business processes. Take time to understand the work currently being done, identify areas where data and analytics could be used to improve efficiency or effectiveness and determine the analytics that would be most helpful in those areas. Quantifying the value in terms of dollar savings, time savings, risk reduction, or new revenue potentially generated is imperative.
- Consider Technology Capabilities: Evaluate your existing analytics stack and ensure that your current technology infrastructure can support your organization’s needs. Don’t be afraid to bring in new technologies, even if there is overlapping solutions. Your goal should be building value–not simplifying your stack for “streamlining your stack”.
- Culture of the Organization: Finally, it’s essential to consider your culture when determining analytics needs. Examine factors such as the level of data literacy within the organization, the willingness to adopt new technologies, and the overall appetite for data-driven decision-making. By understanding your organization’s culture, you can better determine the types of analytics that will be most successful and well-received.
Once the business goals, data sources, and analytics needs have been identified, the next step is to develop an analytics roadmap. This involves defining the specific projects or initiatives that will be undertaken to implement the analytics strategy and identifying the resources (people, technology, etc.) that will be needed to support those initiatives.
The analytics roadmap should be flexible enough to allow for adjustments as your organization’s needs will change over time.
Step #4: Monitor the Progress
Finally, it’s essential to regularly monitor and evaluate the progress of the analytics strategy to ensure that it is meeting the organization’s needs and supporting the business goals. Be sure to conduct regular reviews, gather feedback from stakeholders, and make adjustments as needed.
By using tools like Tableau, Microsoft Power BI, and Sigma Computing to support an analytics strategy, organizations can make better, data-driven decisions that drive business success.
Like the process for building your strategy or a dashboard, you should identify KPIs and corresponding data sources, interview stakeholders, gather feedback, then create a dashboard to monitor progress!
Building an effective analytics strategy is key to making better, data-driven decisions and achieving business success. By defining business goals and objectives, identifying relevant data sources, determining the organization’s analytics needs, and developing an analytics roadmap, organizations can create a clear plan for using data and analytics to drive better outcomes.
Whether you need expert advise or have a few questions around analytics strategy, our team of experts would be happy to assist! Reach out today to phData for direction into building a data-driven business.