Club Management - March/April 2008 - (Page 15)

Consider a club that is experiencing a membership transition from older couples to younger families. That migration will challenge club management to predict what will be needed, and when, to accommodate the activity levels generated by the then-current membership. BI technology is well-suited for marking those behavioral tendencies, identifying those same markers in members of the remaining population and assigning a level of likelihood that the marked individuals will follow the target behavior. For clubs, the behavioral markers for this example might include member spending and activity patterns, spouse and family usage patterns, purchase size and frequency patterns, demographic factors, such as member age and health, age of spouse and children, etc. BI already is working in other industries to predict similar behaviors with great success. It can work in the club industry as well. Predicting Future Dues Revenue Long-range planning is a mainstay of the private club industry. But what good is planning if the club’s future revenue stream is based on guesswork? That’s the concern of many club managers as they struggle to establish a long-term strategic plan that is supported by predictable future revenues. Fortunately, BI has been predicting revenues in other industries for more than a decade. One important revenue-predictive design for private clubs is based on member age. Clubs with older memberships worry about the impact of age-related resignations. This predictive model would calculate the lost revenues for future years, based on the age progression of members during that time span. For clubs whose dues are based on age brackets, such an analysis would save countless hours of Excel spreadsheet work. For clubs with membership in transition (say older to younger members), the predictive model would calculate the impact on dues of older members being replaced by younger members and would track the progression of individual members through age ranges and membership categories. What makes this model even more valuable is the ability for clubs to create “what if” scenarios to determine impact on future dues revenue. What if the patterns of the past ﬁve years continue unchanged for the next ﬁve years? What if the percentage of younger new members increases and the average age of the membership decreases? What if the club creates a new “senior” membership and allows older members to step down rather than resign? What if? Of course, predictions of this sort also could be performed for joining, initiation and other recurring fees. Predicting Club Facilities Requirements Long-range planning isn’t all that difﬁcult for relatively stable clubs experiencing only minor changes in their membership proﬁ les and activity levels. Dynamically changing clubs, on the other hand, face serious challenges in predicting future usage needs for dining, events, sports and other facilities. As a club’s membership changes, so do the demands made by the members upon the club’s infrastructure and facilities. For example, consider a club that is experiencing a membership transition from older couples to younger families. That migration will challenge club management to predict what will be needed, and when, to accommodate the activity levels generated by the then-current membership. BI can be used to predict activity levels, which are analogous to facilities usage. Predicting the future number of covers, for instance, by dining style, day and meal period, will allow management to determine what type of dining facilities and capacities will be needed to accommodate future memberships. BI’s “what if” functionality will allow clubs to base predictions on past trends or on an array of assumptions, some generated by the BI engine and others based on external industry predictions. Conclusion This article only highlights what predictive BI technology can mean for the club industry. Examples abound of BI results that could have a profound impact on long-range planning and decision making. Seeing into the future is every club manager’s dream. But the point of predictive technologies is not just to see the future but to adjust current behaviors to effectively change the future. Alan Kay, the father of object-oriented programming, had it right when he said, “The best way to predict the future is to invent it.” Consider that concept the next time business intelligence is on your club’s agenda. ❚❘ About the author Bill Boothe is director of club/resort technology consulting for RSM McGladrey, Inc., the nation’s ﬁfth-largest accounting, tax and consulting ﬁrm. He has assisted more than 325 private clubs and resorts with the planning, evaluation, selection and implementation of computer technology in all facets of their operations. Bill can be reached at bill.boothe@ rsmi.com and (561) 682-1638. MARCH/APRIL 2008 • 15

Table of Contents Feed for the Digital Edition of Club Management - March/April 2008

Club Management - March/April 2008 Contents President’s Message Board Governance Technology Human & Professional Resources 2008 CMAA President Peter Homberg: A Profile in Courage, Perserverance Welcome, CMAA 2008 Board of Directors Club Events: Bring Magic to Your Members Club Adopts 'Dependent Parent' Membership Policy Paving a Path to Success Groundbreaking Project Measures Environmental Data for Golf Courses Paradise Preserved HFTP Insight New Directions Global Outreach Products and Services Marketplace Advertiser Index/Advertisers.com Club Wrap

Club Management - March/April 2008

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