What is Data Quality Management program?
Frustrated employees are constantly having to maintain several Excel spreadsheets in order to generate reports. There is data from different systems, and different time stamps with different codes to explain different events. Someone is always pushing the responsibility of managing the data to someone else. Depending on which report is needed there is always some type of fire drill. That is why every utility and state municipalities need a data quality management program.
What is Data Quality Management?
Data quality management (DQM) refers to a business program that has the right people, processes and technologies to improve the data quality that matters most to the organization.
All of the data from different systems doesn’t actually work together. The problems cited have been that very few people are focused on the data until it is needed. That is why you need to look at all of your unstructured data and put it into an easy to use format.
But this data doesn’t tell me anything
When an organization is ready to use their data, they need a solution that can enable IT leaders to govern, support, and scale multiple integrated environments. This new environment must provide end users with autonomy, ease-of-use, and speed to work with all structured and unstructured data. The analytical solution should enable the team to see their data as it relates to finding issues before they become problems.
Historical Data as A Guide
NRECA has done a great job with benchmarking historical reliability using the SAIDI (System Average Interruption Duration Index) reliability metric. Other utilities have kept years of their reliability data to see how they are improving. PwrMetrix provides a comparative view of reliability measures to municipalities and governors. This comparative analysis allows to see from both a high and detailed level of which areas may experience the most power outages, and most importantly, which would cost the most.
Quality, Not Quantity
You are better off having less quality data points than more data that is of lesser quality. That is what we are hearing from several cooperatives who have years of data that are not correlated to anything specific. Context matters for most of the data points.
What Are The Components Of A Data Quality Management Program
The core components of a solid data program are the following:
- Overview of all systems creating, housing, generating or sending new data points
- Identification of core problems with existing data
- Remedy of current issue with data collection
- Gap analysis on any data issues
- Cleaning and standardizing core outage fields
- Documenting roles and responsibilities for data assurance
- Education of all staff on data-driven approach
- Quarterly data-program updates and TQM (Total Quality Management) on newly added data
- Grade of data-program adherence and follow-up training
This process can be conducted entirely remote via a conference call. The employees can be trained during a two-2 hour sessions. This customized approach allows employees to use the data and understand it as it relates to their specific role in the organization.
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