By Brendan Watkins, Chief Analytics Officer, Stanford Children’s Health.
The purpose of analytics is to provide insights using data to empower people in an organization to make smarter decisions. It gives decision-makers a better understanding of what’s going on, what happened, why it happened, and what’s likely to happen based on hard data. When done right, analytics will improve the overall performance of the organization.
It is important to ensure that insights are strategically disseminated throughout a company to maximize benefits. Just as an organization’s culture is an important factor in its performance, its data culture is crucial to disseminating this wealth of knowledge and information.
What is data culture?
Data culture is a broad concept that encompasses several aspects. The most obvious aspect is how much value executives place on data and analytics, and how leaders are aligned with the organization’s data strategy. How leaders view analytics has a huge impact on the motivation of analysts to improve their skills in reading, interpreting and analyzing standardized data (also known as data literacy). Data culture requires connection between the analyst cohort and the organization’s data strategies, and establishing a network that permeates the organization is critical.
Set up networks
The formal way to establish this network is to set up federated analytics and named analytics power users. This structure allows for alignment and gives analysts the tools, data, and support they need. It is important that these analysts derive value from the collaboration and are encouraged to acquire valuable skills and relationships.
The informal network of relationships is key to developing a positive and impactful data culture. The data management structures should support a strategic roadmap of analytics initiatives undertaken as partnerships between the central analytics team and analysts in business areas. Shared ownership in developing analytic solutions fosters a vicious circle where team members have deeper buy-in.
It highlights the value of the governance that brought about the projects and the project team members build strong relationships by working together in the trenches. After the initiatives are completed, relationships are positioned to remain strong, allowing analysts to pick up the phone for support and tuning rather than waiting in designated forums. Positive relationships breed others as the mood and energy among peers takes hold.
Rent (and train) for culture
Fundamental to creating a positive data culture is hiring people for an appropriate culture. Technical skills can be learned and improved, but it is much more difficult to influence softer skills such as collaboration and communication. It’s important to reward positive relationships and partnerships that foster data culture. Members of the Analytics team must be connected to the mission of the organization and understand its key priorities.
Ideally, the team will embrace (and be ambassadors for) the core principles of analytics and share in the challenge of advancing data culture. By creating an atmosphere within the analytics team that rewards great people for challenging thinking and enabling creativity, highly skilled people connected to the mission will foster data culture once they find it meaningful, rewarding, challenging and fun.
Analyzing should be fun. It is an essential function for an organization because it leads to better decision-making by providing valuable insights. It is a journey to improve understanding, so the work is never finished. While it is important to develop analytics solutions and capabilities, once a baseline of this is available, advancing the data culture can have more impact.
It’s up to leadership to create the right environment to foster a strong data culture. From here, staff can take over, own and distribute it throughout the organization.