Share of Usage Models Better Predict Growth

Growth is a common objective among virtually all healthcare systems.  Most healthcare executives, like most executives in other industries, believe that improving customer satisfaction, likelihood to recommend, or Net Promoter Score levels will drive growth. Certainly these metrics are important and are correlates of provider choice.  However, there are other ways to predict patient choice and usage more accurately and identify strategies to gain increased service usage more effectively.   

Better Models to Enable Growth 

There are a variety of “Attitudinal Equity” and “Share of Wallet” models that focus on the amount of “spend” customers devote to an organization.  An abundance of research favors these models over traditional satisfaction models in predicting purchase (usage) behaviors and organizational growth¹

These models seek to reflect the subjective disposition of consumers toward a brand as a concept, going beyond the functional services offered under its name and symbols, i.e., how much strength a brand has in attracting a consumer before he or she considers the features of any particular service from that brand.  For patients, Share of Wallet, or “Share of Usage” (SOU) is generally the percentage (“share”) of their expenses for, or usage of, a service that goes to the provider organization.  Healthcare is notably different from many other organizations in that patients’ service usage is frequently funded by insurance companies.  This argues for a share of usage orientation in place of a share of wallet focus. In many cases insurers restrict the patients’ choice of providers.  Still, in most cases, there are quite a few options that can be considered by most patients and the SOU model is very relevant in determining the intensity of their usage of all available options. This perspective also applies to affiliated physicians, another key customer set of healthcare systems. 

Share of Usage Models 

The SOU models are based on “Share of Wallet” principals² but focus specifically on the share of services used by patients (and physicians) of a healthcare system, relative to the usage at competing systems.   The choice of the Share of Wallet models primarily rests on their simplicity and the comparability of performance in predicting growth and identifying growth foci relative to the Attitudinal Equity and Power of Mind approaches that aspire to provide the same intelligence³. 

How an SOU Approach Drives Growth 

If we view the growth objective of increasing market share for a healthcare system, we recognize that: 

Market Share = Penetration X Service Usage X SOU 

where Penetration is the proportion of customers (patients/physicians) who use a system’s services at least once in a given time period, Service Usage is a measure of how heavily customers use a system’s services relative to all customers who have need of those services, and Share of Usage is the percentage of customers’ usage of a system’s services vis a vis that of competing systems. 

A SOU growth strategy is therefore about getting more customers to allocate a greater percentage of their usage to a system’s services.  Experience informs that it is almost always easier and more cost effective to improve customers’ share of usage (of the same or other types of services) than it is to acquire new customers. 

To deploy a SOU growth strategy requires that this metric be calculated at the organizational level, and preferably at each major service level. One simple approach to this is the “Wallet Allocation Rule”.  This calculation uses a brand ranking approach to predict the share of usage by customers and is easily obtained as: 

WAR = (1 – Rank/Number of brands+1) X (2/Number of brands) 

This approach was validated as predicting change in share of wallet over time as accurately, or more accurately, than other models seeking to foretell this factor, and is notably less requiring of calculation intensity. 

The Necessary Ingredients 

The key issue though is gathering data with respect to customers’ ranking decision rationale.  The reasons customers may be satisfied with a provider will likely differ from the reasons they rank a provider higher or lower.  It is these reasons that must be understood to increase usage and drive specific service and overall organizational growth. 

Key factor categories that contribute to customer ranking decisions typically include the customers’ descriptors, the customers’ experiences, and the customers’ emotions associated with an organization/service and its competitors. As an example, if a healthcare system was interested in understanding its SOU for birthing services, customized surveys of expectant mothers, women who are thinking of having children, and women who have given birth at your and competing organizations would be in order.  Asking them to rank their perception of the organization and its competing organizations overall, and for birthing services, would provide the necessary input to determine an SOU score with this segment for birthing services and your organization overall.  It would also provide valuable guidance as to how your organization can increase SOU.  

SOU Can Drive Increased Physician Utilization  

These same decision constructs can be used, employing slightly different verbiage, with physicians who use your and competing system’s services, say for surgeries.  In this case the calculations should be even more precise in that there are more frequent and continual experiences to frame factor determinations and resulting organizational rankings.  Further, in most cases, there is activity data that can be attached to the rankings to more effectively identify physician targets for attention to increase Share of Usage. 

Customer Loyalty Perspectives Enhance SOU Growth Strategies 

Some researchers have indicated that Share of Wallet (or Share of Usage in this instance) is the ultimate measure of loyalty³.  However, this view is very incomplete. SOU does not address all of the ways that customers can deliver value back to a healthcare system and thus support overall growth.  For example, the SOU factors do not consider loyalty factors such as such as referral and/or experience rating behaviors that are influential in gaining additional market share.  There are also compliance benefits that can decrease cost and/or improve outcomes that are not specifically addressed in SOU calculations.  Increasing SOU is a key consideration in increasing Customer Lifetime Value, but it is important to consider these loyalty metrics in concert with SOU ranking factors to assess the full value that a customer set may or are delivering back to the organization. It is therefore important in gathering customer ranking factors to also address loyalty behaviors so as to compute the total customer-delivered value in driving growth. For more insights on the breadth of customer-delivered value from loyalty initiatives see this. 

In Sum 

To Conclude, health system growth strategies will benefit from increased attention to Share of Usage strategies.  The metrics driving the understanding of the status and value of this approach can be easily obtained, given proper determination of service and brand perceptions.  The drivers of usage will usually be different from experience satisfaction measures and more powerful in driving growth strategies and tactics. This approach can be augmented by understanding and motivating a variety of additional ways that customers drive value, and thus growth, to the organization. 

  

1. Louw, Alice, and Jan Hofmeyr (2012), “Reality Check in the Digital Age: The Relationship between What We Ask and What People Actually Do,” in 3D Digital Dimensions 2012 (ESOMAR Publication Series Volume S355: ISBN 920831-0261-4), Deborah S. Fellows, editor. Amsterdam, The Netherlands: ESOMAR.  
2. Aksoy, Lerzan, Timothy L. Keiningham, Alexander Buoye, and Joan Ball (2016), “Linking Satisfaction to Credit Card Decisions: An Application of the Wallet Allocation Rule,” International Journal of Bank Marketing. forthcoming.  
3. Jones, Thomas O., and W. Earl Sasser, Jr. (1995), “Why Satisfied Customers Defect,” Harvard Business Review. 73 (November- December), 88-99.