The Dangers of Using Low-Quality Data in Your Business

All modern companies need to use data to make well-informed business decisions and improve outcomes. In the past, companies manually collected data through direct conversations with customers or by doing surveys via phone. They made all the conclusions and entries manually.

Even though this kind of approach did give some valuable insights, it’s a minimal data management strategy. Today, companies use a wide range of data management, data gathering, and data analytics tools for a seamless process.

Entry is standardized, and it’s easier to measure and quantify data. This kind of data can help find solutions to existing problems, understand the market, predict likely outcomes, etc. That includes CRM tools, CRE lending software, project management tools, etc.

However, many companies don’t correctly set up the whole data lifecycle, leading to various adverse effects. Here are some of the dangers of using low-quality data.

1. Productivity drop

Using poor data leads to productivity loss across the whole organization. That affects everyone within an organization in one way or another, leading to slower operations. Managers use data to decide how different processes will work, while employees use the data to do their jobs more effectively.

For example, partial data can easily lead to mistakes and poor decision-making. Why? Because people can’t see the whole picture and make wrong assumptions based on their data.

You must recognize and fix these mistakes because they waste a lot of resources. If you can’t fix the errors, these poor practices will also reduce productivity.

2. Bad business strategies

One of the most common uses of business data is to improve decision-making and increase the chances of success. Using inaccurate data has the opposite effect, and instead of bringing your goals closer, you will move away from them.

Business data doesn’t magically give all the answers, but it’s possible to clarify strategies with the right set of mechanisms and experienced data scientists. Data can provide companies with guidance and show them which methods have better chances of success.

Using low-quality data to make business decisions is as bad as not relying on any data. These are crucial decisions that can make or break a whole organization.

3. Increased costs

Poor data quality directly leads to increased costs. Companies can lose a lot of money when using this kind of data, and it’s crucial to find the right balance between investing in the proper data practices and investing too much.

Many companies suffer high costs each year caused due to poor data quality, with the average at around $9 million annually. Low-quality data is bad for business, and some research shows that companies lose up to 30% of their revenue because of low-quality data.

Despite companies investing more in AI (Artificial Intelligence) and other BI (Business Intelligence) tools, that is happening across industries. In reality, data volume growth increases the amount of poor-quality data, and companies are taking on more information than they can handle.

4. Missing potential business opportunities

Every time your business makes the wrong decision due to poor-quality data, you’re missing something good. For example, knowing about customer behavior, interests, and budgets can help you recognize opportunities on the market or adjust your offer correctly.

However, your business is likely to reach wrong conclusions and set up strategies with less potential with inaccurate data.

On the other hand, this kind of data is more challenging to analyze. Cleaning data and fixing mistakes also make it difficult for a business to be flexible and launch strategies on time to stay competitive in the market.

5. Reputation issues

A business with poor data makes wrong decisions that also affect its customers. Compliance issues, poor customer support, and reduced productivity due to poor-quality data directly impact your customers.

Over time, your customer satisfaction drops, and people perceive your business negatively. Poor data practices related to the business strategy can also damage reputation.

For example, suppose you wrongfully conclude that your customers are looking for a specific kind of product and market this solution to them. In that case, they might think that you don’t understand their needs and lack the knowledge to develop the products that address their pain points.

Conclusion

Data represents the best way to look at your business objectively and see where you stand. It’s a way of measuring your results and operations to optimize them and run your company smoothly. Many companies don’t have the knowledge or experience to measure the results independently but can outsource data processes at an affordable price.