It’s easy to accept myths as reality. If you hear something enough – it HAS to be true right? I spent most of my lifetime believing (and saying) “Lightning never strikes the same place twice” only to realize my mistake on a tour of the Empire State building when they announced that lightning strikes that building on average 100 times a year. Boy, do I hate being wrong!
Data Quality myths are no different. People may choose to believe and say them for a lot of reasons, but Utopia’s squad of data experts is here to set the record straight! Here is our Top 5 List of Data Quality Myths… let’s count it down.
Data Myth #5 – The data belongs to THOSE guys.
It’s easy to write off the data problem to another department. Maybe you have heard things like “It’s IT’s issue to manage” or “It’s the maintenance team that can’t seem to get their asset master data in order”. If it’s always someone else’s problem, it’s no one’s solution. There are likely people across your organization who rely on the data for many different reasons – and often other departments or business units may not even be aware of them. Because of that, data stakeholders must be identified and need to collaborate to determine goals and desired outcomes from the data. The processes and business rules to create, access, manage and change data must be consistent and aligned with the organization’s business priorities. That can only happen when the right people are involved from the beginning.
Data Myth #4 – In the words of Notorious B.I.G.… More data, More problems. (paraphrasing, obviously)
Okay… so yes, large amounts of data could multiply existing underlying issues with the data – but even organizations with a fairly simple data landscape can have complex challenges from bad quality data. The pure volume of data may complicate things, but every organization has the potential to have perfect data with the right data strategy and governance processes in place. We see some of the biggest data challenges resulting from 1) Data residing in multiple systems of record with no strategy or process for updating records across them. 2) Too many manual processes for data creation and management. Excel and email are great for a lot of things – but if it’s the primary way you’re making updates or changes it leaves the door open to mistakes, version control nightmares and audit headaches. 3) Important data is living in legacy systems that require specific knowledge to access and maintain – a lot of companies have that “one guy who knows how to do it” which unfortunately puts the company in a bad spot if that individual leaves.
Data Myth #3 – Migrating to S/4HANA will fix our data.
SAP S/4HANA is a powerful business platform – but it is only as good as the data which fuels it. Data accuracy is a critical part of a successful data migration and new system implementation and planning for long-term data quality is essential to realizing the ROI of the new platform. The c-level is asking for more advanced reporting and business intelligence insights, but there are too many questions around the accuracy of what the data is telling you. As a result, all the reports that had wrong information before – still have wrong information. They are just delivered faster and in prettier packaging.
This happens time and time again because the data migration/conversion stream of the ERP project did not receive the attention that it deserved. It was left to another team, another stakeholder, another phase maybe– you know the old story. "Here is the file format we need – provide the data in this format and we’ll load it for you." But the responsibility for the quality of the data is with someone else. We hear it time and time again and that’s why we refuse to let data quality take a backseat during any implementation. We have a few resources focused on migrating to SAP S/4HANA if your company is considering that move.
Data Myth #2 – Data isn’t a top priority.
There is a finite amount of resources within any organization – time, money, people… so not everything can get done all at once. But what’s interesting is that many organizations will prioritize other initiatives that rely on quality data for their success yet make the data cleanup and long-term governance a “nice to have”. Good data cannot be viewed as a luxury to any company who wants to improve efficiency, recognize cost savings and leverage analytics to drive positive business outcomes. Data is at the foundation of what you do – whether that is data related to digital twins of your assets, master data for customers, vendors, materials, articles, or any other form. When you hear people say “Data is the new oil” that really means it must be treated like a currency and the valuable asset it is.
Data Myth #1 – We don’t have a data problem.
Everyone has some sort of data challenge. Even companies who have undergone successful, massive digital transformations have to look at what’s next – maybe it’s an M&A or large capital project. Maybe it’s the next new system implementation and all your perfect, clean data has to be migrated. Regardless of what you may say to others in your company… or to others… there is no better time to take a microscope to your data than right now.
If you’ve found this article – it’s probably not because you were searching for “what to do now that we have perfect data and everything is amazing”, right? So let’s have a conversation – we LOVE talking data.