CUSTOMER MDM

Jewel Tan

Considering the alternatives

Data quality and consistency should not be neglected, market research suggests that poor quality, data redundancy, and data inconsistency are what most businesses struggle with on a daily basis. Customer data says Pretectum, is amongst the most common of the data that represent challenges to marketing, sales, service, support and billing, and collections functions. There has never been a better time to implement a more disciplined approach to customer data management than today!

Customer Master data management (“CMDM”) itself is the convergence of people process and technology to maintain a disciplined approach to the definition, creation, maintenance, and distribution of customer data. Customers can be consumers or businesses and when you consider consumer customers these encompass those that visit a brick and mortar stores and locations as well as those that your business engages with via eCommerce or via phone, mail, or home visits.

The discipline of master data management as a whole is an element of data governance which in turn is an element of business information management.

Although MDM has historically been the exclusive domain of specialized data groups and IT.

The Pretectum C-MDM platform view is that master data management and Customer MDM in particular, as an area of data management, cannot be realistically managed and controlled by technologists and IT.

Instead, we view it as something that should be controlled and managed by business data managers and stakeholders

Any Customer MDM seeks to ensure there is uniformity, accuracy, semantic consistency, controls, and accountability of the organizational customer master data. There should be the expectation that the data is to be used by multiple groups with different needs and expectations in relation to that data.

A typical set of traits in your customer master data management system should provide infrastructure, methods, and processes in support of the following key activities:

• Business Area partitioning
• Multi-user role and team definition
• Metadata definitions of one or more customer master object(s)
• Metadata definitions of the key attributes and what are acceptable data types and values
• Definition of a semantic data model and classifiers
• Definitions and mechanisms to support data governance procedures
• The collection of master data in a central repository via manual entry & automation
• Data maintenance processes including data quality and statistical reporting
• Provision of the master data to systems and stakeholders manually & via automation

What about machine learning and artificial intelligence?

While the use of artificial intelligence and machine learning is advantageous and can prove to be accelerators in the implementation and adoption of any MDM, these are technical approaches to ensuring the efficacy of data governance and data management where the processes policies and procedures are clearly defined.

The presence of AI and ML should not be mistakenly considered a prerequisite for MDM particularly if there is a low level of organization data governance maturity or where the business is nascent in it’s data governance program.

Pretectum C-MDM comes with AI and ML but it is not necessarily technology that is suited for every kind of scenario. The Pretectum C-MDM provides businesses with a single source of the core customer data that you define, in one or more ways, for use across the entire organization. This centrally trustable and governed data repository helps businesses to gain valuable insights and engage in better decision-making.

What do I get from implementing MDM?

As a business, implementing a master data management program in support of the customer master will bring a great many hidden and obvious business benefits, among these your business should expect:

• Reduced or eliminated poor quality data and duplicates which leads to improved speed in identifying customers and maximizing your understanding of those customers
• More effective customer prioritization and reduced friction and the likelihood of mistaken identity when interacting with customers.
• Improve confidence in customer interaction opportunities and a likely higher yield from targeted customer event-based activities.
• Improved decision-making across all divisions and improved value from existing and new data assets

To achieve the best results, in considering an MDM for the customer, it is essential to assess your overall business goals and examine your business data priorities in particular. Your customer master may not be your main priority, the main priority may lie in inventory management, your product catalog, or some other area of your business.

If you identify that you have a high degree of issues with your customer data, consider what your business is missing in terms of opportunities and determine what you consider would be success criteria for any initiative that you would implement in pursuit of improved data governance and in particular, the implementation of a Customer Master Data Management program.

From instantiation through onboarding, data maintenance, and data syndication; businesses will adopt and get desirable results from leveraging Pretectum C-MDM in improving the overall performance of the data governance program using the platform’s customer data specialism.