A recent CIO article opens with the question, “Is your organization aligned to deliver quality data for analysis by intent or by accident?” The piece acknowledges that it may strike readers as an odd question but that recognizing organizational change levers can help companies find new ways to improve their entire data supply chain.
As we’ve frequently discussed here at the APEX of Innovation, establishing the right culture is an essential component of any data-driven journey. As part of this, organizations must align the company toward the ultimate goal of improving data quality, which often requires using multiple levers to change employee behaviors and perceptions.
Read on for examples of how to improve data outcomes throughout the organization.
Data Quality & Business Outcomes: Metrics and Measures
Data itself is of little value if it’s not linked to business outcomes. The first step in achieving this is to set data quality metrics so that any resulting analyses are rooted in a strong foundation of good quality data. However, it’s just as important to set metrics around the business decisions enabled by that data—choices that are likely to result in increased revenue, reduced costs, or improved asset utilization, for example. The more that companies can align data measures to business outcomes, the greater the overall organizational understanding of data’s role in driving business value will be.
Role and Responsibility Definitions
If you want to ensure accountability for results, each role must have clearly defined responsibilities and expectations. According to the CIO piece, a good rule of thumb is to limit the responsibilities to 3-5 critical items. In addition, data responsibilities should align with existing core functions. For example, legal departments should retain ownership to ensure compliance with privacy, storage, and related standards.
Department or Individual Recognition and Rewards
Studies have consistently documented that recognition is key to driving employee performance and satisfaction. As such, praising the contributions of individual team members or entire departments can go a long way in fueling future data transformations. Rather than linking this recognition to existing performance review cycles, the CIO article encourages companies to set up a separate rewards program specifically focused on improving the data supply chain.
For details on what this might look like and other tips to align the company to deliver big data returns, take a look at the CIO piece here.