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Return on Investment 71

system is structured in silos, with heterogenous databases
for products and services, without unified code management;
– what is the price of not respecting a business
regulation due to financial statements with non auditable
reference and master data? This data may be locked and
dispersed in databases that are unable to restore a full and
unified data history that can be used by business users and
auditors of business regulations;
– what is the price of a poorly managed personnel
rotation due to heterogenous descriptions of posts and skills
with different data coding depending on production lines,
with no reason other than the IT silos that trap the data in
heterogenous technical structures?

Nothing prevents taking these malfunctions into financial
consideration in a new management control that would go
beyond the single accounting view. It is then necessary to
integrate the analytical keys giving way to a measure of the
quality, in financial terms. In the absence of such a
management control reform, it is often necessary to rely on a
more statistical approach, based on samples, i.e. such as
those that we have just given. This exercise will considerably
reveal hidden costs that the MDM approach can correct.

4.2. The financial gain of data reliability
Financial losses due to the reliability of information are
less studied than those of non quality, even though they are
significant. Data which is of poor quality almost immediately
penalizes anyone exposed to it. A reliability defect does not
always result in an immediate problem for the process that
uses it. This problem will resurface later, which renders
execution of any necessary corrections more complex. The
longer the delay, the more significant the risk of a large-scale
spread of the problem. It is important to weigh the difference
between reliability and data quality: