In the cloud computing age, data quality is integral to smart decision-making. With reliable data, your enterprise can derive valuable customer insights that drive productivity, profitability, and overall business growth. However, if your data is outdated, incomplete, or riddled with inaccuracies, your business may suffer. Read on as we explore common data quality issues, and their negative impact, before discussing how Doppio and Syniti can enhance your master data management strategy.
If you can’t trust your data, what good is it in business? Here are several problems caused by poor data quality:
1.) Disorganization – If you don’t maintain and categorize your data, it’s bound to have inconsistencies, which can cause confusion and waste additional time for anybody working with the data sets.
2.) Incorrect data – Your analysts could be working with inaccurate data that isn’t a true reflection of your business, market, or consumers.
3.) Unnecessary duplication – Sometimes, a data set may contain multiple item codes defined for the same product. In this case, analysts may not see the complete picture if items are separated, and will need to conduct additional reporting to consolidate items and eliminate any surplus duplicates.
4.) Poor security – A by-product of these data quality issues is that an enterprise can also struggle with security flaws. Without a holistic overview, you may find that outdated, disorganized data is harder to manage, and easier to exploit. Enterprises must seek to implement better data governance that secures their master data.
When it comes to master data management, M3 customers can run into trouble in several areas if you let the data quality problems above go unchecked:
1.) Business performance issues that reduce ROI- If you are working with outdated or invalid data, you will invariably end up with inaccurate reports that misguide your crucial business decisions. The upshot is a negative impact on productivity that will crush the return on investment (ROI) of your sales and marketing campaigns.
2.) ERP issues that spread doubt– An organization with low data quality standards will find it hard to leverage the full benefits of an ERP platform. At best, this approach is a waste of your resources, but at worst, it could make management think there’s something wrong with the software or even question how suitable ERP technology and cloud computing is for their business. Such a belief is a dangerous misconception that could cost an enterprise big in the digital age.
3.) Compliance issues that could cost you big- Another precarious aspect of data is how your enterprise navigates the latest regulatory standards. As giants like Facebook and Yahoo have discovered, falling foul of data regulations is not good news for your company’s reputation. Your master data management strategy should entail hard and fast rules for data governance, giving you accountability as you work on improving data quality. For example, you could periodically hire a third-party to conduct a data quality assessment to ensure your company is compliant with government regulations for data management, processing, and security.
4.) Data reconciliation problems during a merger- Before a merger, a parent company should have an existing data set with sound data quality, which makes it easy to apply their rules for master data management to the converted data from the company they acquire. This way, you can be confident that the business processes you have defined for the parent company will work effectively for the newly merging business.Mergers and acquisitions are much more challenging if you don’t have the data quality defined and organized for the parent company. If data quality is not of a high standard, mergers can pose serious issues.
By offering data-as-a-service, Doppio and Syniti ensure improving data quality isn’t a one-time event. Instead of taking a set-and-forget approach, we consistently support M3 customers with managed services that evolve with their data needs.
Doppio is a knowledge platform with unrivaled expertise with Infor products, bolstered by a vast network of relationships in the industry. We have tech consultants with functional expertise and industry experience on niche business processes to support customers with a diverse array of data quality issues.
Besides, you can integrate your M3 platform or data lake solution directly with the Syniti knowledge platform, paving the way for seamless data management across your enterprise.
Syniti and Doppio want to offer M3 customers the means of improving data quality, with a master data management strategy that is proactive, instead of reactive. Rather than waiting for a problem to happen and then reacting, we take things to the next level, as we don’t stop when we identify issues. We go beyond the initial problem to get to the source of data quality issues, discovering recurring instances of similar problems within your data infrastructure, and ultimately, offering remediation services to improve data quality in the long-term.
Your ERP system and data quality go hand-in-hand. The purpose of an ERP system is to facilitate better data-driven decisions, which, in turn, enable a business to scale. If your data quality is poor, this system will not support your goals. In the end, you’ll fail to maximize the full potential of your ERP system and your enterprise data.
Enterprises need to change their mindset to move away from being reactive about data quality. Instead, they need to define a robust master data strategy that allows them to tap into the power of the data-driven age.
The data quality framework that Doppio and Syniti provide is the future of master data management for M3 customers. Nobody else offers the support, expertise, and technical services that this partnership does for M3 customers.
Find out more about how we can help you conquer your data quality problems by chatting with Emily at email@example.com or by signing up for our email list to get the latest updates from the Doppio blog.