Poor Data Fuels Interdepartmental Conflict and Organizational Inefficiency – Here’s What to Do
In a recent conversation with one of our customers, my team uncovered a troubling reality: Poor data quality wasn’t just impacting their bottom line but also causing friction between departments. In one hong kong rcs data instance, they explained how their marketing team could not run a campaign on time because they had to wait for the IT team to clean, dedupe data, and send over a clean contact list. Meanwhile, the IT team had other tasks to manage and so failed to prioritize marketing requests.
The result?
A junior marketing analyst had to manually clean the list, causing unnecessary delays and affecting the company’s bottom line.
In another conversation, a company’s CEO shared how he lost trust in his sales team after discovering that nearly 20,000 of the 70,000 contacts they claimed to have were duplicates, and many others were incomplete or inaccurate. They only discovered the extent of the duplicates when they used AI-powered data matching to link records.
In the many years that I’ve worked with customers, both as a business consultant and now as a member of a data company, I’ve seen how data can create conflicts.
Some common scenarios that lead to conflicts:
The data team delivers inconsistent reports to the finance department, causing errors in quarterly projections. This sparks conflict, and teams start blaming each other for missed revenue targets – until someone loses a job.