The
Key To Unlocking Your Software Potential
By John Marchisin
Is your software an information system? This
may sound like a strange question, but when you
think about it, does your software provide you
with clear, concise, decision making information?
In most cases, the answer is no. The most common
issue users voice regarding their current software,
or when seeking a replacement is that they cannot
retrieve information from what they are currently
running. They often view the lack of canned reports
as the problem. Unfortunately with this belief,
they will most likely never receive quality information
from their software. The true problem is not the
reporting, it is the lack of data integrity.
Too often software is implemented and used as
a transaction processor. Users tactically enter
data into the system with little regard for data
coding standards in an attempt to complete the
transaction as quickly as possible. While this
may be quicker on the front-end, it results in
data that has no reporting value.
Improving the integrity of your database is a
multi-faceted initiative that requires a focus
in several areas to ensure long-term sustainability.
Without addressing the root cause of why data
is inaccurate, the clean up process will improve
data quality for a point in time but it will quickly
begin to break down. For long-term sustainability,
the initiative must focus on policy, procedure,
and end user education in conjunction with the
actual clean up of the data. If your plan or service
offering is missing any of these elements, your
results will be short lived.
The process begins by defining what information
you need to access. This is imperative because
the Business Intelligence you are seeking will
have a direct impact upon database maintenance
and transaction processing procedures. Information
such as cost per procedure, total purchase volumes,
and clinical outcomes requires the procedure to
address data coding standards, what data is captured,
when is it captured, and who captures it. With
this understanding, data coding standards and
the data default hierarchy of the system to facilitate
data capture are defined.
The physical activity and process for data clean
up may include entering data directly into the
system or extracting data and updating it outside
of the system. The decision should be made based
upon the ease of update, the impact upon historical
information, and the overall effort for making
the change. Improving data management may impact
your ability to retrieve historical data but this
may be a small issue if either information currently
has little value or there are tremendous daily
operational issues. Whichever route the organization
chooses, the key is attention to detail. The clean
up effort must be performed accurately and to
the specification outlined in the definition stage.
Long-term sustainability of data integrity requires
the definition of new policies and procedures
for database maintenance and the enforcement of
such policies. If data is of value to you, begin
by restricting the number of data entry points
for your master files. While this may slow down
the front-end of the process, the time expended
is minimal compared with attempting to create
information from bad data.
Finally, provide education sessions for both
the end users and the impacted "customers."
These training sessions should include an explanation
of why the changes are being made as well as an
escalation procedure in the event that your customers
have a transaction slow down.
Your software's ability to provide quality reports
does not happen by default. It occurs through
a commitment to data integrity that is recognized
both within your department and your customer
base. By putting the proper infrastructure in
place, you can ensure your software performs as
a true information system.
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