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Data sharing and collaboration: the drivers of innovation
Our relationship with data has changed drastically over the past few years following global shifts in the way we work and interact with one another. These unprecedented changes have forced many businesses to shift their viewpoint on data from “protectionism to democratization.” But what is the next step for businesses to continue growing and, ideally, thriving?
Beyond treating data like the valuable commodity it is, sharing or collaborating with data, presents an even more lucrative opportunity for organizations.
For pioneering companies, data sharing is a Key Performance Indicator (KPI) that reflects their level of stakeholder engagement and measures how much value is delivered on an enterprise level. According to Gartner, those who “share data externally generate three times more measurable economic benefit than those who do not.”
This is due in large part to the fact that Data and Analytics leaders who promote data sharing “have more stakeholder engagement and influence than those who do not.”
What are data sharing and collaboration?
Data sharing, per Snowflake, is “the ability to distribute the same sets of data resources with multiple users or applications while maintaining data fidelity across all entities consuming the data.” Or, to put it simply, sharing data safely across your business ecosystem.
Data collaboration is another term that’s often used when people refer to data sharing. But it can have the added meaning of businesses working closely together with shared data to gain previously undiscovered insights. Ultimately, the goal is the same – to generate more value, unlock new insights, and boost levels of performance and innovation!
According to Snowflake’s Data Sharing for Dummies, modern data sharing, predominantly in the cloud, includes a few core use cases. For example, eliminating data silos for a single source of truth or improving business efficiencies by sharing live data with partners to optimize costs and streamline operations.
But before companies start plotting out how to use data sharing to improve or expand their ecosystem, there are a few things to consider. For data sharing to be successful, Snowflake Summit keynote speakers share that three core elements should be in place to establish a solid foundation: trust, diversity, and efficiency.
- Trust – all parties involved in data sharing must trust each other to share their sensitive data
- Diversity – everyone views problems differently. So when you bring two or more people together, you get a more diverse view that often leads to innovative solutions
- Efficiency – your collaboration must work smoothly and help you achieve your mutual goals, otherwise, you won’t gain any value
And once your foundation is in place, you’re able to collaborate more efficiently with your colleagues or external stakeholders. From there, the data-sharing relationships that you establish can be broken down into three workflows:
- Across Lines of Business (LOBs) – sharing internally among other departments, units, or subsidiaries
- Between external organizations – receiving and sharing data with an external business such as a business partner
- Monetized data and data services – accessing and sharing live data as a service (if you’re using a cloud platform)
Next, we’ll explore the benefits of these relationships in more detail.
Data sharing elevates business performance
Data sharing creates many advantages for a business. For instance, Gartner reiterates that organizations promoting data sharing will “outperform their peers on most business value metrics.”
So how does this work in practice? Consider all the partners involved in a supply chain, for instance. If these businesses – from the supplier to manufacturers and the marketing company – pooled their customer data, they’d have a much broader view of demand. And with these insights, they could bridge the customer gap with innovative personalization.
Now, let’s take it further, with a deeper look at data-sharing relationships and their benefits.
Line of Business data sharing
When data is shared across LOBs it means any combination of departments can share live data (on a cloud platform) and solve pretty much any business case. For example, a sales and finance team share data so they can collectively track revenue and sales to forecast organizational performance.
Sharing data with external organizations
This is the next level of data sharing, where organizations get and receive data quickly from external organizations such as vendors, customers, or other partners, and accelerate digital business. For example, retailer 84.51˚ securely sharing data with their CPG partners to optimize their supply chain.
In the past, monetizing was left to a few elite enterprises due to the high cost involved. However, today cost is no longer a barrier and more companies are bringing their data and services to market. How do they actually monetize their data? By charging for access to governed slices of their data, such as retailers generating insights from the information gathered from their point-of-sale software.
Overcoming barriers to collaboration
Executives may have concerns about added security risks as a result of data sharing.
Yet, this traditional way of thinking could stagnate business growth. Businesses shifting from a ‘don’t share data unless’ approach to a ‘must share data unless’ approach can unearth many new opportunities.
Along with traditional thinking, another potential barrier to collaboration is reliance on traditional methods of logic and accessing data, like Extract, Transform, Load (ETL), and copying or moving data. With these outdated methods come slow data transmission, stale data, error-prone processes, unsecured transfer methods, and a lack of scalability. The result is stunted business growth, no 360-degree view of customers, struggling to work with data across various siloes, and greater security risks.
Modern analytics systems, like cloud solutions, easily reduce the risks, costs, and frustration that traditional sharing methods bring.
Live data sharing with modern cloud architecture
Enterprises that utilize modern cloud architecture can safely and easily share data across their whole business ecosystem. Basically, they can access live data to share internally and externally, and uncover untapped innovation without any added risk!
Live data sharing, using cloud architecture such as Snowflake, produces another positive outcome: a reduction in costs. Cloud-based collaboration means the workforce (and external stakeholders) are all tapping directly into the same source of data, so there’s no longer any cost of replicating or moving data. Plus, with enhanced data quality, everyone is working with trusted data.
Businesses leveraging cloud solutions to share data also unlock new insights. And faster. They accomplish this by accessing live data from across their ecosystem on a granular level, and discovering insights that would otherwise remain hidden with traditional analytics models.
Another key difference in modern data sharing is concurrency, or the ability for multiple users to access the same data at the same time. Live data sharing is certainly a far cry from having to fight for limited, shared resources, being slowed down by poor product performance, and being plagued by inconsistent data.
What’s more, enterprises can also strengthen their business relationships. One Chief Data Officer captured this sentiment perfectly at Snowflake Summit 2022, stating that “If you want to go fast, go alone, but if you want to go far, go together.”
There will be data and analytics leaders who have concerns about the safety of sharing data both internally and externally, and those concerns are valid. But when you’re sharing data via a cloud infrastructure like Snowflake, you not only get controlled access with data governance, you benefit from built-in security measures to ensure your data is secure and aligns with compliance requirements.
Now, these benefits and features will go a long way to successful data-sharing, but what’s the best approach to kickoff this endeavor?
Six steps to kickstart data sharing and collaboration
Here are six steps to advance your business with modern data sharing, per Snowflake’s practical guide:
1. Identify opportunities – take a look at what opportunities are available both internally and externally. Focus on the data that will create the most value.
2. Define your stakeholders and their roles – who is in charge of data-sharing initiatives? Consider establishing a dedicated team, similar to a digital transformation dream team.
3. Establish the capabilities of your data sharing platform – do away with dated methods of sharing such as emails, and explore solutions like Astrato’s cloud-native analytics solution, built for the cloud.
4. Start with a proof of concept – experiment with new data sets to test their value. And establish how well the platform matches your business needs.
5. Initiate your data sharing strategy – get the right terms, conditions and processes in place and memorialize them in a flexible data sharing agreement.
Data sharing and collaboration, especially with cloud solutions, present an unmitigated opportunity for businesses to work collaboratively – innovating fast and enabling them to stand out from the competition.
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