Introduction

Data management is a crucial aspect of any organization’s operations, and there is an ongoing debate about whether it should be led by the business or IT. In this article, we will explore the different perspectives and discuss the importance of collaboration between IT and the business in achieving effective data management.

The Role of IT in Data Management

In many organizations, IT departments are at the forefront of data governance, data quality, master data management, and other related initiatives. This is not surprising, considering that IT often takes the blame when complex, data-centric projects fail to deliver the expected results. With data quality being a significant contributor to project failures, IT specialists often recognize the importance of data management before the business does.

The Need for Business Involvement

While IT plays a crucial role in data management, it is essential to involve the business in the process. Data management should be ingrained in the corporate culture, and the enterprise should strive to maximize the productive use of information, eliminate duplication of effort, and ensure reuse. To achieve this, collaboration between IT and business members is necessary.

Leveraging Business Expertise

Data management is not solely a technical endeavour; it requires a deep understanding of the unique business circumstances that define the value of data. Business members bring valuable expertise that can help differentiate good data from bad data in context. Therefore, the best practice is to have business-led teams that incorporate IT specialists.

Driving Data Management Forward

If IT is currently leading data management in your organization, it is advisable to drive the adoption of data management principles until the business reaches a similar level of data maturity. However, it is crucial to note that this does not merely involve making technology investments. Instead, tactical projects should incorporate data management principles, such as data profiling, while working towards a reusable framework.

Measuring Impact and Planning Ahead

To evaluate the effectiveness of data management principles, it is essential to measure their impact on project delivery. Projects without a data management focus often encounter hurdles and delays during testing due to inaccurate assessment and management of data-related risks. By identifying and addressing data issues early in the project lifecycle, you can improve project outcomes.

Building an Enterprise Data Management Capability

The ultimate goal of data management is to establish an enterprise-wide data management capability. This can be achieved by defining and implementing data standards, which enable incremental benefits with each new project. While technology plays a supportive role, it should align with the enterprise’s vision and requirements.

Our Data Management framework provides a prioritised view of where IT or Business stakeholders should lead any engagement.

Communicating Success

As you make progress in data management, it is crucial to communicate your achievements to the broader community, including business stakeholders. Sharing the tactical successes will garner enterprise attention and may serve as a catalyst for launching a comprehensive enterprise data management initiative.

Conclusion

In conclusion, effective data management requires collaboration between IT and the business. While IT often takes the lead in data governance and related initiatives, the involvement of business members with their unique expertise is crucial for success. By driving data management forward, measuring its impact, and communicating successes, organizations can unlock the full potential of their data assets and improve overall business outcomes.