Data integrity is a vital part of supply chain management. Forecasting uses data to improve your ability to estimate future sales, reduce shortages and overstock, etc. However, bad data will impact the accuracy of your forecasting. If the input is off, the output will be as well. It is estimated that data integrity costs British businesses about £1.2 billion per year.
So, where does this bad data come from? How can inventory management fix it?
Problems
Issues with data integrity have many possible roots. Here’s a few to consider:
- Volume
First of all, there is a vast amount of data available. With sheer volume in mind, it is not surprising that something is off. Is your current strategy equipped to handle the amount of data? - Sources
Where is your data coming from? If you’re acquiring a new system, you may struggle transferring data back and forth. Moreover, those who manually transfer data risk human error. If your data differs between systems, how will you know which one is right? - Collaboration
How do you ensure that you are on the same page as your suppliers and customers? If your systems aren’t updating in real-time, this will cause issues. Especially when transitioning with new supply chain parties, your data integrity is at risk.
Solutions
You can use inventory management as a tool to minimize bad data. Here’s how:
- Seamless Data Flow
Using a system to push and pull data eliminates human error. As a result, you won’t have to worry about mistakes during data transfer. This will also save you the time and cost of manual labour. - Visibility
With proper inventory management, you can increase transparency. As a result, your suppliers and customers can have real-time access to data. This can greatly increase efficiency and decrease wasted time. Also, providing a greater visibility improves trust among parties. - Real-Time Decisions
Speaking of real-time, access to current data can greatly improve your decision making. You won’t have to wait hours for a report. Instead, you can instantly access the info that you need. As a result, you can make data-driven decisions that are quick and informed.
When you have faith in your data, you can also have faith in your analytics. After all, analytics is garbage in garbage out. Forecasting is a vital part of supply chain management. When correctly used, it can offer many benefits to your firm. But if you use bad data in your forecast, your project was knocked off course to begin with.
