Are you aware that you have data anomalies within your source systems? Can you confidently say that your data is 100% accurate and that you can get the best business decisions to your organization management based on it? Think again! In our previous post, we demonstrated how human error and common mistakes in uploading data into your source system create data anomalies in it. We are all taught to think that ERP, CRM and other applications are closed “full proof” systems when it comes to data integrity, but this is just not the case. With popular business management systems being heavily based on manual data recording, data anomalies are easily created on a day to day basis.
Data anomalies occur every day, in every area and aspect we can think of.
ERP, CRM and other business applications are specifically designed to support customer business procedures. They are not meant to be data monitoring applications. Thus they will not alert the user to data anomalies and other mistakes.
The quality of your data will be as good as what users will load into the source systems. Data uploading takes place based on source systems logic, but mistakes might occur unintentionally and sometimes they are even deliberate.
Wrong data can have a direct impact on your business. According to RingLead, the cost of one dirty CRM record is $100. Anomalies can be duplicate entities such as duplicate supplier invoices, duplicate discounts, or mistaken records such as spelling mistakes and capitalization errors. Sometimes the mistake lies within a system and sometimes between source systems.
Data anomalies can have a disastrous effect on business results. Dirty data naturally includes duplicates but it can also consist of inaccurate, missing or outdated information. The following example shows plainly how deep the damage can be: “Wrong” discounts may cause selling of products at a lower price than production costs. Thus causing the company significant losses.
The data anomalies in between systems:
Misalignment between integrated applications, for example differences in a customer’s definition in the ERP and CRM, might reflect on potential leads, with the misalignment causing delays in transforming those leads into sales opportunities and then into sales orders on time. Misalignment is even more common between on premise applications and Cloud applications that are not properly synchronized.
Data that is stuck between different applications/ source systems, or within the same application between different modules can impact the business’ responsiveness, reaction speed and its adaptability to business changes. High quality source system data contributes to optimal reaction to new challenges.
Data anomalies business impact:
All these data anomalies are obviously having an enormous impact on business decisions, business results and the management’s ability to response rapidly and accurately in a competitive and volatile market. And yet many managers remain unaware that such anomalies exist in their systems.
If the cost of a bad CRM record is $100 and there are tens of thousands records out there, you have only to do the math. Ringlead further claim that an organization can generate up to 70% more revenue based on keeping its data clean. So how is it possible that decision managers have not yet jumped onto the data cleaning train?
To understand how organizations can manage data anomalies and be PRO-ACTIVE in managing curtail data exceptions. Wait for our next post… 🙂
