In a thriving data culture, people already know that collaboration is a true necessity to a functional working environment. Even better, data collaboration is also key to transformative results.

Traditionally, teams in any organization have worked in silos and kept information to themselves. There may be one reporting group for each department, with everyone else acting as a passive consumer of that group’s output. With true data collaboration, you see much more personal investment into the product and many more teams working together. And because data is widely available and shared, every team has a role in reporting, and every person can take a proactive interest in the results. So how do you get there? 

Data collaboration ground rules
Here are a few rules of thumb to get your first data collaboration program off the ground:

  • Have a strong use case in mind. Collaboration for its own sake won’t yield meaningful results.
  • Get a project sponsor on board. Ideally this is an upper-level manager or executive stakeholder. Teams often don’t like to work together, at least initially, so you have to have an agenda as well as someone with authority behind you to help act on it. 
  • Build a product that would be helpful to the organization. Even gathering the data on what that product should be requires collaboration, which is a change in mindset for many companies.   
  • Don’t forget data governance. Data governance solves a major problem in many companies, which is that people don’t trust their data. With good governance practices and technology, you can ensure that the data is a good source of truth and inspire confidence that the collaborative data your colleagues gather has been vetted and is accurate.

Any project or program that requires cross-functional analysis is a candidate for data collaboration. Finance and HR might have to collaborate for budget and head counts, for example, or manufacturing may need to work with a commercial group. 

Unsurprisingly, the larger the company, the more that data becomes segmented. This means that collaboration is essential so you don’t keep reinventing the wheel from one department to the next. Of course, when you do assemble collaborative data, you also benefit from the opportunity to understand each other’s contributions, so you can work to build better and more insightful data products.

The recent pandemic has accelerated the data collaboration trend in public and private enterprises. As many of us witnessed firsthand, the need for data increased sharply, either to come up with a sound forecast or to reduce wasted expenditures. In both scenarios, companies were on the hook to explain to stakeholders what was going on and how they could solve it.

How data collaboration drives shared benefits
When I worked at the state government level, a lot of people considered data as a nice to have rather than a necessity. Once the pandemic hit, we had to collaborate across our department to change how we gathered data, who we worked with, and where team silos had to be taken down to improve data access and get insights out. This was an all-hands collaboration born of a crisis, because the Governor’s office, the Secretary of State’s office, and the media were looking for answers about things like unemployment benefit backlogs. And because it was all taxpayer money, there was a lot at stake.

In private enterprises, it’s just as common to see a lot of people ingesting data via PowerPoint or flat files. Without up-to-date data collection and visualization tools, they aren’t able to interact with data and get tangible context into decisions being made. As a consultant and an employee I’ve seen firsthand the impact of training people on collection and visualization tools. You start to see a lot more valuable insight generated, but just as important a thirst for more information, data sharing, and deeper partnering. You can almost see the physical difference when someone realizes that they don’t have to work from their gut anymore, and they can help enable more informed decisions than shrugging and saying, “Well, it seems like this is it.” 

The lasting impact of data collaboration? You’ll start to see more cross-functional teams where there were few before. This gives people new avenues to pursue and new opportunities that didn’t exist. Working from a broader platform, people also are more passionate about gathering insights from their data and building their own visualizations rather than just “sending out” for someone else to build them. As any data leader knows, that sense of empowerment, confidence and yes, collaboration, is where transformation begins.