 The Importance of Data Quality
Accurate data leads to improved decision making throughout your business. Therefore, it is important to ensure that the data collected by your business is accurate and complete in order to obtain maximum business value from your information assets.
In the real world, accurate data isn't always the norm. Inaccuracies or omissions due to human error at data entry are common causes of data quality problems.
Poor data quality impacts much more than the direct mail efficiency issue experienced by our employee (multiple credit card offers received). In fact, data quality is at the core of some of the most imposing problems in business today:
Budgeting and Planning: Bad data quality results in poor decision making and planning. Productivity decreases as management is forced to guide employees away from revenue-generating activities to verify facts and numbers.
Supply Chain Management: Again, poor data quality results in bad decisions that cause overstocks, stockouts, and delays.
Information Technology: Garbage in, garbage out. Poor data quality can kill technology initiatives and increase IT workload by making tools and applications less effective.
Since data entry is still performed largely by humans, it is safe to assume that there are errors present in much of the data stored today. These errors can arise from a number of different factors, but policy and process deficiencies are often the cause. For example: data entry clerks may ignore or add generic values to certain fields just to get through the form or process. In this case, management has not provided clear policy or instruction on these fields, or policy enforcement is "thin".
Alpine's Data Quality Assessment Program
Due to the dynamic nature of business, there will always be grey spots in our policies and processes. Thus, it will be difficult to completely prevent and eliminate data entry errors. But there is good news. You can get a handle on data quality. Alpine consulting can help you identify data quality problems and recommend solutions that will make a real impact on your business.
Below is a summary of findings from a Data Quality Assessment performed for one of our clients. After the assessment, Alpine worked with the client to build a quantified business case for data quality.
Poor Data Quality - Impact on the Business
Example |
Count |
Event Cost |
Total Cost |
Result |
Bad addresses |
14,000 |
$7 |
$98,000 |
Mail returned |
Duplicate addresses |
3,000 |
$4 |
$12,000 |
Existing customers hit twice - customer relations suffers |
Date errors |
2,000 |
$5 |
$10,000 |
Out of range date causes solicitation of invalid prospects |
SSN issues |
100 |
$10,000 |
$1,000,000 |
Invalid SSN used as fraud indicator - business writes off average of $10,000 per customer |
Name misspellings |
500 |
$10 |
$5,000 |
Poor customer relations |
Tax ID issues |
300 |
$100 |
$30,000 |
IRS penalties
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Something to think about: You spend a lot of money on Information Technology. Can you afford to let poor data quality dilute these investments? A data quality program can protect and increase the value of these technology investments, and can make your business more efficient and competitive in the marketplace.
Alpine Consulting can help identify and address your data quality challenges. We offer a no-cost Data Quality Assessment program to help you define specific data quality problems, suggest potential technology and process solutions, and build the business case for data quality initiatives. Give us a call or CLICK HERE to get started!
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