Maximizing Your Data Budget: Essential Strategies for Optimizing Your Data Investment

Data is becoming an increasingly important asset to run a business. At the same time, data continues to be an underfunded asset in most companies. For this reason, it’s critical to get the most out of your data spend. In this article, we’ll explore several ways to make sure you’re best positioned to optimize your data budget and set your company up for long-term success.

1. Evaluate and Reevaluate Vendors Regularly

The data landscape is constantly evolving, with new vendors entering the market and existing ones expanding their offerings. By periodically reviewing your current data vendors, you can ensure your organization is always benefiting from the latest innovations, competitive pricing, and improved data quality.

Many companies stick with the same vendors for years without question, but in doing so, they may miss out on cost savings or better-quality data. Routine evaluations also open the door to negotiation opportunities, allowing you to adjust contract terms or achieve bulk discounts if multiple departments use similar data. To optimize your budget fully, make vendor reviews a routine part of your data strategy.

At Nomad Data we’ve seen that one of the most common reasons companies don’t look for alternatives to existing vendors is that when they originally searched, there were only a handful of vendors. Many don’t realize the number of alternatives that have entered the market, regardless of the data type. It’s critical to continuously compare your current vendors against new ones in the market when it comes time for renewal.

2. Consolidate Licenses to Avoid Redundant Data Purchases

One of the most common ways businesses overspend on data is through redundancy. When different teams operate in silos, they might unknowingly purchase the same or very similar datasets, leading to unnecessary costs. Consolidating licenses across departments not only saves money but also facilitates a more unified approach to data use across the organization.

For instance, if the marketing and sales teams both need access to similar datasets, consolidating their needs under a single license can lead to significant cost reductions and improved data access for all involved. Creating a streamlined system for sharing data across departments can help you leverage volume discounts, manage fewer vendor relationships, and reduce administrative overhead.

3. Track and Monitor Data Usage Across Teams

Data usage can vary greatly from one department to another, with some teams heavily relying on specific datasets while others use them minimally or not at all. Implementing a system to monitor data usage across departments helps ensure that your investment aligns with business needs. It’s essential to establish usage thresholds to determine when a dataset is underutilized and assess its return on investment (ROI).

For example, if a dataset is only accessed a few times a year, it may not be a necessary ongoing expense, and those funds could be redirected to higher-priority resources. Data usage monitoring allows you to make informed purchasing decisions, and, over time, helps you develop a culture of data responsibility within the organization. Encourage teams to review their data needs periodically and adjust their requests based on usage patterns.

4. Standardize Data Vendor Management to Avoid Duplicate Purchases

In organizations where teams work independently, duplicate data purchases are a common and costly problem. Standardizing data vendor management across the organization can prevent this waste, allowing you to gain better visibility into which data each team requires and ensuring that purchases are coordinated to avoid duplication. By establishing clear protocols for vendor selection, approval, and data sharing, you can minimize redundant spending and streamline your data management process.

Additionally, fostering cross-departmental communication around data needs can reduce miscommunication about data resources and allow teams to share insights on effective datasets. This collaborative approach enables you to align data purchases with broader business goals and cut costs without sacrificing data quality or availability.

Nomad Data’s Data Relationship Manager: A Comprehensive Solution for Data Budget Optimization

To effectively implement these strategies, a data vendor management tool like Nomad Data’s Data Relationship Manager (DRM) can be invaluable. Nomad Data’s DRM is designed to help organizations track and optimize their data spend, providing insights that can significantly impact your bottom line.

Track Dataset Usage

With Nomad Data’s DRM, companies can monitor the usage patterns of every dataset, ensuring that they are only paying for resources that add value. This functionality is essential for identifying underutilized data and reallocating budget toward high-priority datasets.

Discover Alternative Vendors for Similar Data

Nomad Data, through its market of nearly 4000 data vendors, can help you identify other vendors who offer comparable data, allowing you to periodically review vendor options without conducting extensive manual searches. This feature ensures you’re always in a position to negotiate the best deals and prevent vendor lock-in. It also keeps you up to date on emerging vendors who may be a better fit for your data-driven use cases.

Centralized Departmental Tracking

Nomad Data’s DRM offers visibility into which departments are using which datasets, making it easy to spot opportunities for license consolidation and cross-departmental coordination. By centralizing data usage tracking, you can ensure all purchases align with real usage and business priorities.

Avoid Duplicate Purchases

Perhaps most importantly, the DRM helps organizations prevent unnecessary, duplicate purchases by flagging potential redundancies. This feature protects your budget from waste and promotes a more cohesive approach to data management across departments. As soon as an employee is connected to a vendor through Nomad, they are immediately alerted if they are speaking with a vendor previously known to the organization.

Conclusion

Having a repeatable data procurement process is essential to maximize the ROI on your data budget. By regularly evaluating vendors, consolidating licenses, tracking data usage, and implementing standardized vendor management processes, companies can avoid overspending while still maintaining access to the high-quality data that drives business success. Nomad Data’s Data Relationship Manager is designed to streamline this process, providing a single platform where you can monitor, manage, and maximize the value of every dataset in your portfolio.

The issue many companies face is that their data procurement process is extremely ad hoc and oftentimes lives outside of the data organization. Having central procurement as the sole source of oversight for data purchasing usually doesn’t work well. Data is a far different type of asset than a typical product or a service that a company acquires. Unlike other products, assessing the value of data to an organization is typically far more time consuming and complex than services from other vendor types. Having the central data team build out a procurement process that better matches the requirements around data is likely to lead to much better outcomes.

Investing in a comprehensive data management solution like Nomad Data’s DRM not only simplifies data oversight but also helps build a data-centric culture focused on accountability and efficiency. To explore how Nomad Data’s Data Relationship Manager can help your company optimize its data spend, reduce redundancy, and gain a clearer view of data usage, reach out for a demo today.