The growth of the Internet, the rising number of consumers conducting business and purchasing goods online and the increase in the number of systems deployed by companies to manage customer data have all significantly increased the volume of customer data collected by businesses. Dramatic decreases in the costs to store and process data means that many businesses are retaining customer data much longer and are using it to create more complete, historical views of customers.
The Internet has also impacted consumer expectations. Consumers now expect the companies they deal with to be able to access complete, up-to-date information about their accounts and provide that information at all points of service, regardless of whether the information is one year or one minute old. New expectation levels have increased pressure on businesses to collect, integrate and understand all customer information housed within their organization.
Most enterprises today appreciate that, unless they have a firm grasp on customers and how customers fit into the overall “big picture,” they could be missing huge business opportunities to increase revenue, growth and customer satisfaction. Companies also have increasing concerns about regulatory compliance issues and new data privacy and security requirements for this growing quantity of customer data.
To create a complete, single view of each customer, many organizations know they need to accurately match customer data from multiple sources. They also know that implementing a customer-centric master data management (MDM) solution is usually the best approach to achieve these goals. What they are often confused about is that long-standing question regarding technology: to build or to buy? The answer depends on an organization’s own circumstances, goals and objectives, which need to be considered before making a decision about whether to build or buy an MDM solution.
To Build or Buy? It Depends
Before deciding on an MDM strategy, an organization must first answer the following questions about its data and how it will be used:
- What is the organization’s current data volume, and how will this volume increase in the future?
- How will data be used now and in the future? Will additional types of data be collected over time that may change matching criteria? Will outside data be leveraged to augment internal data?
- What level of data accuracy and completeness is required to support business goals, and will these levels vary by business user?
- Is real-time access to a complete view of data a requirement? If not, what level of data latency is acceptable?
- What resources and budgets, now and in the future, are available to support an MDM initiative?
- How much time does the organization have to deploy an MDM solution?
- How much impact do regulatory compliance issues have on the organization?
Once an organization has answered the questions above, it is ready to take a closer look at whether to build or buy.
A Closer Look at Build
Most companies will not actually build an MDM solution from scratch, but rather assemble different systems to create a multistep approach to MDM. These steps usually include the following:
- Extract, transform and load (ETL) tools pull, at a minimum, initial data loads out of existing repositories and put it into a common format and location.
