Why Your Data Sucks (and What to Do About It)

Kade Brewster • Sep 19, 2023

You probably have bad data...there, we said it. But there is a solution!

Data has become a cornerstone of business success, one that cannot be ignored, delayed, or unutilized any longer. Small businesses, just like large corporations, rely on data to make informed decisions, understand customer behavior, and identify growth opportunities. However, not all data is created equally, and many small businesses find themselves struggling with poor-quality data that hinders their progress. 


So how do you know if your data sucks? We’ve outlined the risks, causes, and steps to improve below. Use it as an assessment with your team to analyze the quality of your data, and let us know what was most helpful to you at the bottom of this article. 


The Pitfalls of Bad Data


Before delving into solutions, let's understand the implications of bad data for small businesses. There are a number of pitfalls that businesses often stumble into thanks to inaccurate or incomplete data. For business owners, failing to identify and correct these issues could completely stunt their growth as an organization.


Misleading Insights

Poor-quality data leads to inaccurate analysis and misguided decision-making, potentially resulting in missed opportunities or costly mistakes. A growing business cannot operate on incorrect information, thus it’s likely that this problem holds thousands of businesses back every single day. It also leads to…


Damaged Customer Relationships

Incorrect customer information can lead to communication errors and frustration, damaging your reputation and customer trust. Customers purchase from people, not companies. This is true today more than ever before. With so much information that customers are forced to deflect every time they open their phone or email, they want to give their business to people that understand who they are. Incorrect information inherently prevents your business from excelling in this area. 


Inefficiency

Incomplete or disorganized data can hinder day-to-day operations, making it difficult to manage inventory, track orders, or forecast demand effectively. Data governance is one of the most critical elements to the growth and sustainability of a business. Proper data governance helps combat inefficiencies caused by missing or disorganized data. 


Lost Revenue

All of this funnels to your P/L. Inaccurate pricing or billing information can lead to revenue leakage, impacting your bottom line. What businesses fail to realize is that corner cutting or lethargy in data management can have real consequences. 


Why Your Data Might Suck


We’re all on the same page about the issues stemming from bad data, but you want to know where these errors are occurring. Here are some of the most common causes of incorrect or incomplete data.


Lack of Data Governance

Without proper data governance policies, multiple sources of data can result in conflicting information and confusion. A lack of clear ownership and accountability can lead to data discrepancies. We broke down why data governance is so important in this short video. 


Data Entry Errors

Manual data entry is prone to mistakes, typos, and inconsistencies, especially when dealing with a high volume of information. Simple human errors can lead to significant consequences, affecting the quality of your data. The implementation of standard operating procedures can help with eliminating these errors (more on this in a minute). 


Siloed Data

When different departments or systems don't communicate effectively, data becomes fragmented and inaccessible, hindering comprehensive analysis. Siloed data prevents a holistic view of your business.


Insufficient Validation

Neglecting data validation processes allows inaccurate or incomplete data to enter your system undetected. Without proper checks, errors propagate throughout your databases.


Outdated Systems

Legacy software or outdated technology can limit your data management capabilities and hinder data integration. Incompatible systems can create bottlenecks and prevent seamless data flow.


Steps to Improve Your Data Quality

Establish clear data definitions, standards, formats (Standard Operating Procedures), and guidelines for data entry, ensuring consistency across your organization. By having a uniform approach to data, you keep your team on the same page at all times. Consistency with your standards leads to the reduced likelihood of errors. When building a data dictionary, it’s important to include, at the very least, three critical components to each definition. 

  • The data element/metric - what the metric is physically named
  • The business definition - How does the business define and refer to the metric
  • The technical definition - The systems and fields from specific tables that are used to define the metric


Implement Data Automation and Validation

Use automation tools to streamline data collection and reduce manual data entry, minimizing human errors.You should also set up validation checks to identify and correct errors at the point of entry, minimizing the chances of inaccurate data infiltrating your systems. Automated validation tools can catch discrepancies before they cause issues.


Integrate Systems to Scale

Implement integrated software solutions that allow seamless data sharing between departments, eliminating data silos. When systems communicate effectively, your data becomes more coherent, valuable, and relevant to each operation. There's a good way and a best way to integrate your systems if scaling your business is a goal. As your business grows, the number of systems to support your business does too. Establishing a centralized data warehouse that integrates with all of your core systems is the best way to ensure you maximize your data environment and productivity as the business scales. 


Conduct Regular Audits

Regularly review your data for inaccuracies, duplicates, and inconsistencies, and clean up your databases accordingly. Scheduled data audits help maintain data quality over time. 


Provide Training

Educate your team on the importance of data quality and proper data handling procedures. By raising awareness and skills, you empower your employees to contribute to data excellence and continue pushing the business towards your goals.

Taking the Next Step 


In the competitive landscape of small business, data quality is paramount. While poor-quality data can hinder progress and erode potential, a concerted effort to improve data practices can yield transformative results. 


By addressing the root causes of bad data and implementing robust data management strategies, small businesses can harness the true potential of their information assets, fueling growth, and driving success in an increasingly data-driven world. Remember, the journey to better data quality begins with a single step, and our team is ready to help you act. 


Brewster Consulting Group is equipped to partner with your organization and answer all of your questions surrounding data quality. If you’re looking for a solution that can be as personal as an employee, and yet as versatile as a larger organization, our team is ready to help. 


Schedule a conversation today and let’s learn how we can drive results for your business.

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