Data covers everything that your business needs and uses. This includes product, customer, client, investor, and confidential business information. Every piece of data you use contributes to your company’s success; hence, you must ensure the quality of your data. Bad data can muck up your system, compromise your product, and even sabotage your company’s success.
Let’s take a look at some steps you could take to avoid bad data from polluting your business and consequences of using it.
Data Cleansing To Maintain Business Integrity
Even before data is used, it already goes into different phases such as the data gathering process and data sorting. All those phases make data vulnerable to errors. Data cleansing is an important process that helps avoid data deterioration, which may then lead to problems in the long run. There are certain preventive measures you could take to avoid bad or duplicate data and maintain the integrity of it and your company.
Data profiling is checking the information from your database for accuracy and completeness. This entails understanding factors such as structure (is the data consistent and correctly structured), content (are there any errors in the data), and potential (for which projects or processes could the data be used).
Data profiling involves multiple processes:
- Collecting descriptive statistics.
- Data collection including data types, length, and recurring patterns.
- Tagging data with keywords or categories.
- Discovering metadata and assessing its accuracy and more.
- Deleting duplicate data.
Data Quality Management
fter profiling your data, you can now take more proactive steps to ensure data quality. The first step to this is, of course, determining the present quality of any data you come across with. This is the part where you would determine if data is bad and do something about it.
Simply put, good data is something that meets the set standards while bad data pertains to those that fall short. Once you determine which kind of data you have, you can decide what to do with it. If the data is not too bad, you may opt to make some alterations that could make it qualify as good data. It is important to know when to simply give up on a data; if it’s bad and correcting it would consume too many resources, just delete it.
For more effective data management, make a list of qualities that must be met for a data to be deemed of good quality. Some of the things to check for include accuracy, completeness, consistency, timeliness, uniqueness, and validity.
The Consequences of Poor Data Quality
Aside from the loss of monetary value, data with poor quality can significantly impact your overall business operation – from your business’s efficiency and productivity to your decision making and systems implementation.
Incorrect or incomplete information in your database can cause a domino effect which could, eventually, ruin your business. Here are some serious consequences if bad data is consistently overlooked or disregarded.
1. Compromised Productivity
Most business operations start with information already in their database. For example, you can’t go ahead with your marketing campaign without any information regarding your targeted leads, or you can’t reach out to your customers if you don’t have their contact information.
So, imagine how quickly the wrong information can disrupt a whole business process. Not only does bad data affect your productivity, but your efficiency as well. Instead of completing the job right the first time, you might need to go back to the beginning and waste more time figuring out what went wrong in the first place.
2. Smudged Credibility
Inaccurate data can cause errors that leave a bad impression on people who look up to your brand. Consequently, such inaccuracy could destroy trust.
Establishing your brand takes so much effort and time, but it only takes one piece of bad information to ruin that credibility. For instance, a new investor follows up on the financial report three days after your agreed deadline. Upon checking, you did send one a day before, but because there was one character missing on the email address, the message was not received. Due to the missed deadline, the investor changed his mind as you seem to be unprofessional.
3. Missed Opportunities
Inaccurate data could negatively impact your marketing strategies, causing you to miss out on critical and golden opportunities. Your target audience is the most vital part of your marketing campaigns. No matter how great your content or how enticing your pitch is, if you can’t relay the message to the right people just because their information is invalid, it won’t make any difference.
4. Insignificant Decisions
Business-related decisions are based on generated logistics and statistics. If somewhere on your graphs and excel sheets contains inaccurate data, you’ll make the wrong decisions for your business. One wrong decision could negatively impact your business for years.
5. Wasted Resources
There’s a monetary loss involved in all of the aforementioned consequences. Money is the most tangible effect of having bad data. Every campaign you start requires you to spend upfront and the return on investment solely depends on the campaign’s success. Hence, if poor data quality jeopardizes your campaign, you can bid goodbye to your invested money.
On top of the cash or cash equivalent that you could lose, bad data could also waste your time, energy, and effort.
6. Demotivated Staff
Imagine putting all your time and effort on a certain project only to find out you’re not reaping any benefits, and you need to start over because there was something wrong with the data or the details. Poor data quality can go as far as degrading the morale of your staff and pushing them to quit.
Efficient and accurate data processing is crucial in avoiding bad data. Each step that involves managing your data, acquiring your data, and evaluating your data is crucial in ensuring the integrity of your database and business. Bad data is a weak link, a rotten egg, a mistake that you must avoid because it could be compounded in a big pile of problems that may hinder your company’s success.