Most of us have embraced video calls and chat tools, but it is important to remember that collaboration isn’t just about communication. It is about combining insights and experiences to achieve the best possible outcomes. And the ways of doing this will differ for different objectives.
Establishing new collaborative processes is particularly challenging with a distributed workforce. The more pervasive and important role of data in many organizations as a result of the pandemic is a prime example of this.
Professionals with limited or no experience of using data to make decisions are increasingly required to integrate it into their working practices. In fact, research fom Qlik previously revealed nearly two-thirds (63%) of global employees make decisions with data at least once a week, despite just 21% of the working population being data literate. Putting the responsibility into the hands of employees to use data to help navigate their organization through new and changing environments, particularly when there is no one physically on-hand to show them how, presents significant challenges to CIOs and CDOs.
Organizations that have established a culture of data-driven decision-making to achieve Active Intelligence will attest that getting there is neither linear nor a solo expedition. It is not a case that “the computer says no” and that’s it. Not only does data dictate the outcome, but also the context which informed the thinking.
But, how can CIOs and CDOs foster a culture of data collaboration in their remote workforce? Here are three tried-and-tested approaches.
1) Create Collaborative Data Workspaces
Many businesses have traditionally kept data in silos. Sales and finance teams, for example, would hold data in their own environment, and would rarely share it – let alone collaborate. Why you ask? Platforms did not have the data integration capabilities to ingest different data sets and present them with consumable insights.
Today it is now far easier for organizations to create shared data workspaces that not only integrate disparate data, but leverage data exploration tools. This enables individuals to document the journey they have taken through data and how that has led to the insights produced. This shouldn’t just be at the end of the analytics process, as it typically has been to date. Collaboration should be built in across the analytics pipeline to support whole team decision-making processes and enable Active Intelligence.
But, this approach should not be limited to the confines of one organization. Shared applications can foster collaborative data-decision making with partners and suppliers to drive benefits for all. The i-supply application created by Wickes to manage its supply chain, for example, was integral in helping suppliers, like AkzoNobel, the producer of leading paint brand Dulux, understand which products were selling best during lockdown. This ensured its finite production capabilities were focused on the most popular products and, most importantly, it was delivering for customers in the face of disruption. The heat map developed by health care solutions provider WellSky is critical in enabling home-based care providers across the United States track COVID hot spots, anticipate locations with increasing infection rates, and distribute PPE resources to the locations where clinical staff need them most.
2) Develop a Consistent Data Vocabulary
For some, talking in “data” is like speaking gobbledygook. That is why how we visualize data is so important to the presentation of our insights.
But, what if every time we looked at a dataset, the way in which it was presented changed? For new users, this can be confusing and impacts their ability to confidently understand and articulate decisions based on data.
To overcome this challenge, Nationwide created a Visual Vocabulary across the building society, which guarantees all charts designed to inform decision-making are uniform in output. The Visual Vocabulary Application helps users to create a simple dashboard to display insights in a consistent and easy-to-consume format. By breaking down visualizations into logical categories and making them accessible to all data literacy levels, anyone can more confidently read, collaborate and communicate with data.
3) Encourage Data Storytelling When Presenting Insights
It is unsatisfying to flick to the last page of a book to learn how the story ends – its value and enjoyment is not just in how it concludes, but how the characters grew and the story got there. Similarly, when presenting data, the most impactful approach is to bring your audience with you on the journey that has led to your conclusions.
The most powerful data storytellers are those that communicate the journey they took through the data to determine the insights being delivered. Non-profit organization, Namaste Direct, for example, has found that the use of data analytics has not only been critical in helping it understand the impact of COVID-19 on the small businesses in Guatemala it supports, but also in communicating this back to its donors. The analytics program creates a presentation that draws directly from the charity’s databases to help them easily use data when communicating with their donors.
Fostering a Collaborative Culture Around Data
Organizations around the new world are rapidly adapting to the new environment, but this is a marathon, not a sprint. The changes to our working practices in the long term require organizations to think about the skills they’re investing in and practices they’re encouraging to ensure that their business can keep driving forward.
Establishing an enterprise-wide data-driven culture was no walk in the park even with all teams under one roof and, undoubtedly, the shift to greater remote working has not made it easier. But, these three tried-and-tested approaches provide ways that, no matter where their employees are located, CIOs and CDO can help put data at the heart of their conversations and combined decision-making.