In any business, data plays a vital role by allowing businesses to optimize internal operations, improve targeting, and prosperously drive innovation. As different businesses look forward to embracing the latest technologies and accuracy, data quality becomes extremely vital for business growth.
Today, successful business organizations heavily depend on data to generate informed decisions that produce high-value outcomes. Data management at its earliest included manual collection mostly done through surveys.
However, companies now adopt sophisticated analytics & data management services that complete tasks seamlessly. Data entry is standardized and the information garnered is measurable, thus, assisting in drawing meaningful conclusions and making critical decisions.
Besides, data can help monitor performance, solve problems, improve processes, and provide a better understanding of our market. However, the Impact Of Poor Data Quality In Business is not to be ignored as it could create both short and long-term issues that impact your ROI.
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What’s the Cost of Possessing Poor Data Quality?
Well, research from Gartner reveals poor data quality to be quite costly for businesses by costing an average of around $9.7 million annually. On top of affecting financial resources, it negatively impacts your credibility, productivity, and efficiency as well.
Perhaps, the biggest dilemma poor data quality produces is fixing the errors. If errors are created during the initial data collection process, it can escalate easily and take a longer time to fix. Additional hours are being utilized for accommodating and validating those errors instead of utilizing the data for creating innovative business strategies.
Poor data proves to be insufficient for identifying key marketing trends, this makes it easy to botch critical opportunities for businesses. This, in turn, could result in your competitors gaining an advantage in increasing their sales.
Also, bad data and errors can easily leave lousy remarks on both clients and customers. Inaccuracy lowers your credibility while increases the risk & failure of compliance management.
Five Ramification as a Result of Poor Data Quality
Bad data quality can cost companies not only time and money but several other factors as well and potentially even ruin the company. Here are 5 consequences bad data quality will land you in.
1. Increased Financial Costs
As mentioned earlier, inaccurate decision making as derived from poor/bad data could cause several mistakes and inconveniences, which could lead to increased costs. An IBM research from 2018 estimated a massive cost of $3.1 Trillion in a year for businesses due to bad data.
Another research performed by Gartner reveals the average costs companies suffer annually because of poor data quality to be about $9.7 million. In addition to this, Gartner also surveyed different organizations to grasp their costs concerning the impact of poor data quality in the business.
The calculated annual expenses reached an average of $14.2 million. The simplest verdict is that bad data will eventually equal bad business. Ovum Research estimates companies to lose approximately 30% of their revenue on average and the culprit is poor data quality.
2. Loss of Productivity
Apart from impacting your financial resources, poor data can slow down your entire organization as well. Employees are often heavily affected by it, this leads to reduced productivity.
When talking about data, the majority of companies concern themselves with reaching customers only. Each year, about 30% of email addresses degrade because of poor email hygiene.
A review from Harvard Business claims how poor data quality influences productivity heavily as everyone makes use of it regularly. This would include managers, leaders, workers, customer support, data scientists, and more.
It’s no surprise how partial data potentially influences poor decision making & mistakes. This means more mistakes equals more employee time spent on correcting them. In most cases, these mistakes remain irreversible and further increases the loss of productivity.
Also, bad data can affect the B2B sales team, leading to lowered production, low morale, inefficiency, and frustration. When employees are left unaware of reliable data, it will become difficult for them to establish their work and remain productive.
3. Incorrect Business Strategies
For business data, their primary role is to enable better decision making for your plans to have higher success rates. However, utilizing inaccurate or poor data will lead managers and business leaders to have faulty conclusions.
Instead of driving closer to their plans and goals, bad data quality will end up doing the exact opposite. Data can uncover untapped potential for a particular business move but the dangers involved in bad data quality can be extremely harmful and even deadly to many business strategies.
While business data is no crystal ball that provides all the answers, it can certainly be positive, given the data quality is good and reliable. On another note, organizations that are misled by poor quality data sources could end up making ominous decisions that may potentially drag a company under.
4. Missed Opportunities
As the influence of poor data on business decisions increases, the chance of receiving good opportunities begin to decrease. Continuing to establish poor business strategies could also mean, organizations are bypassing several potential prospects.
Companies that fail to acknowledge their customer base won’t be fruitful and the best way for recognizing your customers and ensuring success is through the use of good quality data.
5. Damaged Reputation
A report from Gartner reveals how many companies often make assumptions regarding their data accuracy. This could lead to problems like reduced productivity, compliance issues, various inefficiencies, bad customer support, and more – directly affecting customer satisfaction, which in turn starts to reflect on company reputation.
It is reported that around 21 percent of companies admit to experiencing a damaged reputation because of bad data. Additionally, media can heavily influence the image of a company and when customers are left unsatisfied, they will not hesitate to express their opinions and feelings towards the company on websites, social media, and even in person as well.
This means negative reports about your organization could spread like wildfire. Meanwhile, bad data quality also leads to inaccurate information which customers could directly receive from the company itself, thus making the organization look unprofessional.
Data at its core represents statistics & facts that display your business operation. It converts performances into numbers that can be utilized for measuring external & internal business activities. Hence, poor data quality will no doubt impact businesses considerably.
Committing to data quality begins at the top and if leadership teams are not sold on improving the data quality, the negative impacts of bad data will keep expanding. Stakeholders and leadership teams need to commit to improved data quality by making investments, getting people involved, and continuously measuring & improving data quality.