Six Key Enablers
Enabler #1 - High Value Data Collection
It is essential that businesses understand their appli-
cation estate. We strongly believe in “High Value Data
Collection,” which focuses on defining upfront: the
context, the data to be gathered, how it will be con-
sumed and the final outcome.
Taking on a migration initiative requires a deep dive
into the enterprise’s portfolio. Gear your discovery
and analysis effort toward addressing the main busi-
ness drivers and specific goals. Based on those goals,
target an analysis exercise at the estate, application
and infrastructure levels, as well as specific to an
individual component. We recommend that every
organization perform an analysis at each of these lev-
els based on various business drivers.
The following are the typical use cases:
• Defining general strategy for transformation
across the landscape, understanding common
patterns and identifying first movers (Estate
Level Analysis)
• Addressing challenges for a specific application
portfolio for a line of business (Application Level
Analysis)
• Addressing specific pain points, such as middle-
ware or database transformation (Component
Level Analysis)
• Addressing more specific business drivers, such
as “exit a data center,” which may require an
infrastructure-centric analysis
18 | THE DOPPLER | SPRING 2018
The type of data required for each of these use cases
varies, from general application information to asset
details, detailed architecture and dependency
information.
Even though creating a data model to define exactly
what is needed for each of these analyses should be a
no-brainer, many organizations struggle with this.
Issues range from not finding required information,
to being overwhelmed with the amount of data, as
well as the time and effort needed to gather it.
We recommend that organizations spend up-front
time and effort creating a data model that defines the
use cases with the following requirements:
• Asset information
• Additional analysis attributes
• Data gathering mechanisms
The data gathering mechanism can range from
self-service questionnaires, to discovery/monitoring
tools, to CMDB sources. Many discovery tools have
additional capabilities for analysis, including cost
analysis, architecture recommendations and plat-
form recommendations.
In summary, organizations need to enable high value
data collection through the proper definition of use
cases, asset details and other functional data that is
key to the analysis. They also need a robust discovery
mechanism that can gather all the required informa-
tion, and maintain it in a repository to use in further
stages of analysis and eventual migration, if required.