An
ERP implementation is a major undertaking for any organization, regardless of
company size. Whether you are upgrading your existing ERP, implementing the
company’s very first, or merging legacy systems together to achieve one common
enterprise platform, the process can be quite timely and complex.
If you speak with any industry professional who has previously been through an enterprise system implementation, chances are they will tell you that data quality was one of the most critical and underestimated success factors. Here’s why…
If you speak with any industry professional who has previously been through an enterprise system implementation, chances are they will tell you that data quality was one of the most critical and underestimated success factors. Here’s why…
The
purpose of an ERP is to provide integrated visibility across all business
units, while enabling efficient asset utilization and planning. What fuels this
ever so important piece of technology is data, more specifically high quality
data. There are many variables that define quality data such as completeness,
information accuracy, standardization, classification, and proper formatting.
In many cases, legacy data has been entered by several different employees with
varying languages and interpretations, using multiple enterprise systems, and
with little to no standard guidelines. Without complete, consistent, and
reliable data, ERP search and reporting functionality is significantly limited
and often misleading.
Implementing
a data cleansing initiative in parallel with an ERP implementation not only
makes sense from a project success and ROI standpoint, but also from a
budgetary perspective. It is often much easier to build the cost of data
cleansing into a larger ERP implementation than it is to justify a separate
project after the fact. In order to maximize ERP functionality and project
success, legacy data must be merged together, cleaned, and migrated into the
new system. “Clean” implies that the data now maintains a standard
nomenclature, possesses valid attribute-rich descriptions, and has been
properly formatted to the specified system requirements.
A
Data Cleansing solution provider will utilize a combination of internal software,
subject matter expertise, and manual procedures to effectively clean,
standardize, and enhance legacy data. Prior to project commencement, a custom
Standard Operating Procedure must be developed to define the nomenclature,
abbreviations, classifications, policies, and formatting structure that will be
applied during the cleansing process. The Standard Operating Procedure will not
only be used during the initial cleansing project, but will also be used in the
ongoing governance of all future data entries. During the cleansing process,
duplication and unidentifiable items will be flagged for company review. Upon
review, these items will later remain in the item master provided that adequate
information has been collected, or will be removed completely. Once the project
is complete, cleansed data is prepared into a load-ready file for seamless
migration into the new ERP system.
Undeniably,
an enterprise system is only as functionally useful as the quality of data
flowing through it. If you are planning to implement a new ERP system in the
near future, do your team and your company a favor by including data cleansing
as a priority in the project plan. In the end it will save you a lot of time,
stress, and money, in addition to the shame of a failed ERP implementation.
For
more information on data cleansing or to request a data evaluation, visit www.imaltd.com or contact info@imaltd.com.
