January 25, 2018 | Written by: Michelle Reinhold
New Year, New Data
As 2017 recedes into the review mirror, many organizations are looking towards the next 12 months and what initiatives, programs, and projects should take their attention and resources. For many firms, the new year will simply bring a continuation of the last; marching forward to the existing organizational goals.
For others, a new year brings opportunities to take stock of current organizational goals and redistribute resources elsewhere. Change is a constant in modern business, in the IT world specifically, and often times trends and an organization’s focus changes with the same frequency. As organizations look to 2018, there is one area which may deserve more attention that the typical organization tends to give.
Enterprise Resource Planning (ERP) systems and Business Intelligence (BI) platforms generally take a large chunk of the IT budget at many organizations. What tends to get overlooked in these efforts, however, is the quality of the data being generated and consumed. Modern ERP systems generate a large volume of transactional data in addition to the primary business data such as customer and vendor information. While the primary benefit of these databases is near instant access to every piece of information the business generates, often times little or no effort is made to ensure the accuracy of this data.
Organizational data should be treated as an asset, just as equipment, property, or petty cash. One of the first tasks in any data quality management program is to identify who in the organization is responsible for the various data sets within the organization’s IT systems. Generally, the Data Owner is responsible for defining valid data profiles, how the data can be used, and who has access to view, edit, or disseminate it within and outside the organization.
The two most critical tasks the Data Owner performs is access control and defining quality standards. Quality standards can include how data entry is performed, reviewing system processes to ensure data is calculated/generated as expected, and ensuring that data cannot be changed without proper change controls. Data profiles should be defined which describe what constitutes valid data, periodic data reviews to ensure the system contains only valid data, and how to resolve data integrity issues when they are discovered.
Access to data is just as the name implies; with the caveat that data access restrictions are not stifling to the business. Oftentimes, data access restrictions can go too far, restricting necessary data from the staff best equipped to use it to aid the organization’s decision making. Data access also involves interfacing with the organization’s IT security experts to ensure that outside access to the organization’s data is restricted, and to put controls in place to track when data is access or distributed from the organization’s IT systems.
As those in the IT industry are fond of saying: garbage in, garbage out. Every organization today is built on decisions informed by data. All too often, the ongoing quality of organizational data is overlooked, which does a great disservice to the organization’s decision makers and devalues the IT systems that generate and maintain it.