As a leader, your ERP system might just be your most important tool. It connects you to the heart of your corporation – giving you visibility into and control over core business processes. But to get the complete picture, additional sources are needed. Here is why a data platform might be your ERP’s best friend.
The last decade has ushered in a new era of resource planning and financial management. Better technology and better data have allowed for leaner, more efficient operations. As more of the management reporting and transaction-based timesinks are automated, knowledge workers are free to use their skills on analysis and decision-support. But few ERP systems are also decision-support systems right out of the box.
Three scenarios, three challenges
First of all, an «ERP project» usually refers to any of the following three scenarios: You either implement a new ERP system from scratch, upgrade your legacy version to a newer one, or make the switch from one system to another. Each of these scenarios carries with it unique challenges. Here are the most common:
- No complete picture of your organization’s data. To get a comprehensive view, you need to combine your ERP system with external and/or other internal data.
- Poor data quality. This increases risk and reduces the benefits of the ERP project as a whole.
- Licencing costs to maintain access to historical data.
Solving the problems
The absence of a complete picture is usually due to ERP systems’ lack of support for cross-functional analysis. A simple question arises: How can we integrate our data across various sources? This is a common challenge in all three ERP project scenarios outlined above.
Having a pure data platform, more specifically a data warehouse that allows for automation based on metadata, is the way to address it. By integrating your ERP system into a data platform, you secure the correct identification of data sources, as well as being able to seamlessly combine these data across all silos.
Ensure proper data quality
The problem of poor data quality can also rear its ugly head when either upgrading or switching ERP systems. The GIGO (garbage in, garbage out) principle still applies when you are transferring your data to a new system. This is why it is important to analyze the data so that you can discover and mitigate data quality issues as soon as possible.
Detecting this early in a project – preferably already during the initial planning phase – allows you to implement measures or set more accurate expectations going forward. A data and analytics platform such as Xpert BI might be your best tool in identifying these quality issues.
Avoid the costs of history
In the modern business world, historical data are important insofar as they can tell us something about the future. Traditional ERP systems, however, either do not store historical data to the extent that an enterprise data platform would be able to utilize, or they force you to continue paying licensing costs to access them. This is primarily a problem when switching from a legacy ERP system to a new one.
The drawbacks of this are obvious, all the while historical data can be used to make forecasts. As such, tying your ERP system into a modern data platform, and using that as the primary storage, ensures
- that you keep your data for as long as you want. This also reduces the cost of lock-in when switching ERP system
- that data is pulled from the correct sources
- better cross-functional analyses
Insight as support
The problem with many ERP systems is that while the data might be there, underneath, flowing like water streams deep under the ground – it is just not organized or accessible. ERP systems are not decision-support systems because they were never designed to be.
A metadata-driven platform, however, gives you insight into which data are available, where they come from – and what they mean. Consequently, two different reports derived from the same data sources will actually return equal values. This is not always the case when you do not have access to aggregated, sensibly stored data. But when you do, and it is made easily accessible, you have a decision-support system as powerful as the quality of your data.
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