In order to streamline and support business process transformations, organizations have been looking into consolidating and standardizing their key master data sets such as customers, vendors, and products. Business process transformation activities in this case range from global souring efforts on the supply chain end to product harmonization efforts on the marketing and sales end.

A large number of off-the-shelf packages are available in the market today that cleanse and consolidate master data sets. There are a large number of data providers as well that will validate and consolidate against their master database and send the results back to the source organization. Most of these approaches work well in terms of getting the bulk of consolidation (60%-90%) done faster. For the remaining data sets (un-consolidated) there is a gap in the market in terms of toolset that bridges the gap between cleansing and creation.

Typical Cleansing Cycle

A typical cleansing/consolidation cycle for an entity is depicted below.

Step 1 involves consolidation and cleansing of physical data sources. The consolidated master needs to be then fed into a new to-be centralized creation process or creation engine to eliminate having to cleanse on-going dataset that are being created.

Step 2 deals with process and/or toolset change for the existing master sources into a consolidated process/repository.

Step 3 involves reversing the feed into the current master data sources so that the information is available for the transactional system around it.

In the entire process, Step 3 typically is the most challenging part – dependent on the existing landscape of master sources that are being consolidated. Ignoring Step 3 results in constant cleansing and re-cleansing of data being created.

Cleansing Options and Challenges

Organizations have multiple options for cleansing

a) Use off-the-shelf cleansing tools for automatic match.

b) Use external data providers such as D&B or American Express (primarily for customers and vendors).

c) Manual cleansing and validation internally using customized, hybrid approaches.

Regardless of the approach taken, there is some percentage of manual cleansing or validation that needs to be performed to get a complete master data set created.

Due to a lack of single toolset that can handle, consolidation, cleansing, creation and distribution, most organizations end up configuring two or more packages to get the process working. Even with multiple packages, the issue of manual validation and cleansing sometimes is left out.

OneData Solution

OneData as a toolset handles all aspect of master data consolidation and new creation process including the deployment back to the current sources.

Partnerships and linkages with cleansing package vendors and data providers aids in a plug-and-play architecture that allows for cleansing algorithms to be implemented as needed by the customer. Manual cleansing and validation processes are handled using internal OneData hook command. Easy to use interface to configure and allow the end users to see the data and execute commands on-demand enables a streamlined process from cleansing to creation and then deployment.

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