The new ERP system your company invested in did not boost operational processes? The new CRM that you were relying on to get in-depth customer insights did not return the expected ROI? Or you just realized that you are going through 'spreadmart hell' (a term used when multiple groups or individuals maintain spreadsheets of the same data set). Beware! This could be a case of bad data.
According to research by O'Reilly, organizations are dealing with multiple data quality issues. They either have too many different data sources, inconsistent data, or simply do not have the resources needed to clean up data quality problems. And this is just the tip of the iceberg.
Importance of Master Data
Master Data is the prized possession of any company, as it contains vital business information that is shared and used across the organization. It is data that is important for business operations and analytical decision-making. 'Master Data' can refer to data about customers, employees, vendors, suppliers, and materials. Master Data Management is vital for any business, irrespective of industry and size.
Companies often employ considerable resources to ensure the quality of master data. However, handling master data is not free from challenges. One of the biggest challenges faced by data stewards is bad data management. To-Increase's Master Data Management (MDM) solution helps you manage bad data efficiently.
Master Data Management Studio is one of the most advanced business integration solutions for Microsoft Dynamics 365 Finance and Operations. It enables better decision-making by managing master data between companies and applications. However, you need to comprehend the scope and depth of the damage poor data quality could cause your company before you identify the best way to handle it.
In this blog, let's look at how exactly bad data affects your business and the steps you can take to safeguard your data.
5 Ways How Bad Data Affects your Business
- Disrupts Business Processes
As master data is the most valuable source of information for all the departments across your organization, any discrepancies in the master data would affect multiple business processes in your company. Any error in the master data would have a snowballing effect, which would be very difficult to control once it has started.
Apart from setting off a chain of errors across departments, bad data would also consume many of your business resources. In the case of data discrepancies, you would need to allocate your business resources to do a root-cause analysis and take up corrective measures. This process would, in turn, affect your employees' productivity.
- Impacts Decision-Making
Inaccurate data produces misleading results, and companies can make poor decisions based on bad data. If key decision-makers in the company are looking at inaccurate reports and dashboards, their choices would be incorrect. Your company's management would be either misinformed or under-informed about various business processes. Eventually, this cycle of bad data would lead to weak and uninformed decisions, which would jeopardize your company's growth in the long run.
- Hinders Business Operations
The customer data that we store in our databases, CRM systems, and automation platforms is decaying at an alarming rate. Customer data typically degenerates at 2 percent per month or 25 percent annually. Any data inconsistencies like outdated, incorrect, duplicate, or missing data can affect your business operations. It can also cause delays which your business cannot afford. For instance, if you are part of a manufacturing unit, such inconsistencies may have a ripple effect. If master data is recorded incorrectly, it could affect the whole production line of your business. Even if product labels are not entered into the system correctly, it could result in the entire shipment's return.
- Results in Increased Costs
Apart from the wrong decisions derived from bad data, it also causes an increase in costs. For instance, shipping the wrong product to the wrong customer at the wrong price will incur expenses for the company. Making decisions based on incorrect data may result in lost sales. All these are examples of direct costs associated with bad data. There can be indirect costs, such as poor pricing policies, focusing on the wrong customer segments, employee dissatisfaction.
If data in your CRM is unreliable, then user adoption will decrease, resulting in indirect costs to the company as the investment in the CRM goes waste.
Because bad data requires time and resources to be spent detecting and correcting errors, it results in increased operational costs. According to research by Gartner, poor data quality costs businesses an average of $9.7 million to $14.2 million annually.
- Hampers Regulatory Compliance
Compliance is critical for any business. Many countries have data privacy laws in place, and these laws govern how information on individuals can be used.
What are the Causes for Bad Data?
Unfortunately, no organization is immune to bad data. If not corrected early on, bad data can have profound implications. Here are the major causes for bad data.
- The leading cause of bad data is human error. Errors in data entry by employees hampers data quality.
- Migrating data to new systems pose a risk for data quality.
- Users across different locations follow inconsistent data capture protocols. For example, employees in the UK may enter currency in pounds, and it would be dollars in the US.
- Data is constantly changing. For instance, it is estimated that over 40% of users change their email addresses every two years.
How Can You Manage Bad Data Efficiently?
There is no cure for human error, but you can start by setting clear data quality policies. One of the best ways to manage bad data is to invest in a comprehensive Master Data Management (MDM) solution. Give your data stewards access to intelligent tools that can handle master data efficiently.