Good data vs. bad data: welcome to Data-City

What if Gotham City was a real place, and you lived there every day? Just imagine Data City: a metropolis under constant threat from all the worst villains. Where Data Joker thrives on chaos, misinformation and complete unpredictability, and constantly messes up your vendor master data in SAP. Where Data Two-Face's choices influenced by a coin toss lead to harm, disorder and exploding cost of bad data. And where Data Bane orchestrates data mayhem in your legacy systems, ready to unleash havoc upon data integrity and to turn qualities of good data and information completely upside down.   

Being a citizen of Data City is no easy story. In the middle of data chaos, where a multitude of truths and lies collide, and good quality data must be defended, your ability to stay sharp, alert and focused becomes your guide. Will you tell what's real from what's not? Will you stand up for clarity in the face of confusion? 

The city of Data Quality 

Everybody loves to have data of high quality, but nobody is interested in spending money, time, and energy to make it become high-quality data.

Jean-Marc Klopfenstein 
Global Master Data at Nestlé

This grim reality is all too common, with a staggering 59% of customer and supplier master data records showing critical violations.

Based on our data quality benchmarks, we also know that 21% of business partner records become outdated within a year, showcasing the rapid pace of change in the data landscape.  If you don’t have a sustainable approach to maintaining your data, how much impact of poor data quality do you co-create?

Just as in Data City, this isn't just about numbers and statistics—it's about the far-reaching consequences that poor data quality can have on your business operations. 

Data quality improvements bring tangible benefits to real-world business operations. But since a working Data Bat-Signal is only available in real Gotham City, businesses need different strategies to overcome the problems with data quality. 

Impact of poor data quality vs. good data practices 

In the rapidly evolving landscape of modern business, data has emerged as the lifeblood that runs through every system, decision, and customer interaction. The power of data is undeniable—it fuels core processes, empowers decision-makers, enhances customer experiences, and drives overall business success. However, the true potential of data can only be unlocked when it meets the high standards of accuracy, completeness, and reliability. 

In the absence of automated data creation and maintenance, the occurrence of data errors becomes more than just an inconvenience – and especially in the field of business partner data. The repercussions of bad data ripple across the entirety of business functions, and the consequences are far from trivial, as the very foundation of your business processes and relationships begins to crumble.  

O2C Headaches 

In a world where master data isn't accurate, things get messy when it comes to handling orders and getting paid. Invoices might end up going to the wrong people or have the wrong amounts, causing arguments that hurt your income and make customers unhappy. Payments might go to the wrong place or get rejected, causing delays and needing a lot of work to fix. Plus, wrong credit limits are a big problem because of all the duplicates. What's the result? Customers don't like the experience, and it makes your company look bad. 

Instead of applying pills as a pain relief, CDQ customers apply data quality as a service.  

• As a result, a leading global food producer slashed transaction costs by 14%, turbocharging the business partner onboarding process from seven days to a seamless single day.

Procurement Pitfalls 

Having the right and current master data can really help avoid problems in procurement. When supplier information is wrong, it can lead to buying from the wrong places or getting the wrong details, causing arguments and maybe even losing money. Making payments to the wrong people or with the wrong amounts means things are late and might not even go through, making more work for everyone. This doesn't just affect transactions—it hurts relationships with suppliers and might even cause trouble with taxes. Plus, wrong SLA management and messed-up spend analysis make it hard to keep track of supplier groups. 

Instead of jumping over a pitfall, CDQ customers make their ground safe and solid.  

• A global leader in the specialty chemicals industry harnessed CDQ software solutions to trim bank account validation efforts by 50% and expedite supplier onboarding. 

Sales & Marketing Misfires 

Having the right master data really matters for sales and marketing. Think about what could happen if your information is wrong and messes up your campaigns. It could lead to wrong deliveries when customers are deciding to buy, making them unhappy and hurting your brand's value. If sales predictions are off, it messes up making products and planning when to do it. If you're not reaching the right people, you're wasting chances and resources. This messes up reports too, making it hard to know if marketing and sales are working well. And the worst part is, you can't plan well for important customer groups. 

Instead of putting down data fires, CDQ customers can put trust in their data. 

• Using data quality rules and automated data entry, a top food producer creates 80% of their customer data records first time right. This has cut down creation time from 7 days to less than 24 hours, making the sales process faster. 

Finance & Controlling Riddles 

The finance and controlling part of business isn't safe from mistakes in master data. These mistakes can be really bad. If financial reports are wrong, it could lead to legal troubles. Bad decisions might happen because of wrong information. Budgeting could be messed up, making it hard to use resources well. Trust from important people is also affected by how honest the financial reports are. And when there are mistakes, they can spread to other parts of the financial system, causing even more problems. 

Instead of solving the riddles, CDQ customers see the clear picture of their business ecosystem. 

• A top chemical company automated hierarchies’ linkages, resulting in a remarkable 25 times increase in linked accounts. 

Risk & Compliance Red Flags 

Lastly, wrong master data is a big problem for handling risks and following the rules. If you can't know the risks of your business partners well, you might break the rules and get into trouble with the law. There's also a worry about dealing with people who are not allowed to do business, especially if you can't tell they're connected. If you can't handle risks well, it could cost you money and chances to make good partnerships. 

Instead of spotting red flags, CDQ customers spot opportunities for sustainable compliance. 

• A leading manufacturer of vertical windows and doors used CDQ's tools to check 700,000 business partners against 1,700 sanction and watchlists. And they completed it all in just 20 hours. 

You can only unlock the true potential of data when it meets the high standards of accuracy, completeness, and reliability. This is where the concept of data quality comes into play, and it isn't just a theoretical concept—it's a tangible reality that affects business outcomes on a daily basis. From the unprecedented growth in data volume to the constant dynamics of business partner data landscape, the challenges will not disappear all at once.  

But, with challenges come opportunities, and if you think about Data-City again, CDQ can help you recognize some real Data-Batman superpowers. 

Watch how Nestlé successfully applied quality to their business partner data here.