A Guest Post by Pedro Calcono
Every successful business organization today relies on data to make informed decisions that will result in high-value outcomes. At first, data management included manual collection by talking to customers in person or surveying them over the phone. Employees had to make entries manually, and data management work was minimal. Today, companies have sophisticated analytics and data management tools that can do these tasks seamlessly. Not only is data entry standardized, but the information gathered is measurable and can help you arrive at meaningful conclusions and make critical decisions. Data can help you solve problems, monitor performance, improve processes, solve problems, and get a better understanding of the market. However, poor data quality impacts your business negatively.
Before we go into the details of the impact poor data quality can have on businesses, let’s see some general adverse effects that businesses suffer.
Less Productivity and Growth
Low data quality hinders business growth and reduces productivity across the whole organization. Once it’s in the system, it requires a lot of effort to neutralize all the negative effects.
Expensive and Ineffective Processes
A single piece of bad data can lead to many other mistakes and issues. It can be very challenging to trace back and find out where the errors came from in the first place and get rid of the cause. The root of the problem can sabotage many other processes and cause a lot of unwanted expenses.
Poor Decision Making
With poor data in the system, business leaders, managers, and employees alike will have a tough time recognizing if a piece of information is valid or not.
Unnecessary Copies
Employees and entrepreneurs will often create both physical and digital copies through the wrong data. This means that they will spread more incorrect information throughout the organization and to customers.
Poor Customer Relationships
Using poor data means that you will be giving customers the wrong answers. You won’t be able to help them deal with their problems, and this will reflect on the relationship you are trying to establish with them.
Five Major Consequences Caused by Poor Data Quality
1. Wrong Business Strategies
The primary role of business data is to allow you to make better decisions so that your plans have a higher chance of succeeding. When working with inaccurate data, business leaders and managers will only make the wrong conclusions. Instead of using data to get closer to their goal, they will do the opposite.
Even though business data is not a crystal ball that will magically show all the answers, it can be helpful. Data can show you how much potential there is in a particular business move and what the chances of success are.
An organization misled by its data sources could make terrible decisions that could potentially lead to the company going under.
2. Increased Financial Costs
Not only will inaccurate decision making derived from bad data cause various mistakes and inconveniences, but it will also lead to an increase in costs.
Research done by Gartner shows that the average yearly costs companies suffer due to poor data quality is around $9.7 million. Additionally, Gartner has also surveyed various organizations to learn about their costs associated with the impact of poor data quality.
They have calculated annual expenses at around $14.2 million on average. Bad data equals bad business; it’s as simple as that. Ovum Research has estimated that companies lose approximately 30% of revenue on average due to low data quality.
3. Productivity Loss
Not only does poor data cost businesses money, but it slows down the whole organization. All employees are affected by it, leading to reduced productivity.
Harvard Business Review reports that poor data quality impacts productivity to a great extent because everyone uses it daily. This includes workers, managers, leaders, data scientists, customer support, and so on.
Partial data leads to poor decision making and mistakes. The more mistakes there are, the more time employees spend on correcting them. The mistakes are irreversible in many cases, and this succumbs to even further loss of productivity.
When nobody knows which data is reliable, they won’t be able to streamline their work and be productive.
4. Damaged Reputation
According to a report by Gartner, a lot of companies make assumptions about their data accuracy. This leads to various inefficiencies, reduced productivity, bad customer support, compliance issues, and so on. This directly affects customer satisfaction, which in turn reflects on the reputation of companies.
When customers are unsatisfied, they will gladly express their feelings on social media, websites, and while speaking to others in person.
This means that bad word of mouth will spread about your organization. At the same time, when customers get inaccurate information directly from their service or product providers, that organization looks unprofessional to them.
5. Missed Opportunities
Each time poor data leads to bad business decisions, a good opportunity is missed. Establishing a poor business strategy also means that the organization will miss out on a lot of potential prospects.
Knowledge about spending power, behavior, and interests of potential customers is essential to companies. If this data is inaccurate, companies will create wrong and ineffective strategies. At the same time, they won’t be able to analyze data and find out plausible opportunities.
A company that doesn’t know its customers is the one that fails, and one of the best ways to get to know your customers is through quality data.
Data Helps Measure Business Activities
At its core, data represents statistics and facts that show how your business is operating. It converts your performance into numbers which you can use to measure external and internal business activities. Hence, there is no doubt that poor data quality impacts businesses considerably.
Data represents the foundation for reporting, which is vital in modern business. A lot of companies don’t have the knowledge or the resources to gather data on their own. They have their data entry outsourced that helps to gather relevant data for business and helps to get over the negative impacts.
