Creating a Data Sharing Business Model: Opportunities and Benefits

You and a team of explorers are lost in the jungle. Each of you has unique skills and knowledge, but none can survive or thrive alone. Sharing expertise and resources allows you to navigate the jungle, dodge jaguars, discover hidden treasures, and establish a new, thriving society. 

Your reality might be closer to the concrete jungle, but in business, going it alone only on your data is more likely to make you jaguar fodder. That’s why a data-sharing business model is so effective; sharing data with trusted partners helps everyone gain new perspectives, identify new opportunities, and achieve more tremendous success than they could on their own. It’s simply a better way to put your data to work.

To fully capitalize on the benefits of data sharing, businesses must establish secure and effective data-sharing agreements. This article will explore the opportunities and benefits of a data-sharing business model and provide practical survival tips for successful data-sharing partnerships.

The Benefits of the Data Sharing Business Model

Data sharing can provide numerous benefits to businesses of all sizes and industries. Let’s explore the benefits in more detail.

Access to new markets

Data sharing between companies helps everyone gain new insights into customer needs and preferences across different markets. By sharing with partners in different regions or industries, businesses can leverage new market intelligence to identify growth and expansion opportunities. Analyzing consumer behavior data might help identify gaps in the market so a business can develop new products or services to fill that gap. 

Revenue generation 

Collaborative data sharing doesn’t mean you give the goods away for free; you can sell your data to other businesses to generate revenue. Whether you sell data or share it, new data can help inform product development or uncover opportunities for new lines of business.

A data sharing strategy can also foster collaboration and partnership opportunities when businesses team up to develop new products or services for new or existing markets. That means an expanded customer base and a huge value-add to existing customers. 

Partnership and collaboration opportunities

Partnerships can manifest in many ways. By sharing Snowflake data across departments or teams, businesses can gain cross-functional insights into their operations, customers, and markets. 

External data and collaboration with customers, suppliers, or startups can spark new ideas and technologies. Data sharing can also facilitate research and development (R&D) collaboration. By pooling resources, businesses can achieve more in developing new technologies, products, or services. By working together, partners can gain fresh insights and develop products or services that meet previously unmet needs.

Increased competitive advantage

Shared data can create or increase competitive advantages. For example, a business that promotes data sharing may gain a better understanding of customer needs and preferences than its competitors. This can create a better customer experience and increase customer loyalty, which is an important source of long-term revenue.

Businesses that leverage data sharing tools and partnerships might also identify substantial cost savings. For example, by sharing data on supply chain operations with panthers, a business may discover an opportunity to optimize processes and add greater efficiency. 

Activity tracking and security

Sharing data with cloud services and platforms like Revelate automatically tracks data-sharing activities, including who accesses what data set, when, and from where. Revelate’s data web store tracks every action, allowing you to quickly identify security gaps, implement improvements to security measures, and determine whether to adjust access settings. That makes your data sharing more secure and ensures only authorized users can access your sensitive data.

Improved decision-making

Businesses can make more informed data-driven decisions with access to broader and deeper data and insights. When facing business challenges, it’s better to have research data with more data points for maximum context and accuracy. This also reduces risk and helps businesses avoid potentially costly mistakes. Data access enables faster decision-making, an important factor in fast-moving industries like technology, retail, finance, or healthcare.

Real-world data sharing use cases and examples

Here are just a few examples of real-world situations where businesses have seen positive results from data sharing.

1. Mastercard’s “Mastercard Data & Services” program enables businesses to leverage Mastercard transaction data for marketing, analytics, and other purposes. This has given many businesses insights into consumer spending behavior and knowledge to develop targeted marketing strategies
2. General Electric’s “GE Digital” program shares data from their equipment and machinery. This enables GE to provide recommendations for maintenance and optimization, increasing efficiency, improving performance, and saving on costs.
3. Airbnb’s program “Airbnb Data” gives businesses access to Airbnb’s data on travel trends and customer behavior. As with Mastercard’s program, this enables businesses to improve customer engagement and develop targeted marketing strategies.

How to Create a Data-Sharing Business Model in Your Organization

Building a data-sharing business model requires a strategic approach. By implementing the following steps, you can pave the way to reaping all the benefits of data sharing.

Establish business objectives

Before you do anything, define the business objectives that a data-sharing partnership will support. Your objective might be to increase revenue, access new markets, improve your customer experience, or reduce costs. Sharing data for the sake of sharing rarely provides high-value ROI, so be sure to have a clear objective.

Identify potential partners

Next, scope out potential partners. You can find potential partners at industry associations or leverage existing supplier or customer relationships. And don’t forget to look at competitors. Identify areas of overlap or complementary strengths with your competitors to determine if they may be good partners.

Existing data marketplaces are also valuable sources of potential data-sharing partners, since it’s easy to identify a business that already has the data types that align with your needs. Finally, take a look at publicly available data sources, including government databases, social media platforms, and other online sources. 

Establish data requirements, protocols, and a sharing agreement

Once you’ve identified potential partners, determine the data requirements for the sharing partnership. This includes:

• Types of data to be shared
• Data sharing frequency
• Data format

You’ll also need to set the terms and conditions of your data-sharing partnership. This includes data ownership, security and privacy, data usage, and financial terms or compensation.

This is also the best point to determine a data-sharing trust framework. A trust framework eliminates fear-based objections and outlines scenarios to foster trust among partners. There are four categories to identify in a trust framework:

1. Data sharing use cases: Outline your use cases for data sharing. These should line up with your business objectives
2. Perfect levels of trust: Determine what resources, tools, and technologies would ensure a “perfect” level of trust
3. Situational levels of trust: Define trust levels that match your use cases. Consider the risk/reward of “imperfect” data use in these scenarios
4. Remove elements of trust that misalign with situational trust: Consider what initiatives might be unsustainable or unobtainable, whether due to resources, technology, or budget. Then determine what’s needed to reach situational trust

Next, establish protocols for managing shared data. This includes:

• Data quality standards
• Data storage and backup procedures
• Data access and retrieval protocols
• Data privacy, governance, and regulatory compliance

Develop an analytics strategy and monitor performance

Once data has been shared, your organization should develop a data analytics strategy to analyze and interpret data. Visualization tools, machine learning algorithms, and other techniques can help drive insights and make informed decisions. 

Then track the metrics that correspond to your business objectives. This might include KPIs like revenue growth, customer satisfaction, or cost savings.

How Revelate Supports Effective Data Sharing

Revelate makes data sharing easy, regardless of who wants access to datasets. 

Here are just some of the ways Revelate enables the data-sharing business model:

1. Revelate automates data fulfillment to reduce pressure on technical significantly and IT teams. This is key to an effective data-sharing program, whether internal or external. 
2. Revelate provides a secure platform for sharing data with partners to protect data from unauthorized misuse or access.
3. Revelate helps organizations standardize data-sharing processes and protocols to ensure data is shared consistently. This improves data quality and reduces errors.
4. Revelate helps businesses integrate data from multiple sources. This provides a more comprehensive view of a business and makes it easier to analyze data and make informed decisions.
5. Revelate’s centralized sharing platform helps partners collaborate and communicate seamlessly to share real-time insights, feedback, and other information.

While the world of data may be a wild, unpredictable jungle, businesses embracing data sharing can unlock new opportunities and succeed in a dynamic environment. By working together, businesses can navigate the data-driven economy and emerge as true leaders in their respective fields.

To learn how to add efficiency and security to your organization’s data-sharing program, book a demo with Revelate today.