Club Management - March/April 2008 - (Page 14)

Technology Business Intelligence: Changing the Future of Private Clubs By Bill Boothe B ©iStockphoto.com usiness Intelligence (BI) is a term getting a lot of play these days in the private club industry. Pundits are writing and speaking about it. Club managers are asking for it. Club software providers are promising it. But with all this attention being given to BI, a basic question still lingers in many minds: Exactly how can business intelligence help the typical club? Thus far, the BI functionality offered has represented little more than ad hoc report writing and database queries. Such extractions of demographic, sales and activity data are readily available from a number of providers. That data can prove helpful in understanding sales operations and member behavior. However, the information obtained is focused primarily on the past, while the most valuable result of BI is to help predict the future. Of course, current BI solutions do provide some amount of predictive value. Knowing which of your club’s members have attended certain themed events can help predict future attendance at similar events. Knowing food and beverage sales totals by member categories or age ranges can help predict future sales as the club’s membership changes. Knowing who the top 50 spenders in the golf shop are can help predict…Uhmm What does that predict again? And that’s the trouble with today’s BI solutions for private clubs: lots of data, not much predictive value. All of this attention to BI – with only meager predictive results – has some club managers wondering whether BI is actually worth getting excited about. My mission in this article is to present a few examples of predictive BI that – if they were generally available to private clubs – would make a serious difference in long-term club management strategies throughout the industry. Predicting Member Resignations It’s no secret that over time, the industry’s focus has moved away from attracting new members and toward retaining existing members. Predicting which individual members are most likely to resign would provide club managers with a golden opportunity to intervene in the disengagement process. The result could avoid a resignation altogether, or at a minimum, prolong the term of membership. How could such predictions be accomplished? Behavioral predictions are old hat for advanced BI solutions. The process begins by developing a “behavioral proﬁ le” that predicts the future behavior in question: in this case, a membership resignation. The proﬁ le is based on the behaviors of the target group – resigned members. Fortunately, people tend to behave in similar fashions in preparation for signiﬁcant lifestyle changes. 14 • CLUB MANAGEMENT

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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