Quality data should be the top 5 priority of enterprises if they want to succeed. Many organizations struggle with poor quality data, which ultimately leads to poor decision-making. Essentially, decisions are based on the data available. This means that wrong decisions can be made with poor quality data. On the other hand, reliable, accurate and complete data supports efficiency and is the cornerstone for sound decision-making.
What are the consequences of poor quality data?
- Mistrust. Poor quality data breeds mistrust among internal and external departments. Bad data in one place means bad data everywhere. If data becomes horribly inconsistent, it will be difficult for departments to work together. Bad data could also send an invoice to the wrong place. These simple consequences can harm your business’ reputation and decrease your customer satisfaction ratings.
- Bad or delayed decisions. If you suspect unreliable or incomplete data, you might delay decisions. Later on, it becomes a confidence issue. You will constantly worry that every decision will come back to bite you. Mitigate this consequence by taking responsibility for your data. Use the right technology to alert you when something falls below or above a certain threshold.
- Wasted budget. According to a recent study, department budgets are eaten up by poor quality data. Inaccurate data also contributes to the waste of money. Did you know that on average $8.2 million is lost due to poor data quality? Most of which comes from lost productivity.
Above are some of the most serious consequences of poor quality data. You do not want to compromise the revenue forecast of your company, breed mistrust among your departments, enable bad decision and waste millions of dollars to it. So, what can you do? Ensure data quality in your business. Keep in mind that “you” are responsible for ensuring quality data in your company.