Auto-Assign

Auto-Assign” is the capability of the software to assign guests to tables, row/seats or golf groups without significant intervention by the operator.  While it sounds a little scary, it really is not and it does eliminate some the the tedious work that is required to seat a complex or large event. 

Auto-Assign can be used to create either a first draft or finish up an event after the important seating has been done.

The original DOS version of the software had the limited capability to “auto-assign” guests from the wait-list based upon their wait-list date. Since then many modifications and new capabilities have been added.

Some of the more frequently used algorithms are:

JFK Libary - Pavilion

Museum Pavilion of the John F. Kennedy Presidential Library in Boston, MA; overlooking the Charles River.

  • Assign by Wait-list Date: assigns guests to tables based upon their wait-list date
    (acceptance date)  without consideration of other factors. Those with the earliest wait-list date are assigned to the best tables.
     
  • Assign by Priority: assigns guests to tables based upon their “priority”; guests with the highest priority are assigned to the best tables.  The “desirability” of the table is determined by it distance from a point in the room, such as the center front of the stage.
     
  • Assign by “Not the Same”: This algorithm was the first “auto-assign” capability developed for multi-event events. It can seat multiple events so that no one sits with the same person twice, unless intended.
     
  • Assign by “Sit With Request”: satisfies “sit with requests” by assigning requester and their requested to the same table. This module can be directed to satisfy a request only once, or as many times as there are events. In events where there are several classes of tickets, the software will identify where a guest of a lower class has been requested by a person of a higher ticket price, so that the operator can make a decision on how to resolve the situation.
     
  • Assign by Group: collects all of those identified as being within a particular group and seats them at the same table. If there are more in the group than can sit at one table, it looks for the nearest table with enough seats to complete the group.
     
  • “Round Robin”: this algorithm attempts to seat guests at multiple events so that they meet as many other attendees as possible.  It was developed to facilitate “meet and greet” sessions in conferences, where each session is only a few minutes long. The algorithm starts with 9 or more events.  While it is somewhat similar to the “Not the Same” algorithm, it varies from the NTS module because it tries to maximize the number of “news” and minimize the number of “repeats” as each guest is assigned.
     
  • “Annual Meeting - Smooth Mix”: this module is the most complex implementation to date and was developed to create draft seating solutions for three to five sub-events by considering the the extended attributes of each attendee. These attributes can include:
     
    • Business Specialization
    • Office Location
    • Country
    • Technical Expertise or Practice Area
    • Gender
    • Executive Position - “yes” or “no”. This attribute is used to assign hosts to each table.

    The module creates “seating solutions” with a maximum of diversity or range of attributes at each table, while also attempting to seat attendees so that no one sits together more than once during the meeting.

  • “Jett Algorithm”: this module  was developed at the request of a client to significantly reduce the work required to assign the seating for three events within a corporate event following specific “seating rules.” Previously it has required two staffers to work for between 15 to 20 hours to create a “seating solution.”  This module can create a preliminary seating solution in approximately 15 seconds.
  • It is required to:

    • Consider both “sit with requests” and “golf with requests” separately.
       
    • Honor “don’t sit with requests”
       
    • Create Table Hosts/Co-Hosts by:
       
      • Assign senior staff of the hosting organization as table hosts.
         
      • Assign less senior staff of the hosting organization as co-hosts of each table.
         
      • Assign the co-host to a seat opposite the primary host.
         
      • “Sex Balance” by attempting to create “female-male” or “male-female” pairs.
         
      • “Grade Balancing” by assigning co-host to tables where the host is not significantly senior to them.
         
    • Set the table designation, depending on the seniority of the host assigned.
       
    • Rates each tables “desirability” by computing its distance from a point in the room. This results in tables in the front row to be classified as more desirable than tables in the back row.
       
    • Assign awardees to VIP tables close to a center aisle.
       
    • Use “Not the Same” when assigning both the golf event and the second dinner.
       
    • Use the marketing/client relationships when assigning all events. The organization has sales organization data in the event data that can be described as “Supervising VP/Contact VP/Client” and clients are prioritized.  The software assigns clients to sit with their SVP and the CVP (or vise-a-versa) in successive events.
       
    • If there are openings at VIP tables to only assign senior clients to the open spaces..
       
    • Create a spouse event for the spouses and guests of the primary attendees and retain the VP/client relationship information.
       
    • When creating golf pairings, consider:
       
      • VP/Client Relationships.
         
      • “Golf With Requests”
         
      • the sexual make-up of the guests being assigned so as to create “all-male”, “all-female”, “couple-couple”, or “parent-child” pairings.

    The “request” processing portion of the Jett module can detect and satisfy “daisy chain” requests; that is where Guest A requests Guest B who requests Guest C who requests Guest D.  The module can also detect and satisfy “looped daisy chain requests” which is where Guest D requests Guest A in the example above.

    The resultant “seating solution” is not the final product. However, it does create a excellent starting point and allows more time to fine tune  it.


Performance Considerations:

    1) For a black tie gala preceding the dedication of an memorial in Washington, DC the “sit-with-request” algorithm matched up and seated 3400 guests in approximately 22 seconds.
     

    2) For the US Holocaust Museum and Memorial, the “grouping & sit with request” module seated about 3000 attendees in about 20 seconds.
     

    3) For a 350 person, 3X event (dinner, golf tournament and dinner) the Jett module can generate a preliminary solution in about 15 seconds on a Pentium IV Laptop computer.


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Version: 04/10/07