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The use of Business Intelligence to
          maximise terminal retail activities




John de Giorgio
Managing Director – Concessionaire Analyzer Ltd
www.shireburn.com/airports
Agenda




         ontext

         hat are the issues?

         hat is the opportunity?

         hat is the solution?
Context

 ownward pressure on landing fees from
 carriers

 irports are increasingly reliant/focused on
 retail sales

 evenue share lease agreements common in
 airport terminals
 s   fixed rent, thresholds, minimum guarantees etc.

 sually identical % across products within a
 concession despite different product margins
What are the Issues?

 eed to analyze retail sales to drive
 airport’s decision-making but…..

 anual collation of concessionaire
 sales data by airports
 •   Inefficient
 •   lack of control & auditing
 •   latency of information
     Generally data is aggregated per day
  No transaction/product level details
  Barriers to deep analysis of retail data
What is the Opportunity?

  o analyze retail sales transaction data
  through Business Intelligence
  techniques:
  •   to gain an understanding of retail patterns
      & trends
       •   sales by route, carrier, product category etc.
  •   to be able to improve negotiations with
      concessionaires and airlines
  •   assess effect of promotions
  •   tweak retail sales mix
  •   maximize retail revenues and income
Prerequisite

  utomate collection of
  concessionaires’ sales data into a
  data warehouse
  •   Transaction level detail
  •   Ease upload of sales data by
      concessionaires
       •   Web services
       •   Standard file formats
       •   Automation possibilities
Business Intelligence (BI)
Business Intelligence


  ancy name for reporting?

  nalyse, monitor, plan & project

  ashboards, scorecards, KPIs

  ombine sales, passenger, lease &
  property data into analysis
BI Examples


  ncome/m2 by concessionaire

  ncome by route, airline, day/time etc.
  •   Income per pax by route, airline etc

  ncome by product category

  op 20 product categories by income

  ross margin per pax by concessionaire
  •   Important for per pax fee monitoring
Secondary Effect
Opportunities

 mplement revenue sharing at product category
 level to reflect product margins

 acilitate move to per pax based fees

 mprove control of concessionaires & reduce
 fraud, under-reporting etc
 •   Completeness checks
 •   Sales gap analysis
 •   Mystery shopping

 mplement standard POS solution for some/all
 concessions
 •   opportunity for real-time sales data
The Solution?


        More info in exhibition space and at
        www.concessionaireanalyzer.com



      Carolina Court
      Ta’ Xbiex, XBX 1425
      Malta
      Tel +356 2131 9977
      info@concessionaireanalyzer.com
      www.concessionaireanalyzer.com

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Ca+ ppt nicer 1.

  • 1. The use of Business Intelligence to maximise terminal retail activities John de Giorgio Managing Director – Concessionaire Analyzer Ltd www.shireburn.com/airports
  • 2. Agenda ontext hat are the issues? hat is the opportunity? hat is the solution?
  • 3. Context ownward pressure on landing fees from carriers irports are increasingly reliant/focused on retail sales evenue share lease agreements common in airport terminals s fixed rent, thresholds, minimum guarantees etc. sually identical % across products within a concession despite different product margins
  • 4. What are the Issues? eed to analyze retail sales to drive airport’s decision-making but….. anual collation of concessionaire sales data by airports • Inefficient • lack of control & auditing • latency of information Generally data is aggregated per day  No transaction/product level details  Barriers to deep analysis of retail data
  • 5. What is the Opportunity? o analyze retail sales transaction data through Business Intelligence techniques: • to gain an understanding of retail patterns & trends • sales by route, carrier, product category etc. • to be able to improve negotiations with concessionaires and airlines • assess effect of promotions • tweak retail sales mix • maximize retail revenues and income
  • 6. Prerequisite utomate collection of concessionaires’ sales data into a data warehouse • Transaction level detail • Ease upload of sales data by concessionaires • Web services • Standard file formats • Automation possibilities
  • 8. Business Intelligence ancy name for reporting? nalyse, monitor, plan & project ashboards, scorecards, KPIs ombine sales, passenger, lease & property data into analysis
  • 9.
  • 10. BI Examples ncome/m2 by concessionaire ncome by route, airline, day/time etc. • Income per pax by route, airline etc ncome by product category op 20 product categories by income ross margin per pax by concessionaire • Important for per pax fee monitoring
  • 11.
  • 12. Secondary Effect Opportunities mplement revenue sharing at product category level to reflect product margins acilitate move to per pax based fees mprove control of concessionaires & reduce fraud, under-reporting etc • Completeness checks • Sales gap analysis • Mystery shopping mplement standard POS solution for some/all concessions • opportunity for real-time sales data
  • 13. The Solution? More info in exhibition space and at www.concessionaireanalyzer.com Carolina Court Ta’ Xbiex, XBX 1425 Malta Tel +356 2131 9977 info@concessionaireanalyzer.com www.concessionaireanalyzer.com