You’ve read the industry reports and business news and adopted big data. Big data is supposed to lower operational costs, improve sales and marketing efforts, bring efficiency, and drive smarter business decisions into the future. So, what happened?
Why have your data efforts not delivered the results and improvements you were expecting?
Unfortunately, the most probable cause is poor data quality. Simply put, poor-quality data is data that is inaccurate, corrupt, duplicated, or redundant, throwing off all of your analysis.
What are the problems that poor data quality causes, and how can you bring your data up to par?
Bad Data Impacts Business Decisions
In any industry, you need to know the facts to eliminate risk and make smart, well-informed decisions, but if your data is poor every move made based off of it will be as well.
When data is accurate and has been correctly analyzed, it can aid and expedite business decisions.
For example, real-time data analytics can be used to deliver BI, determine where the good (and bad) investments are, whether or not pursuing a certain business deal makes sense, and even where the most lucrative prospects are hiding.
If your data on these issues is poor or false, any decisions you derive from analyzing it will be misguided.
Bad Data Impacts Sales & Marketing Efforts
Data is invaluable to sales and marketing.
Data from social media, your own customer service department, website, and other rich sources can help you identify new leads, determine where to place ads, decide which marketing messages and mediums are most effective, among other things.
If your marketing and sales data is poor, these decisions won't render the positive results your organization needs to and ultimately reflect on your teams that made moves based on it.
Bad Data Leads to Bad Financial Decisions
Probably the most detrimental risk of poor data is making bad financial decisions. Financial data that isn't accurate can throw off all of your reporting, forecasting, investing, and can even land you in legal trouble.
Misreporting income, payroll numbers, investments, and other financial data can lead to fines, penalties, and even jail time in the most extreme cases.
Bad Data Can Hurt Your Company's Public Image & Employee Morale
Blaming your employees for mistakes made based on poor data, not only hurts morale, it can increase turnover.
Businesses today rely so heavily on analytics and data sources that are out of their control. If your team has invested their trust in certain resources and made the best decisions they could given the information it provided, it can be seen as completely unjust and unethical to scold them for the resources mistakes.
Decisions made based on poor-quality data can also reflect badly on your corporate image as a whole. When an up and coming or normally flawless organizations falter it can lead to bad press, making people reluctant to work, invest in, or do business with you.
Overall, the repercussions of poor-quality data are boundless.
How to Fix Data Quality Issues
Despite these risks, there is a light at the end of the tunnel. You don't have to live with bad data or its consequences. Click below to get a clear picture of the quality of your data within minutes through Naveego DQS (Data Quality Services).