3 Critical Challenges of Modern BI

Modern BI Three Critical Challenges and How can Healthcare Organizations Overcome Them? Continue Reading to Learn More


Why do we have so much data and yet so little insight? Healthcare organizations also have multiple BI tools and yet executives do not have timely information for decision making. What is holding back the ability to deliver insight at the point of need?

Here are some common modern business intelligence (BI) challenges for healthcare organizations, along with our take on how to overcome them.


Increasing volumes and complexity of data 

Digital transformation initiatives in healthcare have resulted in increasing volumes of data. In a world where data is being digitized through new devices, apps, and monitoring technologies, this means more tracking, analyzing, and storing massive amounts of data. Because of the data explosion phenomenon, the variety of data available is almost limitless. 

Data is also being produced in multiple formats (images, texts...) with different degrees of difficulty to be harnessed. The excessive data needs to be leveraged by businesses which can be a complex challenge for BI teams. Some lack the needed data preparedness to turn immense quantities of patient intake into insightful information. The result is a barrier to improving care and increasing efficiency that can be key to guiding operations, treatment plans, and reimbursements levels.  


High demand for insight

The ability to utilize data to understand customers and optimize services has become a tremendous competitive advantage. Executives need to understand their businesses, reports need to be timely and accurate, visualizations need to be clear and relevant, analysis needs to be fast and specific. This high demand for various insights will be a challenge for BI teams

As demand increases, more pressure will be on centralized BI teams who will find it impossible to cater all the needs for insight. This makes centralized BI teams a bottleneck in the delivery of insight. Overwhelming such teams can create other issues since the ability to extract accurate insight from data depends on the effectiveness of these teams. If not properly managed, this situation can lead to missed opportunities for better patient care or operational efficiency.     


The advent of self-service tools 

The need for fast and timely insight has led to frustrated business users initiating their own shadow reporting efforts. This trend is reinforced by modern BI tools being designed with self-service capabilities. However, if left uncontrolled, the self-service approach could degenerate into chaos with organizations struggling with data quality issues, trust, and siloed systems. 

An unmanaged or ungoverned self-service BI approach will lead to locally produced reports diverging from one another in different business units to the point of conflicting insight. This can ultimately hinder effective decision-making.


The solution: A Governed Self-Service BI Approach

To overcome the challenges listed above, it is important for healthcare organizations to adopt a governed approach to self-service BI. This means that businesses must embrace self-service BI but put governance infrastructure around it to ensure timely data can be found, understood, and trusted. To make this successful, BI managers must adopt a supply chain management mindset where they do not necessarily control all aspects of insight delivery but can influence key partners in the delivery chain.

In fact, data governance is a discipline that provides clear-cut policies, procedures, standards, roles, responsibilities, and accountabilities to ensure that data is well-managed as an enterprise resource. The discipline includes details on data: how it is transformed, stored, visualized, shared, and protected. This will better manage the availability, security, usability, and integrity of the organization’s data.                    

In creating governance standards, data will be managed by authorized personnel, users will know what data to trust for specific activities, and ongoing compliance with government regulations will be ensured. 

A governed self-service BI approach will help users deal with the complexity of data available, satisfy the demand for valuable insights that cater all department’s requests, facilitate, and enhance the self-service user experience. 


There is no doubt that modern business intelligence platforms help expand an organization's capabilities with more advanced tools than previously possible. But it does not come without new challenges. A good way to approach them is through governed self-service BI where users are empowered with tools, processes, and training but also bear ownership and responsibility for their outputs. This fosters a data culture where centralized BI teams are no longer sole producers of insight but catalysts for insightful decision-making at the point of need. 





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