Big data technology is having a huge impact on the future of business. Nielson recently announced that it is going to start including big data in its rankings for all industries, since it is very important for their ability to serve customers and stay profitable.
While there are a lot of advantages of big data, it can be difficult to use it strategically. We have some guidelines on using big data strategically, but it is important to understand how to use it on a deeper level to make the most of it.
Managing data is standard. Businesses have data, and need to use that data in order to get great insights and generally just run their company – but what if you could do more? What if your current approach towards data management is just not good enough?
This will usually happen as you get larger. Being an enterprise, especially one with multiple locations across states or even country lines, means dealing with an extraordinary amount of data and a lack of consistency across the board.
Now, you can work with your data fragmented in different locations and systems, but you certainly aren’t getting the most out of your system.
Introducing Master Data Management
Eventually you are going to need to upgrade your standard data management approach into a master data management system. What’s the difference, you may ask?
It’s simple. With master data management, you work to pool all your data together into a single source of truth. This means one person’s customer data is consolidated into a single profile, which you can then use to offer higher levels of personalization and customization immediately.
Upgrading to this system does take a lot of time, organization, and effort, yes. If you’re experiencing any of these six classic issues, however, then know now is the time to invest in master data management.
6 Signs It’s Time to Invest in MDM
1.    Inconsistent Data
If each department has its own definitions for terms, you’re going to end up with a mess of results when you search for that word. If each department saves different levels of data, but that data is never consolidated into one file, then you now have a cookie-crumb trail of information instead of a pot of gold.
These problems only get worse the larger your business becomes. Working with incomplete or sometimes conflicting data means you make less-than-informed decisions. Even something as simple as having two addresses on file for a customer can hurt your marketing efforts or even your distribution team.
2.    Slow Operations and Analytics
If your business needs to first find all the relevant data, and then analyze it, and then use it, you are wasting time. The worst part is if your operations are outright halted because of poor quality data. Things such as duplicate records, missing information, or outright inaccurate or outdated files can cause delays, system errors, and more. Cleaning up your data so there’s only one file for each item (for example, a customer or product) will help all systems work fluidly.
Your operations team can send out products or marketing materials in a flash because your systems work, for example. Or your analytics programs generate insights in a flash because they can find all relevant data quickly, and it’s formatted to support AI and ML programs.
3.    Inaccurate Reporting
You’ll get inaccurate reports if your systems are working with inaccurate results. This is true with analytics, yes, but it’s more important when it comes to compliance. If you believe your system is compliant because of inaccurate reports, but then the official audit comes back with issues, then you face hefty fines.
4.    Ineffective Customer Service
Personalization is the way forward when it comes to enticing customers and winning their loyalty. If you have multiple files for the same customer, however, and that information contradicts itself, you’ll never be able to offer personalization that matters. Only when you have a master file for that customer (which is sorted by a unique ID, not their name) can you offer relevant personalization every time they visit your site or you send out marketing materials.
5.    Difficulty Scaling Operations
Poorly managed data hits your pain points when you try to scale up. If your system isn’t ready for a new influx of data, then that data is going to fall through the cracks, and your business will only get shakier with time.
Using MDM can help you get your house in order. This is because MDM includes creating a master data governance framework, deciding on the tools needed to make the transition happen, and also selecting the data storage solution that’s right for your business.
Only when your data is neatly organized, and there’s a framework in place to easily sort and add to your datasets can you grow without complications.
6.    Financial Losses
Poor quality data management doesn’t just hurt your operations in a vague sense. There are real costs involved, too. It’s expected that poor quality data costs businesses an average of $12.9 million. Improving your data strategy, then, can help you save big, long before it helps you boost revenue.