In addition to the above quantifiable metrics, others that are less easily quantifiable but just as important are worth considering when looking at the cost of bad data.
Erosion of trust: In the data and the data team. the most dangerous consequence of bad data, which can result in bigger issues like turnover in the data team or loss of trust in the company’s ability hong kong whatsapp number data to become data-driven and keep up with the evolving digital landscape. And once the trust is broken, it is very hard to regain it. In a previous experience, I worked around data consumers who would rather not use data and would rather rely on “experience” and “gut feeling” in a very volatile stocks-trading environment than use it knowing that it had a high chance of being inaccurate.
Loss in productivity: With bad data, teams are forced to firefight and correct errors as they arise. This constant firefighting is not only exhausting but also counterproductive. Valuable time that could be spent on strategic planning and growth initiatives is squandered on troubleshooting, diverting resources from more critical tasks.