Good data for your S/4 Migration – What is holding you back?

By 2027, companies using SAP ECC must move – or migrate – to SAP S/4 HANA. No project this complex and time-bound is relished by anyone, but the die has been cast, and it is time to get started on the journey.

One of the first things most companies will realize is that they have a data challenge to go along with their systems migration challenge. As I have written in the past, everyone has a data problem – and a chicken-and-egg problem, as it turns out. Which do you address first, the system or the data?

Like other platform providers, SAP encourages companies to invest in deep data cleansing before implementing new systems. It is a sensible recommendation that requires sophisticated execution. While companies are thinking about how to improve their data, the available migration timeframe is getting shorter, and the business is continuing to create new (bad) data that must be addressed. The combined challenge seems so insurmountable that some companies may put off dealing with it.

Data cleansing does not need to be a source of stress or a barrier to migration. Data can be vastly improved with the right expertise and AI-enabled support, with most of the heavy lifting done by proven systems.

In conversations, we hear three common misconceptions about data cleansing that may be holding procurement back:

Misconception #1: IT must lead the effort

The S/4 HANA migration timeline is fixed, and there is a lot of work to be done. IT seems like the natural leader for such an effort, but they are just as overwhelmed with the process as everyone else. They are also more focused on the migration and associated integrations than the data that lives in the current system.

AI-enabled solutions are totally independent from the current infrastructure (even within a best-of-breed ecosystem) and don’t require integration. Procurement can lead the data cleansing effort, improving their results going forward and making a critical and high-visibility contribution to the company in the process.

Misconception #2: The goal is perfect data

In a perfect world, we would aspire to have perfect data – but that is not where we find ourselves. As Voltaire stated in the 18th Century, “a wise Italian says that the best is the enemy of the good.” While Voltaire was spared the stress of modern technology challenges, his observation still rings true.

Creactives understands this reality, and we help you achieve ‘good’ and even ‘great’ by addressing your data outliers quickly, led by AI with human help. Focus on making the data that you have available, and then let us help you make it the best it can be.

Misconception #3: You must be a data scientist to achieve good data

Many are convinced that because AI must be trained with good data, AI can’t fix your data problems on its own, so you must be a data scientist to fix them. We can demystify it for you. Advanced AI solutions can identify data biases, ask questions to fix them, and update the AI algorithm accordingly. All you need to provide is your current business, spending, and category knowledge.

The S/4 HANA migration is a unique and critical opportunity for companies wrestling with long-standing data quality issues. High-quality data is essential for companies who want to operate competitively in today’s digital landscape.

If you consider a “make or buy” data cleansing and have more than 100k SKU, maybe scattered in different systems and with descriptions in many languages, you probably need to reconsider whether that option is a feasible choice.

We at Creactives can’t create more time, but we can help you with the work that needs to be done.

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