January 31, 2017
The Evolution of Master Data Management (MDM)
As technological advances continue, bringing the global community together in ever-tightening, closely-integrated circles, the focus must be turned towards the use of reliable, all-inclusive data management software. Specifically, these solutions must be able to handle the influx and heavy loads of data now available “out there” for collection, analysis, and use. In the Webinar, The Evolution of Master Data Management (September 1, 2016), Gene Leganza, VP of Research at Forrester Research, stresses the value and importance of collecting and managing data.
As the global market shifts from being business-centric to customer-centric (customers seek out specific products and services they need and desire), enterprises must look at software solutions as more data-centric than just as another application.
eCommerce Forces Paradigm Shift
The increase in e-commerce has resulted in a paradigm shift in how businesses and consumers interact. By putting their goods and services online for a wider audience to peruse, purchase and review, brick and mortar businesses have seen a shift in customer behavior. Businesses are transforming themselves in the way the operate by embracing the latest consumer interactions and technological changes
Net and Mobility
B2B and B2C changes occurred alongside the invention of two must-have products: the internet and the smartphone. Once companies began to put their products and services online for any and all to see, review, purchase and use, the need for accurate and timely data become imperative. Companies risked losing customers if their product and customer data that is fundamental to their business operations were not accurate, were limited or incomplete. This is where Master Data Management (MDM) comes into play.
Embracing the Mobile Mind Shift
Brick and mortar businesses quickly learned that, for some of them, survival meant getting their products and/or services online and usable as quickly as possible. By embracing the innovative technology, they too would remain competitive and relevant in the marketplace. However, simply listing their products or businesses online for the world to see wasn’t enough. They had to figure out how to bring those customers to their websites. Driving personalization and loyalty became easier given the foundation of the “mastered” customer and product data that was churning through the operations.
The New Focus on Data: MDM and DG
One key question that emerged during this enormous paradigm shift is:
How do customers use data in the right way(s)?
The answer to that question lies directly in the hands of the customers. Previously, businesses would determine and drive the market: they would decide what product or service the customer needs, create it, then market and sell it. With the customer now “running the show,” businesses became more reliant and dependent on what type of customer data they needed to know. In order to increase traffic and provide exceptional customer service to their loyal customer base, they began collecting massive amounts of data. The data they collected included customer reviews, surveys, demographics, interests, etc. This information would become the “customer profile” and would be monitored over time, should the needs of their customers change.
Data governance (DG) was put into place to monitor two things: consumption and creation. It was developed to evaluate how the data was being gathered and created throughout the entire system.
The Life Cycle of a Customer’s Experience
Customers go through a cycle during their purchasing process. Managing the data throughout this lifecycle is critical to success. These cycles encapsulate the customer’s buying history and experience. There are four stages to this life cycle: hypothesis, prioritization, mapping, and application.
Hypothesis: This is the stage where businesses are busy uncovering the needs of their customers. They are making an educated guess as to what their customers want from them and evaluating how and where they might fit into those needs.
Prioritization: Once they’ve identified their customers’ needs, they determine what the priorities are and match them with their objectives.
Mapping The data they have gathered allows the company to map out the best and most efficient way to deliver their product or service to the customer. This is their “moment of truth” in customer service and delivery.
Application Once the process has been completed, data analysis of the experience is conducted, which allows the business to evaluate the overall experience, from inquiry and research, up to and including purchase and product review. Any concerns or issues that had occurred during the process are identified and corrected, so as not to create a repeat of the past. Optimization occurs at this point as well.
The need for a system capable of capturing, monitoring and managing of data was identified and spanned across multiple domains. Its design was dynamic and holistic as opposed to the traditional, linear model of data capturing and streamlining. It sought to recognize and work within the customers’ ecosystems, which was an encapsulated information system of digital products and services.
Obstacles to Data Management – a spherical view
Three major obstacles in customer service and satisfaction.
- A majority of them are overwhelmed with data sources.
- Technological savvy customers are challenging solutions that are not based on the latest technologies
- Customers who are working on keeping up with technology changes are finding it hard to chose which direction to go.
In addition, customers are dissatisfied and uncomfortable with data delivery: direct access to data, integration with their existing software landscape and the updates are too slow to keep up with growing business operations and technological changes.
Master Data Management continues to evolve to support the entire purchasing lifecycle of a customer, from marketing through sales. Data management, data governance, and data analytics remain at the top of the priority list. To keep pace with changing customer choices, data management solutions/platforms continues to evolve to be dynamic, holistic and technology focussed.
Interested in viewing the webinar, The Evolution of MDM and why next generation MDM is needed? If so, you can access it here.