Master Data Management and Golden Copy Data Services –
Before creating Data Services ensure Data Quality.
SOA has larger success in the space of information reusability. Master Data Management and Golden source initiatives are party to this and play a key role in success of SOA. Before getting into Master Data Management and Golden copy data services; let’s first understand what Master Data is.
Master data is the key business entity that supports the transactions in operational systems. Customers, employees, suppliers, products are some of the examples of key Business entities that support transactions in operational systems. Master data describes these key entities.
Business processes in operational systems involves use of Master data and transactional data. While Master data describes key business entity, transactional data describes business event in operational systems. Examples of transactional data are claim, purchase order, payment; examples of master data are customer, item and supplier. Master data is commonly used across Organization-wide operational business processes irrespective of nature of transactions they deal with.
For our discussion, we will focus on customer master data, while concept can be applied generically to any other key business entities such as product, employee, supplier and so on.
Master Data Quality Issues and Business Impact
Usually operational systems end-up creating their own copies of master data as per the need of business processes in that particular application. This scenario gets further complicated with Organization’s product segmentation strategy. Taking a typical scenario in a Bank, Bank will have different product segments to serve its customer better; for example
- CASA (current account and savings account) product line for managing customer’s savings and current account needs
- Credit Card division for managing customer’s credit card requirements
- Home Loan division managing customer’s mortgage needs
Banks will have respective set of applications to manage and support these product segments. It is not unusual for the same customer to have savings account and credit card from the same bank. This results in customer information (master data) being duplicated in these multiple operational systems spread across product lines.
While product-wise segmentation is a good strategy to stay focused on specific product line, it results in same customer being represented in different ways in different product lines, this is mainly because the customer data is captured as per the need of that particular product line. In some cases, though customer profile is captured, it is partial and does not provide the comprehensive view on customer. For example, while opening fixed deposit account for customer, all socioeconomic parameters (income, educational attainment, occupation) may not be captured probably because all these details may not be relevant to that function/application. However, more socioeconomic details will be captured by home loan application to manage the risk better. This leaves customer profile duplicated as well as fragmented across product lines.
Let’s look at another example from supply chain domain. A particular electronics product manufacturing Organization may have different business units for Smartphones and Laptops. And same dealer may get duplicated and fragmented in the operational systems supporting respective line of business.
So in a nut shell, same customer can exist in multiple operational systems within product segment as well as across product segments resulting in duplicate/incorrect as well as fragmented information.
The diagram below shows the simple scenario where name of the same customer exists in a different way in different applications.
There are several issues with the master data that exists in operational systems, some of them are:
- Master data may not be correct and is not managed.
- Quality of data is not high.
- Data is captured as per the need of processes in particular operational system and does not provide comprehensive view on customer.
This is just one aspect of master data where common attributes related to customer profile (such as demographic information, socioeconomic information, geography information etc.) gets duplicated and fragmented at multiple places and not managed properly.
Another important dimension of master data is 360 degree view of customer. Since customer may have multiple relationship with Bank (savings account, credit card, home loan etc.). It is important to have holistic view on customer’s relationship with Bank. Such view of customer is primarily required by sales-marketing, customer service management systems to serve customer better, to increase Cross-Sell/Upsell opportunities, to market specific products to particular customer segment.
Let’s have a quick look on how poor quality and unmanaged master data (in operational systems) impacts Organization’s Business. These are just some indicative examples
Incorrect master data
Example: examples of incorrect and unmanaged customer data
- Errors in shipping address – Shipment being delivered to wrong address
- Customer with similar name – Credit card being sent to wrong person
- Dissatisfied customers
- Compliance issues (due to sensitive details being sent to wrong person)
Fragmented master data
Example: example of fragmented customer data
- Customer socioeconomic status information is fragmented across different operational systems not resulting in comprehensive view – Marketing and sales team not able to target products meant for specific customer segment with high income
- Missed revenue opportunities
No 360 degree view of Customer
Example: example of lack of visibility on customer’s relationship with the Bank
- Customer has multiple relationships with the Bank – savings account, personal loan and credit card. These accounts are managed by different applications. If the comprehensive 360 degree view of customer relationship is not available then it results in repeat calls being made by Bank’s sales team to customer for selling product for which he/she already has relationship with the Bank (for example repeat calls for personal loan where customer may have taken personal loan already from the Bank)
- Annoyed customer
- Missed upsell opportunities
Needless to say, quality customer information is required across all Enterprise applications and business processes spread across product lines. Poor quality of data can impact business processes, customer service channels, marketing-sales and reporting applications; ultimately impacting customer experience, revenue and compliance.
Governing and managing master data and providing single authoritative version of truth is mandate and not a choice in today’s competitive market for enhanced customer experience, increased revenue opportunities and adherence to compliance.
For most of the business domains like Banking, Telecom and Hi-Tech, Customer is the key entity around which business revolves. Same is the case with other master data entities such as product, supplier, employee; they also need to be managed effectively.
In the next article we will have a look at benefits of managing master data and role of SOA.