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Famous 6
Presentation On Ecourier,Cablecom &
Bryan Cave: Delivering Value Through
Business Intelligence
CASE STUDY
SUMMARY
SWOT ANALYSIS
QUESTIONS AND ANSWERS
CONTENTS
 SAI MANOHAR ( LEADER )
 ANIRUDH
 AKSHAY
 VIKNESH
 VYSHNAV
 TIBI
GROUP MEMBERS
Ecouriers carry's 2000 packages around London each day.
The operational business intelligence allows the company to keep
real time tabs on customer satisfaction.
Ecourier as a mission to sought out IT problems.
Ditched the idea of phone dispatchers and instead gave their
couriers GPS enabled handhelds.
Ecourier started to use software from a company called “seewhy”
to try to generate customer data more quickly.
SUMMARY
 Uses of this application is a) customers can track online exactly
where their courier is now.
b) eliminates package delivery guess work.
 It is an innovation but did not complete the customer happiness.
 Late deliveries and surly couriers
 Cablecom company used SPSS’s ( statistical program for social
service) statistical software to mine customer data.
 Customer dissatisfaction usually begins around the ninth month of
service and customer losses occurs between the 12th and 14th
month.
 They did a survey at the 7th month to know the customer
complaints.
 In 2002, global law firm Bryan cave, as clients of firm is 800
lawyers in 15 offices world wide.
 company implemented its first BI tool in 2004.
 This BI tool provides a dashboard which tracks hourly mix of
women & minorities working on the firms cases.
 the lawyer used the pricing and staffing modeling tools and
historical analysis tool
SWOT ANALYSIS
 S : STRENGTHS
W : WEAKNESS
O : OPPORTUNITIES
 T : THREATS
SWOT ANALYSIS
Opportunities
• Many softwares like “seewhy”
• Data interpretation
Strength
 GPS enabled handhelds
 User friendly applications
 Optimization of staffing
Threats
• Competitors
• Fake of customer identity
• Updating
Weakness
 Late deliveries
 Slurry Couriers
 Take advantage of a new customer relationship
management and billing system to improve
communication with customers, including
promotional offers.
 Reduce costs.
Challenges of cablecom
01) How do information technologies contribute to the
business success of the companies depicted in the case?
User friendly
Time saving
Digitalization
Optimization of manpower
QUESTIONS
E COURIER : SEEWHY software
 CABLECOM : SPSS’s statistical software
SPSS dimensions survey
BRYAN CAVE : BI TOOLS
pricing & staffing modeling
EXAMPLES
02) In the case of law firm Bryan cave discussed above, the
use of bi technology to improve the availability of existing
information allowed them to provide innovative services to
their customers?
Hospitals
Service industry
Real estate
Banking sector
 Cablecom built a model that could flag when a customer
was at a high risk of leaving, but this model proved only
70% accurate.
 Used SPSS’s dimensions survey research software to
create a online customer survey.
03) Cablecom developed a prediction model to better
identify those customers at risk of switching to other
company in the near future. In addi
It case study[1]

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It case study[1]

  • 2. Presentation On Ecourier,Cablecom & Bryan Cave: Delivering Value Through Business Intelligence CASE STUDY
  • 4.  SAI MANOHAR ( LEADER )  ANIRUDH  AKSHAY  VIKNESH  VYSHNAV  TIBI GROUP MEMBERS
  • 5. Ecouriers carry's 2000 packages around London each day. The operational business intelligence allows the company to keep real time tabs on customer satisfaction. Ecourier as a mission to sought out IT problems. Ditched the idea of phone dispatchers and instead gave their couriers GPS enabled handhelds. Ecourier started to use software from a company called “seewhy” to try to generate customer data more quickly. SUMMARY
  • 6.  Uses of this application is a) customers can track online exactly where their courier is now. b) eliminates package delivery guess work.  It is an innovation but did not complete the customer happiness.  Late deliveries and surly couriers
  • 7.  Cablecom company used SPSS’s ( statistical program for social service) statistical software to mine customer data.  Customer dissatisfaction usually begins around the ninth month of service and customer losses occurs between the 12th and 14th month.  They did a survey at the 7th month to know the customer complaints.
  • 8.  In 2002, global law firm Bryan cave, as clients of firm is 800 lawyers in 15 offices world wide.  company implemented its first BI tool in 2004.  This BI tool provides a dashboard which tracks hourly mix of women & minorities working on the firms cases.  the lawyer used the pricing and staffing modeling tools and historical analysis tool
  • 9. SWOT ANALYSIS  S : STRENGTHS W : WEAKNESS O : OPPORTUNITIES  T : THREATS
  • 10. SWOT ANALYSIS Opportunities • Many softwares like “seewhy” • Data interpretation Strength  GPS enabled handhelds  User friendly applications  Optimization of staffing Threats • Competitors • Fake of customer identity • Updating Weakness  Late deliveries  Slurry Couriers
  • 11.  Take advantage of a new customer relationship management and billing system to improve communication with customers, including promotional offers.  Reduce costs. Challenges of cablecom
  • 12. 01) How do information technologies contribute to the business success of the companies depicted in the case? User friendly Time saving Digitalization Optimization of manpower QUESTIONS
  • 13. E COURIER : SEEWHY software  CABLECOM : SPSS’s statistical software SPSS dimensions survey BRYAN CAVE : BI TOOLS pricing & staffing modeling EXAMPLES
  • 14. 02) In the case of law firm Bryan cave discussed above, the use of bi technology to improve the availability of existing information allowed them to provide innovative services to their customers? Hospitals Service industry Real estate Banking sector
  • 15.  Cablecom built a model that could flag when a customer was at a high risk of leaving, but this model proved only 70% accurate.  Used SPSS’s dimensions survey research software to create a online customer survey. 03) Cablecom developed a prediction model to better identify those customers at risk of switching to other company in the near future. In addi