CRM project. Business impact and technology challenges

Transcription

1 CRM project Business impact and technology challenges 18/10/2012, Ms P. Koleva (Head of IT) & Mr. J. Stoyanov (Head of Change and Portfolio Management)

2 Business case Build on: Improved cross selling; Improved upselling; Improved customer satisfaction=>loyalty=>reduced churn. 2

3 To be achieved by Closed loop; Better targeted campaigns; 360 view; Tight managerial grip (micro and macro); Strong onboarding process. 3

4 CRM system s components Analyses client data via statistical tools in order to identify client needs and dependencies. Analytical CRM (Available as of ) Campaign management (Available as of ) Extracts lists of clients that are suitable for certain commercial activities, generates lists of alerts Operational CRM for individuals (Available as of ) Processes the pre-defined lists of clients and is a data source for client contacts and other client data. 4

5 Closed loop Provides data Analyzes needs Makes contact Holds meetings Understands Needs and sells Records result Operation CRM as well as all other relevant systems Via statistical principles and models In the branch, via phone, letter or SMS Based on the contact made With the help of the 360 degrees CRM view and the pre-defined analyses In order to enable the process to be analyzed 123? Analyzes results and makes adjustments as needed Constantly enriches and adapts the process in favor of better results. 5

6 Better targeted campaigns Having the analytical and data mining tools it is easier to identify the customers with potential 6

7 360 view Core and satellites system; SPR; Productivity report; TBD; BO; ARBESUIT; ocrm Other exl based tools; Calculators 7

8 Tight managerial grip (micro and macro) Monitoring; Control; Transparency; Better transfer of strategic messages. 8

9 Strong onboarding process Churn; Loyalty; Rapid customer development. 9

10 Financial KPIs Payback period < 3 years (2y4m); IRR = 219,7%; Benefit Cost Ratio = 3,46. 10

11 Key to success Not the technology; project scoping and execution; business expertise. 11

12 12 High level architecture Retail CRM data model

13 13 SAS Analytics/ Campaign Management HW

14 Technical Challenges data model Analytical Data Model Design based on common business Product Catalogue o Number of Products in CRM Product catalog o Number of tables in Analytical Data Model o Number of tables in Campaign Management DM - 70 o Number of the fields in Campaign Management DM - 9 Data cleaning and normalization o Mapping CRM data with sources (more than 10 core systems, 15 applications and more than 30 excel sheets) o Applying algorithms for data cleaning using procedures applied in DWH loading process 14

15 acrm infrastructure Specific hardware was requested by the vendor Server part was purchased and installed in scope of DB Consolidation project IBM p7 machines Storage was specified by the vendor with high throughput compared to used in the bank. A special tender was undertaken and IBM 8700 storage was purchased and installed Deadlines for acrm test environment readiness was met from IT side despite tight schedule of IT DB Consolidation project 15

16 ocrm Infrastructure approach by vendor Application server: Requested one big server by the vendor: No plan for disaster recovery Not scalable Needs special hardware purchasing Proposed by the bank IT virtual machines in cluster: Failover in case of failure Scalable if needed more performance No purchasing needed already available resources DB server: Successfully tested and accepted by vendor to be on AIX instead on Windows - $$$ saved in CapEx and OpEx 16

17 acrm UAT stress test completed Stress test of ocrm successfully completed with 800 users on the architecture and solutions, proposed by the bank and approved by the vendor 17

18 Technical Challenges other Creation of Trade subordination employee hierarchy to satisfy Operational CRM requirements. o Solution based on the data in the local HR system. Based on Trade employee hierarchy are managed reports visibility, substitutions in ocrm and security access rules. Integration SAS and local DWH based on ExaData. o Migration DWH on ExaData speeded up 3 times Analytical CRM daily process and users request through business analytical toоls 18