In today’s digital economy, data is more than just a byproduct of business operations—it’s a central asset. Companies are increasingly adopting a “data as a product” strategy to unlock the full potential of their data, transforming it into a valuable, monetizable asset. This shift is revolutionizing the way businesses think about data, not just as a resource to be managed but as a product to be developed, packaged, and delivered. In this guide, we will explore five essential steps to help you build out your data as a product strategy effectively.
Step 1: Define Your Data Objectives
The foundation of any successful data as a product strategy starts with a clear understanding of your business goals. Aligning your data strategy with these goals is crucial. Whether you’re looking to improve decision-making, generate new revenue streams, or enhance customer experiences, your objectives will guide every aspect of your DaaP strategy.
Understanding Goals and Key Assets
To define your data objectives, start by analyzing your broader business goals. Are you aiming to increase operational efficiency, enhance customer satisfaction, or drive innovation? Each of these goals will require different data assets and approaches. For example, if your goal is to enhance customer satisfaction, you might focus on leveraging customer data to gain insights into preferences and behaviors.
Once you’ve established your business goals, the next step is to identify the key data assets that can be turned into products. These could be anything from customer data and market research to operational metrics and product performance data. The key is to identify data that holds the most value for your organization and its stakeholders.
Setting Measurable Outcomes
With your key data assets identified, it’s essential to set measurable outcomes that will define the success of your data as a product strategy. These outcomes should be aligned with your business goals and provide clear metrics for evaluating the effectiveness of your strategy. For instance, if your goal is to generate new revenue streams, you might measure success by tracking the sales of data products or the number of new customers attracted by your data-driven insights.
Step 2: Develop a Data Governance Framework
Secure and effective data governance is critical to the success of any data as a product strategy. Effective data governance ensures that your data is managed, protected, and used responsibly. Without a strong governance framework, your data products may be unreliable or non-compliant, leading to potential risks and missed opportunities.
Creating Policies and Procedures
To develop a strong data governance framework, start by creating clear policies and procedures that align with your data objectives. These should cover everything from data collection and storage to access control and data sharing. Effective policies will ensure that your data is handled consistently and securely across your organization.
Clearly defined roles and responsibilities are likewise essential for maintaining data governance. Assign specific individuals or teams to oversee different aspects of your data governance framework. This could include data stewards responsible for maintaining data quality, compliance officers ensuring adherence to regulations, and IT teams managing data security.
Step 3: Build a Scalable Data Infrastructure
A scalable data infrastructure is essential for supporting your data as a product strategy. As your data needs grow, your infrastructure must be able to accommodate increased demand without compromising performance or security.
Selecting the right tools and technologies is critical to building a scalable data infrastructure. Consider cloud-based solutions that offer flexibility and scalability, as well as data management platforms that integrate seamlessly with your existing systems. The right tools will enable you to manage large volumes of data efficiently and effectively.
Data accessibility is another key consideration when building your infrastructure. Ensure that relevant stakeholders can access the data they need when they need it, without compromising security.
As you build your data infrastructure, it’s also important to plan for future growth. Your infrastructure should be designed to accommodate increasing data volumes, new data sources, and evolving business needs. By future-proofing your infrastructure, you can ensure that your data as a product strategy remains effective and relevant over time.
Step 4: Implement Data Monetization Strategies
Data as a product is all about turning data into a valuable asset that can be monetized. Implementing effective data monetization strategies is key to realizing the full potential of your data.
There are many ways to monetize data, from selling data products and services to leveraging data insights to improve business outcomes. The first step in implementing a data monetization strategy is to understand the different opportunities available to your organization. This might include selling raw data, offering data-driven services, or using data to optimize existing products and services.
Packaging Data for Market
Once you’ve identified your monetization opportunities, the next step is to package your data for the market. This involves creating data products that are easy to understand, use, and derive value from. Consider the needs of your target audience and design your data products to meet those needs. This might involve creating user-friendly dashboards, reports, or APIs that allow customers to access and use your data.
To ensure the success of your data monetization strategy, it’s important to monitor market demand continually. Stay informed about industry trends and customer needs, and be ready to adjust your data products accordingly. This might involve expanding your product offerings, updating your data sets, or enhancing your data-driven services to meet changing customer expectations.
Step 5: Integrate Data-Level Security into Your DaaP Strategy
Secure data management is a critical component of any data as a product strategy.
An innovative, data-level approach brings several benefits. Traditional perimeter defenses, such as firewalls and encryption, are not sufficient against today’s threats. This is why leaders in secure data management have turned to data-level security as the next step in information protection. Data-level security redefines the perimeter by embedding security directly into the data itself, ensuring that it remains protected regardless of where it travels or how it is used.
Better yet, this method doesn’t rely on silos. Siloed data is one of the greatest impediments to effectively implementing DaaP, but the segmentation that causes these silos is often seen as an essential part of keeping data safe — a tradeoff that’s not necessary with data-level security.
A data-level approach eliminates the inefficiencies associated with data silos, creating a unified and secure governance framework across all data assets. Whether the data resides in your CRM, accounting software, or cloud storage, data-level security ensures easy access and consistent protection. This approach not only streamlines data management but also strengthens trust and reliability within a DaaP ecosystem.
Moreover, data-level security simplifies the security architecture by reducing the need for complex layers of defense. Instead, the data itself becomes an active participant in its protection, maintaining its integrity and confidentiality even when it moves beyond traditional network boundaries. This is particularly critical in a DaaP strategy, where data is both a product and a trusted currency.
Maximize Your Data as a Product Strategy with Sertainty
Building out your data as a product strategy requires careful planning and execution. By defining your data objectives, developing a strong data governance framework, building scalable data infrastructure, implementing effective data monetization strategies, and integrating data-level security, you can unlock the full potential of your data and turn it into a valuable asset.
As the digital landscape continues to evolve, organizations must adapt to stay competitive. Integrating data-level security into your DaaP strategy is essential for protecting your data products and ensuring long-term success. Sertainty technology bridges the gap between cutting-edge security technologies like self-protecting files and zero-trust network access with a software development kit that can be seamlessly integrated into a wide range of applications. Explore Sertainty’s solutions to protect your DaaP and other data assets, and position your organization to thrive in today’s digital world.