When building a new analytics platform, most companies begin with the finance department. As the heart of the company, finance plays a critical role in decision-making, managing budgets, and ensuring overall financial health. Focusing on finance first allows businesses to address high-impact areas and create immediate value. In this article, we’ll explore how to prioritize data projects, using the finance department as a practical example to guide your efforts.

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1. Start with the Finance Department’s Pain Points

The finance team often works with critical data, such as budgets, cash flow, and revenue forecasts. Begin by identifying their pain points and the data they need most urgently. Examples might include:

• Monthly Reporting Delays: Are manual processes slowing down reporting?
• Cash Flow Visibility: Is there a clear picture of inflows and outflows?
• Expense Tracking: Are departmental expenses difficult to monitor in real time?

For instance, if the finance team struggles with consolidating data from multiple systems, a project to automate data integration for monthly reports could be a high priority.

2. Involve Finance Stakeholders Early

The success of your analytics platform depends on buy-in from end users. Involve key finance stakeholders right from the start to ensure the platform meets their needs. Organize workshops or interviews to:

• Understand Their Processes: Map out current workflows and challenges.
• Define Urgent Needs: Ask what insights would have the biggest immediate impact.
• Set Success Criteria: Collaborate on measurable goals for the platform.

For example, the finance team might identify forecasting as their top priority and define success as significantly streamlining the process such as reducing the time spent on preparing forecasts from days to just a few hours.

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3. Prioritize Data Projects Based on Value and Feasibility

Work with the finance team to rank potential data projects by their business impact and ease of implementation. Focus on:

• High-Value, Low-Effort Projects: These are quick wins that build momentum, such as automating monthly financial reports.
• Critical Pain Points: Address issues that cause the most friction, like reconciling data between systems.
• Data Availability: Choose projects that rely on readily accessible and clean data.

For instance, creating a dashboard to visualize daily cash flow might be easier to implement than building a complex forecasting model, but both can deliver high value at different stages of the platform's rollout.

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4. Focus on Core Financial Metrics

When starting, prioritize projects that deliver insights into key financial metrics. These might include:

• Revenue Trends: Understanding sales and revenue over time.
• Expense Tracking: Monitoring spend by department or category.
• Profitability Analysis: Identifying the most and least profitable products or services.

Building an initial dashboard with these metrics provides immediate value and gives the finance team tools they can use right away, helping to gain trust and support for the analytics platform.

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5. Iterate Based on Feedback

As you roll out the platform, continue to collaborate with the finance team. Regular check-ins ensure the platform evolves to meet their needs. Practical steps include:

• Demo Sessions: Showcase prototypes or early dashboards to gather input.
• Feedback Loops: Ask users what works well and what could be improved.
• Agile Adjustments: Adjust priorities based on real-world usage and feedback.

For instance, after launching a revenue dashboard, the finance team may request additional drill-down capabilities for product-specific trends.

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6. Integrate Cross-Departmental Insights Gradually

Once the finance team has a robust set of tools, you can expand the analytics platform to other departments, such as sales, operations, or HR. However, the finance department’s data can act as the foundation, connecting with other areas like:

• Sales Revenue vs. Budget: Aligning sales performance with financial forecasts.
• Operational Costs: Monitoring the cost-efficiency of processes.
• Payroll Analysis: Understanding workforce costs as part of overall spending.

By starting with finance, you ensure that the platform provides a strong, business-critical foundation before tackling broader initiatives.

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Conclusion

Prioritizing data projects when building a new analytics platform begins with understanding the urgent needs of key stakeholders, such as the finance department. By addressing their pain points, involving them in the process, and focusing on high-impact projects, you can create a platform that drives immediate value and builds trust across the organization.

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Start small, involve your users, and let the platform grow into a tool that transforms how your business makes decisions.

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