Picture this…

You need to find out how many of your customers have purchased a specific product your company sells. Pretty straightforward, right? This should take you maybe 5 minutes, 10 minutes at the most.

You run a report from your inventory management system, but also decide to check that list against your CRM system to make sure it’s correct. However, you find that your CRM has more than one field that tracks on what you’re looking for and you don’t know which one to use. Cue facepalm.

After some quick advisement from the Sales Manager, you run your report in CRM using the field he told you to use. Except…there are only 5 customers in the report. Clearly, that’s not correct. “Oh, that must be the OLD field,” he says. “Use the other one instead.”

So, you use the other one – and the number of customers still doesn’t jive with the report from your inventory management.

Next, you ask the Billing Manager for a report on customers who paid for that product. They comb through the accounting system, but the product is coded in a way that makes it difficult to find.

You see where this is going? When data isn’t clean, your job becomes much more difficult. What you thought would take 5 to 10 minutes has now taken you almost an hour of your valuable time, not to mention everyone else’s time to help you locate the information you’re seeking.

How clean is your data, actually?

Without proper investment in data hygiene and management, companies will never unlock the potential of their data to accelerate their growth and increase their operational efficiency (for example, in building better products or delivering better services).

But before setting out to analyze data, they need to make sure that their data sets are clean. Smart companies are definitely aware of the importance of data hygiene.

Knowledge is power. Data touches every operation in your business and good data drives good strategic decisions and actionable insights.

Datasets usually contain large volumes of data that may be stored in formats that are not easy to use. That’s why data needs to be correctly formatted and conform to a set of rules.

Moreover, combining data from different sources can be tricky, and the resulting combination of information needs to make sense.

Data sparseness and formatting inconsistencies are the biggest challenges – and that’s what data cleansing is all about.

What is data cleaning?

Data cleaning is a task that identifies incorrect, incomplete, inaccurate, or irrelevant data, fixes the problems, and makes sure that all such issues will be fixed automatically in the future. That can be with the use of automated workflows, consolidated fields, consistent naming conventions, and adherence to organizational processes to maintain data hygiene.

Why should you care?

Here’s why data cleaning is so important: data quality is of the utmost importance to enterprises that rely on data for not just maintaining their operations, but growing business.

Knowledge is power. Data touches every operation in your business and good data drives good strategic decisions and actionable insights.

Everyone knows the song “Dem Bones”, right? Now let’s sing about the bones of your company: The CRM is connected to the ERP. The ERP is connected to the bill-ing. Billing is connected to Revenue.

To give you an example, businesses need to make sure that accurate invoices are emailed to the right customers. So, any systems that collect information for billing (project management, time tracking, etc) need to be accurate as well.

Why else is data hygiene important? Here are 4 excellent reasons:

Boost customer acquisition

Organizations that maintain their databases in shape can develop lists of prospects using accurate and updated data. As a result, they increase the efficiency of their customer acquisition and reduce its cost.

Increase productivity – Bad data is a time suck

Data hygiene clears the way to managing multichannel customer data seamlessly, allowing organizations to find opportunities for successful marketing campaigns and new ways for reaching their target audiences. The ability to map the different functions and what your data is intended to do and where it is coming from your data. Fewer errors means happier customers and fewer frustrated employees.

Avoid costly errors – Bad data is a dumpster fire

Data cleansing is the single best solution for steering clear of the costs that crop up when organizations are busy processing errors, correcting bad data, or troubleshooting.

Improve the decision-making process

Nothing helps to boost a decision-making process like clean data. Accurate and updated data supports analytics and business intelligence that in turn provide organizations with resources for better decision-making and execution.

We all know the phrase “garbage in, garbage out,” which describes the result when you try to report with bad data. You can run as many reports on bad data as you want, but you will always get a fragmented picture of what is working and what is not working. You need to know that you have the most accurate data for making the best possible decision.

Businesses that take proper care of their databases are rewarded with these and many more benefits. Organizations that keep business-critical information in tip-top shape gain a significant competitive advantage in their markets because they’re able to adjust their operations to the changing circumstances quickly. If you haven’t thought about investing in the data hygiene of your various business systems, then there’s no better time than now.