How to Effectively Leverage Data to Take Your Company to The Next Level

Robert Audet, Partner in Advanced Solutions for Guidehouse, was recently interviewed by Authority Magazine in their series about “How to Effectively Leverage Data to Take Your Company to The Next Level”.

Are you working on any new, exciting projects now? How do you think that might help people?

In my role as a Partner at Guidehouse, I lead the Data Management service offerings and practice solely focused on helping organizations better manage data as an asset to enable more effective reporting, analysis, Artificial Intelligence, Machine Learning, and / or data sharing. Many of my current projects focus on defining strategies to help organizations either solve for specific unmet information needs and / or mature data capabilities across an organization to get more value out of its data to achieve mission and be more competitive in the market.

Helping organizations better harness internal and external data to drive value is so critical. Trusted, timely, and relevant data can lead to better outcomes such as patients receiving the proper medical care, pharmaceutical companies introducing needed prescription drugs more quickly, better servicing consumers inquiries…the list goes on. More than ever, organizations can benefit from having a clearly defined data strategy and roadmap to navigate through the complexities many organizations face (e.g., unprecedented growth in the variety, velocity, and volume of data; myriad of technology options to address data issues, increase sophistication in information needs from data consumers, etc.) when trying to maximize the value of their data.

Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” My work centers on the value of data visualization and data collaboration at all levels of an organization. So I’m particularly interested in this topic. For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?

In 2021, I published an article “A Data-Centric Culture is Critical to an Organization’s Success,” following a panel that I facilitated on “Data-driven Culture, Does it really matter?” at the MIT Chief Data Officer and Information Quality Symposium. Quoting from my article, “In summary, a data-centric culture represents the degree to which all people in an organization value trusted, understandable, accessible, visible, and connected data that improves insights, supports behaviors, and fuels better operations and strategic decisions. A data-centric culture also represents shared beliefs and values related to data established by leaders and then communicated and reinforced through policies and behaviors.”

A data-centric culture expresses itself through the approach organizations take to combine technical capabilities, workforce skills, and information sources to draw in the best possible data, effectively analyze it, and use insights to guide management actions. Organizations with a data-centric culture make decisions based more on information and evidence and less on intuition, personal bias, and false narratives. They use data to inform strategic decisions, and day-to-day operations. In addition, they make data available across the organization to empower employees and reinforce strategic direction. For example, a CDO at a large federal government agency rolled out staff-level dashboards with the metrics leadership used to track performance, so people in the field could see the broader picture they were impacting with their work.”

Becoming a data-driven organization takes far more than just data visualization and data collaboration, but these are important elements. Organizations need to develop the business acumen to interpret data visualizations to draw the necessary insights, and then understand how to translate insights into action and have the courage to act.

Given the often decentralized or federated approach to managing and using data, data collaboration is critical to help bridge organizational divides, and ensure the various roles responsible for data are collaborating at the right points along the data lifecycle. For example, data stewards and data owners of a data asset oftentimes need to collaborate on remediation of data quality issues, reconciling master reference data, etc. On the other end of the spectrum, data analysts and data scientists may want to collaborate on the creation of a new analytical model or data visualization to work through various complexities related to the model. Bottom line, collaboration at all levels of an organization starting the C-Suite down to those stewarding a data domain, is critical to become a more data-driven organization.

Which companies can most benefit from tools that empower data collaboration?