Consera Inc - A New Approach to Management Consulting +1-408-504-7571
Case Studies
IT Expertise in:


  • Customer Data Management
  • Vendor Data Management
  • Reference Data Management
  • Data Governance
  • Data Architecture
  • Data Migration
  • ERP / SAP Deployment/Customization
  • CRM / Siebel Deployment/Customization
  • Process Re-Engineering

Successes:


  • Improved order shipping by 600% for a Fortune 500 company
     
  • Reduced world wide customer duplication rate to under 1%
     
  • Sustained customer data by establishing governance body
     
  • Implemented CRM in APAC with zero data issues
     
  • Deployed Global customer data cleansing for 39 countries in 60 days
     
  • Deployed SAP in Europe with zero critical errors
     
  • Migrated 300 million rows of data into Siebel with zero critical data issues
Information Technology Practice

  • Back Office Assessment

Analyze current system landscape

Identify future states gap

  • Data Strategy

Analyze current data structure and quality

Analyze current data management process and policies

Identify data de-duplication requirements

Define future state data management policies and procedures

Define future state reporting requirements

  • Application Strategy

Define application requirements

Define application future state roadmap

Determine future state application landscape

Define data/system integration requirements

Define Software as a Service framework

  • Right-sourcing

Recommend based on skill assessment and capital investment

Implement future state resourcing model


 
Information Technology Service Offerings

  • Release Management - Internal/External Systems or Sales of Your Products and Systems products within the enterprise   [ + ]
  • Phase I - Assessment/Plan - Where you are, where you need to be and how you get there
  • Phase II - Execution - Consera will successfully implement the release management plan defined in Phase I. This execution includes sustainability monitoring for 90 days after the plan is initially finalized and implemented within the organization.
  • Phase III - Sustainability Audit - Should client desire, Consera team in collaboration with client management team to conduct periodic audits to ensure release management process scale with growth and adapt to business changes in a proactive and time-efficient manner.
  • Corporate Hierarchy Quality Audit   [ + ]
  • Consera team in collaboration with client management team will conduct audits to ensure the completeness and accuracy of corporate hierarchies or corporate families. This service is focused on validating the client's (internal staff or outsourced vendor) data cleansing activities. The audit is typically based on data sampling and web research.
  • Data Quality Assessment/Plan   [ + ]
  • Managing your corporate information where you are, where you need to be and how you get there for: Customers, Vendors, Product Master Data, Item Master Data, and Reference Data
  • Data Cleansing Service  [ + ]
  • Consera will implement plan defined in Data Quality Assessment/Plan for: Customers, Vendors, Product Master Data, Item Master Data, and Reference Data
  • Data Quality Sustainability Audits  [ + ]
  • For each data quality types (customer, vendor, product master, item master and reference data) the Consera team in collaboration with client management team will set up periodic Sustainability audits to ensure engagement value add is continued after project is implemented
  • System Implementation   [ + ]
  • Configuration and customization expertise in SAP, Siebel, and Netsuite
  • Targeted Training   [ + ]
  • Data Quality Training Courses: - cost effective means to managing and maintaining data quality Clients staff will understand the problems root cause, transaction cost verse total cost, how to identify potential process issues and how to approach correcting these issues.
    Courses cover:
    • Data Cleansing
    • Data De-Duping
    • Customer Data
    • Data touch points (control and cost)
    • Corporate structure/hierarchies
    • Marketing data acquisition
    • Reference data
    • Data synchronization (complexity trade-offs)

For a practical implementation please see Case Study for IT Practice Support