Data, facts and statistics collected for reference and analysis should underpin every business decision.
If the quality of that data you are making decisions on is bad, so potentially are the outcomes of those decisions. This does not bode well for business.
Bad data quality can lead to inefficiencies in your business. Bad data quality can also lead to excessive costs, compliance risks and customer dissatisfaction.
Good data quality provides you with the facts and enables well-informed decision making. Having good quality, rock-solid data removes assumptions, emotions and politics from the process.
Good data quality is a priceless business decision-making commodity.
If you are making decisions on data you should consider and confirm the quality of the data first.
Company-X has helped many clients in New Zealand and overseas improve their data quality, and make better data-driven decisions as a result.
Data quality issues are often unknown in business until all of its data is pulled together.
Inconsistency in data quality often comes from different regions, offices and staff recording things in a different way. It’s hard to draw any reliable conclusions from your data when it is affected by inconsistencies. Drilling down into the data helps you discover where the issues are and can provide insights on how to improve.
Because you can’t manage what you don’t measure, we measure the dimensions of accuracy, completeness, consistency, timeliness, usability, relevance, and uniqueness.
Does zero really mean zero, or is there no data in the system for that value? That sort of thing.
“On one project we heard a lot of rhetoric that the client had poor data quality but we needed to quantify that,” said fellow Company-X co-founder and director Jeremy Hughes.
“Is data quality really poor and is it poor everywhere? Or is data quality just poor in a few places? The evidence was quite anecdotal so we built a set of 63 metrics which quantified the data quality across the important data and built easy to use dashboards so that people could see where they needed to put their effort and investigate further.”
When you measure data quality and share the results, everyone learns the importance of good data quality. Culture changes and the business decision-making process improves.
If you don’t measure the quality of your data, you run the risk of having a distorted view of reality, wasting both time and energy on perceived problems rather than real ones.