Single View of Customer  
Completing and Maintaining Your Customer Grouping
Companies spend hundreds of thousands of dollars to cleanse and match their customer information against external marketing databases to drive operational efficiency, increase market insight and perform customer account management.  Even with the leading corporate database provider, match rates vary depending on initial data quality and customer geography (higher in the U.S. and G8 countries, relatively poor in other geographies). Managing the unmatched “orphan” accounts consumes a disproportionate amount of time and resource in a largely manual process. Yet without this “last mile”, many of the expected benefits of the customer database are not fully realized and return on investment (ROI) is diluted.

Benefits of Better Customer Grouping
• Improved sales targeting and cross-selling
• Better compensation planning
• Enhanced market “footprint” identification
• Raise service levels to drive higher customer satisfaction
• More reliable credit risk identification
• Balance collection and payment processes with trading partners

Reduce the Cost of Ownership
• Eliminate the need for manual coding of customer accounts
• Eliminate periodic customer database cleansing
• Minimize errors caused by out-of-date customer information
• Reduce the time required to integrate new customer information during acquisition or expansion
• Minimize “data hunts” with a fully auditable process

The MDX Process
MDX employs a rules engine to group customer records. This rules engine learns from data decisions made throughout the life of the system to maintain a tailored set of grouping rules for a client's individual business. These rules can include specific exceptions or inclusions that recognize a client's own unique processing requirements.

The MDX process (Step 1) begins with data preparation, name and address cleansing and matching. By matching internal data to external data a skeleton structure is created using positively matched records. MDX Step 2 uses the external data and the internal customer information to generate a base set of customer grouping rules to group the orphan accounts.
Step 3 involves human intervention to review and validate the results generated by the initial rule set. This function is typically performed initially by the Alliance India Offshore Data Stewarding Group, a CMM Level 5 certified team of experienced data stewards. After each data review cycle, the results are passed to the MDX Learning Engine (Step 4) to generate new rules. This process may be repeated to several times to refine the grouping rules. As the grouping rules approach an optimal state, the client's own internal staff will assume responsibility for review and final validation. Once the rules have “learned” from this manual stewarding, going forward only new data patterns are potentially flagged for review. Concurrently, new and updated data is processed by MDX from both internal and external systems. Changes in this data are automatically incorporated into the rules base thus closing the loop on a sustainable grouping process for customer information.

ERP Master Data Migration Services  
A practical approach for creating trusted, high-quality master data  Producing master data files – such as customer master, vendor master, material master, and others - is a critical, yet frequently underestimated aspect of any application migration effort. With more than 80% of all application migration-related tasks involving some type of master data component, the quality, completeness, and integrity of that data directly relates to the overall quality of the new application. Alliance Consulting’s Master Data eXchange™ (MDX) provides a comprehensive, effective approach to the creation and management of dependable enterprise master data.

Challenges in Master Data Management Despite the array of technology available to prepare master data, time and budget constraints generally prohibit organizations from developing a truly integrated master data management process.

The traditional approach to data integration is generally disjointed, inefficient, and error-prone. Multiple points of update, as well as decentralized control and audit structures, further complicate the goal of producing “trusted results” that are validated by the business community. The complexity of the traditional approach increases project risk exponentially, which is a constant challenge for any project management team.

Unfortunately, there are no shortcuts or silver bullets for effective master data. The ability to produce trusted, high-quality master data requires a comprehensive solution that leverages best-practices in data management within a fully-integrated process for the entire enterprise.

The Alliance MDX Solution
Alliance MDX Master Data Migration Services is a leased and hosted software solution that enables organizations to benefit from a fully-integrated master data management process without the upfront time and cost penalty:

Success Factors for Data Integration
Alliance MDX incorporates all of the critical elements of successful data integration, including:
• Hands-on interaction with data by business users
• Synchronization of data between systems that is critical in multi-phase projects.
• Visibility of rules and data transformations throughout the integration process
• Audit of all changes and complete lineage of each data element
• Ability to rollback data changes at a data element level
• Role-based validation and update

MDX Console
The fully auditable, role-based MDX Console is used by users across functional areas to review and interact with the business data at each phase of integration: cleansing, matching, merging, grouping and synchronization.
The involvement of business users throughout the preparation of their business information is an important attribute of any migration project. The MDX Console provides a unique and powerful interface to enable and empower business users to view, understand, and adjudicate their own master data.

• No capital investment in software or hardware
• Comprehensive, proven data integration solution
• Role based, business console
• Reduced time-to-value
• No application modifications required 

Alliance Jump Start The Alliance Jump Start program is a 4 – 12 week initiative that consists of high-level requirements definition, business case justification, technical assessment, and project planning activities.  At the conclusion of this project phase the client will have a well-defined roadmap of its master data management program including not only the technical development and migration aspects, but also a clear understanding of the accompanying business process and organizational implications as well.  

The nature of master data management inevitably affects many constituent groups throughout the organization, the Alliance Jump Start framework focuses on several key non-technical factors that are critical to the success of the project:

• Stakeholder Identification and Accountability
• Customer / Prescriber Management Workflows (current state/end state)
• Risks, Dependencies, and Constraints
• Charter and Governance
• Organizational and Process Impact

Jump Start Defined
The Alliance Jump Start is designed to establish a foundation for the implementation of an enterprise master data management solution.
The Jump Start phase can be summarized as follows:

• Explore – Explore the business issues, technical concerns, business objectives, organizational structure, and technology architecture.
• Quantify – Stakeholder identification, source system identification, technology standards, workflows, and ROI metrics.
• Plan – Guiding principles, change management, organizational alignment, executive sponsorship, technology architecture framework, and overall strategy.
• Measure – Return on investment analysis, project management, and ongoing quality controls.
• Summarize – Assessment findings and recommendations, Master Data strategy, and an action plan.

Jump Start leverages domain expertise and the experience gained by Alliance consultants and leadership through previous engagements. The result is a solid and measurable foundation on which to base a multitude of master data integration initiatives.

This engagement begins to establish the framework for the master data management solution through the definition of the overall organizational vision and the introduction of guiding principles. This is followed by a thorough assessment of the organizational readiness and technological architecture required to support the new exchange hub and its associated processes.  As part of the Jump Start process, specific criterion is established early on to aid in the measurement of impact, quality, and return-on-investment once the solution has been implemented.

The findings collected during this engagement will be summarized and packaged into an Executive Summary that is delivered with supporting documentation upon completion of the Jump Start phase. The end result is a clear plan to action that will establish a solid foundation and help drive efficiencies associated with later project phases beyond Jump Start including business discovery, data quality assessments, design, development, implementation, and beyond.