How Investing In Data Modernization for ERP Modernization Unlocks Greater ROI

While enterprise resource planning (ERP) modernizations offer significant benefits, they also carry some major challenges and risks, as detailed in the first and second blogs of this series. They also take a lot of work. So, how can you extend the effort you put into data management for your ERP modernization to other use cases? In the third and final blog in this series, we’ll delve into that question and examine how you can improve your return on investment while reducing risk.

Devoting time and resources to data management throughout your ERP modernization can help you with streamlining and de-risking. But if you take it a step further and model other business initiatives and use cases on your previous data management work, you can reap even greater benefits. There is one catch, however — the data management capabilities you choose need to be flexible enough to support multiple use cases beyond just your ERP modernization.

In this blog, we will explore what data management assets you can reuse, how to apply them to your other business initiatives and how doing so drives benefits such as cost savings.

Investing in a data management platform to de-risk and streamline your ERP modernization will require you to create many data management assets. For example, to understand the state of your data in your legacy landscape before your modernization, you will need to develop data management assets, such as a comprehensive catalog of data in your organization and a set of rules to improve the quality of your data. The extensive catalog will help you understand what data resides where and if similar data exists in multiple places. This catalog should include data that might be named differently but is a semantic duplicate, for example a supplier, vendor, merchant or distributor.

The effort required to create this comprehensive catalog might seem daunting, but you can dramatically reduce the work needed by using AI-driven data management capabilities to auto-catalog your data. The same holds true for creating rules to improve the quality of your data. You can significantly lower the effort this takes by using AI-driven data management capabilities to auto-suggest rules for improving data quality.

During the execution of your modernization, as discussed in the second blog in this series, you will create data management assets, such as models to deduplicate your data or integrations to extract data from legacy systems and provide it to new systems. The models to deduplicate your data should be flexible enough to support varying data models and different ways of registering information. For example, a supplier and a customer might merge into one business partner when migrating to SAP S/4. Or consider a customer being called RBS in one system and Royal Bank of Scotland in another system being merged into one.

Most companies have other business initiatives outside of ERP modernization that require data management capabilities. Examples include customer experience or know-your-customer initiatives, supply chain optimization initiatives, regulatory reporting needs such as environmental, social and governance (ESG) or other industry-specific regulatory requirements. Companies now also need data management capabilities to use AI and machine learning to streamline operations and improve efficiency. In addition, companies that often go through mergers and acquisitions will see many benefits from a data management platform since it speeds up onboarding a new company.

Because all these initiatives also require data management capabilities, you can achieve cost savings and efficiency by reusing what has already been created. Here’s how:

• Comprehensive customer master data information can also be used for your customer experience initiative.
• Supplier and product master information can be applied to your supply chain optimization initiative.
• Data quality rules and deduplication models can help you consolidate data for a merger or acquisition.
• A comprehensive data catalog can assist in finding the right data and reporting on its lineage for regulatory compliance.

To achieve this, you must take a different approach to selecting a data management platform for your ERP modernization. You need to look beyond the capabilities required for ERP modernization and investigate if the platform is comprehensive and robust enough to support other business initiatives.

Leveraging an investment in data management for your ERP modernization will allow you to build a solid data management foundation that underpins several different business initiatives to save money, streamline your business and innovate.

Many data management tools have been specifically designed to support ERP modernizations. They can provide benefits with capabilities designed for modernization. However, the downside is that once your modernization is complete, the data management assets you created will be discarded since their only purpose is modernization.

With the Informatica Intelligent Data Management Cloud (IDMC), all your effort won’t go to waste as you can easily reuse your data management assets to deliver additional benefits. As IDMC is flexible and provides AI-driven data management capabilities, it offers more significant benefits and saves you money on business expenses.

To find out more, check out our ERP modernization resources:

• The Key to Successful ERP Modernization: Data Quality and Data Management
• Streamlining ERP Modernization: Leveraging Data Management to Mitigate Operational Risks
• 5 Top Pitfalls of ERP / SAP Migration and How to Mitigate Them
• The 5 Phases of ERP Modernization
• Common Pitfalls with ERP Modernization
• ERP Modernization – Reference Architecture