Your EHSQ data can be an untapped well – one that can have an incredible impact to your organization when it comes to driving operational excellence, compliance, corporate sustainability, and worker safety. But before the impact of your EHSQ data can be felt, it needs to be accurate. This guide outlines five practical steps to take to improve the quality and completeness of your EHSQ data.
This guide covers:
- Making your data complete
- Conformity and consistency in data
- Removing duplicates with data audits
- Timeliness matters
- Involving leadership
Over the past few years, The Economist, Forbes, Wired, Fortune and many other leading publications and thought leaders have been referring to data as the new oil. Why? There’s been a major economic shift from the wealth of resource-intensive organizations to technology companies such as Google, Facebook, and Amazon and it’s largely due to data.
According to the Economist, “Smartphones and the internet have made data abundant, ubiquitous and far more valuable… as virtually every activity creates a digital trace. Meanwhile, artificial-intelligence (AI) techniques such as machine learning extract more value from data…. by collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on.”
This impact is widespread. With the likes of industrial giants such as GE and Siemens now selling themselves as data firms, your data, especially your EHSQ data can be an untapped well – one that can have an incredible impact to your organization when it comes to driving operational excellence, compliance, corporate sustainability, and worker safety.
Before the impact of your data can really be felt, it needs to be “clean.” Clean data drives accuracy. It will improve efficiency, regulatory compliance, and decision making, while also delivering a clear path for future analytics. This guide examines some of the main principles of quality and completeness of EHSQ data and provides initiatives you can implement now to clean up your data.
