Data collaboration occurs when two or more data holders combine their data to generate insights, creating value for all participants. By collaborating on their data and resources, organizations can enhance strategic initiatives, deepen partnerships, and turbocharge their go-to-market efforts. Perhaps most importantly, they can do so without disclosing identifiable or raw data regarding their customers.
To better illustrate the power of data collaboration, consider the following scenarios:
Scenario A: 10 companies are working on a data project, and each company is working in isolation.
Scenario B: 10 companies are working collaboratively on a data project while using combined resources.
In your opinion, which scenario will result in a 360-degree point of view of the project? Which scenario will yield the better outcomes?
The data model that’s creating business disruptors
Gillette, the iconic men’s grooming products company, was the market leader in the U.S. and worth $43 billion in 1999. Dollar Shave Club, a startup, began operations in 2011, followed by Harry’s Shave Club in 2013. Cut to 2019: the two startups are locked in a fierce battle for market share with Gillette, which has been steadily losing ground over the years.
How did two upstarts become powerful competitors to a multibillion-dollar company so quickly? A significant reason for their success was that both shave clubs actively used data collaboration to offer an innovative subscription service for products at a lower price point. Harry’s Shave Club and Dollar Shave Club are part of the growing number of companies that are utilizing data collaboration to expand and prosper.
In the technology sector, all 50 companies on MIT Technology Review’s Top 50 Smartest Companies use data collaboration including Amazon, SpaceX, and Nvidia. According to the Harvard Business Review, two-thirds of organizations are using data collaboration to “blend together five to 15 sources of data for analysis.” According to Andreas Weigend, director of Stanford University’s Social Data Lab, “the ability to collect, access, and analyze massive amounts of data has reached the point where no single entity can do all the work; great data collaboration is a necessity for success at any level of business.”
While sharing data creates security concerns, data collaboration software allows multiple parties to collaborate on data projects without sharing. Each party in the collaborative effort retains control of their data throughout the process. The software does not store data, nor does it make the data available to other parties. Instead, the data revealed is restricted to insights and matches of the collaborating members. Data collaboration is a shift in mindset. It is the difference between mining data in isolated silos and developing insights through collaboration of data and resources.
Key areas for data collaboration
There are three areas where data collaboration is most relevant today: globally distributed teams and in-context collaboration, workflow tracking across data stewards, and the development of a 360-degree point of view.
- Globally distributed teams and in-context collaboration: One of the challenges for globally distributed teams is their ability to share the same view of relevant information as well as insights. In a traditional data-sharing model, methods for viewing information are constrained by geographical location, where some members can see all the data while others have to wait until information is updated. Further, they cannot share insights in real time. Data collaboration easily overcomes these challenges by making the same information available to everyone, at all times. It also greatly simplifies in-context collaboration on a project and leads to faster, more effective decision making.
- Workflow tracking across data stewards: In a complex data project, it is important for data stewards to be able to blend different data sources and track workflow. Data collaboration dramatically simplifies the passage of information from one data steward to another, ensuring the best outcome for the project.
- 360-degree point of view: Perhaps the most meaningful outcome for businesses that use data collaboration platforms is having the benefit of a 360-degree view of a project. With all stakeholders having a full view of the relevant information, data analysis for developing and asking the right questions becomes that much easier. The most successful businesses use a 360-degree view for all projects.
Organizations create strategic partnerships based on mutual interests such as target customers, product integration, and potential future markets. Data collaboration allows partners to aggregate their data, enabling all partners to draw insights that create value for their organization, without compromising data security.