Analytics Revamp Drives Positive Business Direction
A health system’s plans to become a more analytics enabled organization drove the interest of the organization’s leaders in creating a new data analytics paradigm over the next several years. But where to start, what to focus on and how to execute this initiative?
Problem to Solve
As is common in most health care organizations, the greatest issue with data isn’t in its collection, but rather in its analysis and application. It’s not like experts didn’t see this coming. As far back as 2007, it was predicted that by 2020, doctors would face 200 times the amount of data and facts that a human could possibly process. Converting large data sets to actionable insights is a universal challenge.
A large health system faced a significant data analytics dilemma precipitated by the lack of an overarching, enterprise-wide data analytics strategy and vision. The health system’s plans to become a more analytics-enabled organization drove the interest of the organization’s leaders in creating a new data analytics paradigm over the next several years. But where to start, what to focus on and how to execute this initiative?
The health system’s leaders sought to gain an objective point of view from a resource experienced in applying data analytics to achieve operational excellence. Through prior engagements, Freed Associates (Freed) had specific experience with the culture and organization of this particular health system. Freed was engaged to assess the health system’s current and long-term data analytics needs.
Strategy and Tactics
Freed began by assessing the health system’s specific data analytics needs, based on internal feedback from throughout the organization. The goal was to ultimately develop, based on such feedback, a shared vision for the organization’s analytics, sufficient to meet current needs and robust enough to be prepared for the future.
In addition to interviewing key staff members outside of the analytics department, Freed also gathered input from select members of the analytics team to assess their current-state capabilities and identify any skillset gaps. This information would prove useful not only for creating an enterprise-wide analytics vision, but also in defining the key competencies needed when hiring a new analytics leader, a move which Freed recommended.
This initial assessment work revealed that the health system’s analytics needs had evolved in recent years from conventional, one-off request/response type interactions to requests that were increasingly strategic, and aligned with the organization’s long-term business plan. It was in this shift that the organization’s analytics had fallen short. Lacking strong strategic direction and vision, the analytics department had frequently missed opportunities to drive data adoption and analytics as an enterprise-wide strategic enabler, particularly among the organization’s clinical and quality leaders.
For example, not only did the analytics department lack an apparent vision and roadmap, it was also not service- or patient-oriented in its approach. As a result, there was a significant lack of internal trust in the capabilities of the analytics department. This also indicated the need for the organization to hire a strong, visionary analytics leader capable of quickly turning around the department’s work performance and reputation.
Based on this feedback, Freed developed a comprehensive set of recommendations to guide and advance the health system’s analytical capabilities. This also included creating a full-scale overview of a new analytics leader’s current and future-state responsibilities, with a corresponding revised job description which the organization could apply toward its recruiting and hiring plans.
To help the health system introduce plans for its new analytics model, Freed drafted an enterprise-wide operating model, through a series of interactive workshops designed to elicit key attendee input. This led to an overview for the organization of the potential risks and barriers of the new analytics model, as well as Freed’s recommendations for mitigation. From workshop attendee input, Freed emphasized the need for the analytics model rollout to achieve a series of “quick wins” to help gain internal acceptance.
Results and Conclusion
Ultimately, Freed was able to develop a strong, new analytics vision and model for the health system, broad enough to meet the organization’s future needs, and appealing enough to withstand inevitable internal scrutiny. This new model, while focused on operational excellence, also directly addressed the interest of the health system’s leaders in gaining the ability to become a more analytics-driven organization.
