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:
1. What is the organization's current data volume and how will this volume
increase in the future?
2. 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?
3. What level of data accuracy and completeness is required to support business
goals and will these levels vary by business user?
4. Is real-time access to a complete view of data a requirement? If not, what
level of data latency is acceptable?
5. What resources and budgets, now and in the future, are available to support
an MDM initiative?
6. How much time does the organization have to deploy an MDM solution?
7. How much impact do regulatory compliance issues have on the organization?
The ability to describe event-triggered behavior directly in the
diagram separates BPMN from traditional modeling notations. An event can
start a...Learn More