Every business has some degree of “bad data” — information that’s inconsistent, contradictory, and fragmented across application silos.
Organizations that strive to minimize bad data reap rewards that ultimately boost the bottom line. But those who shrug off “bad data” face a host of problems that can cost them millions of dollars each year.
In fact, the experts at Gartner, a leading consulting and research firm, advise in article on data quality, “Every year, poor data quality costs organizations an average $12.9 million. Apart from the immediate impact on revenue, over the long term, poor quality data increases the complexity of data ecosystems and leads to poor decision making.”
What costs and lost opportunities go in that multimillion-dollar impact? In this second post on a blog series on master data management, we break down key impact areas that organizations can face if they neglect data quality.
Download our executive brief, “Trust or Bust: Why Trusted Master Data is Vital to Your Business,” for an overview of the data challenges that businesses face. You’ll also learn how cloud-native master data management helps you make the most of your data assets to run a more data-driven and customer-centric organization.
#1. Poor Business Decisions
Executive and financial leaders depend on data for forecasting and analytics to chart a course for growth. Analyzing cash flow, profitability by customers and products, sales effectiveness, and other metrics all support crucial decisions.
Should we expand into a new state or country? Should we acquire a competitor? Why are we losing money on a given product? Why are our service margins so low? What’s the cost vs. benefit if we hire another 10 sales reps?
Modern analytics tools give organizations robust and sophisticated capabilities to answer such questions. But analytics is only as good as the data it works with. As the old saying goes, “Garbage in, garbage out.”
As it is, data may differ in your core applications such as ERP, CRM, data warehouse, and more. You end up juggling multiple versions of the truth — and making decisions based on educated guesses, not trusted data.
It’s a common concern. In a survey by Experian, a data analytics and consumer credit reporting company, 38% of respondents reported that poor data quality “damages the reliability of / trust in our analytics.”
“Data quality is directly linked to the quality of decision making,” says Melody Chien, senior director analyst, Gartner, in an article entitled “How to Improve Your Data Quality.” “Good quality data provides better leads, better understanding of customers and better customer relationships. Data quality is a competitive advantage that D&A (data and analytics) leaders need to improve upon continuously.”
Better decisions that build a better, stronger, faster company start with a focused approach on master data management.
#2. Diminished Productivity
One workaround to getting data business-ready is to have staff roll up their sleeves and reconcile it manually. Data is pulled from source applications with major discrepancies remediated in a spreadsheet or similar tool.
In another scenario, customer service agents or account managers may field inquiries from customers on a bill or a license. If that information isn’t accurate and complete in a single application, the result can be a flurry of phone calls, emails, and Slack messages to colleagues to address the waiting customer’s question.
Such brute force data chores exact a high cost. Staff hours spent on nitty-gritty data preparation can add up to a hefty monthly bill. Plus, that’s time that staff can’t devote to higher value tasks that grow the business. Job satisfaction drops, and soon enough you’ve got to fill vacant positions because staff grew tired of the endless data drudgery.
It’s no wonder that the Experian survey we mentioned earlier also found “wasted resources and additional costs” to be the top concern around poor data quality, cited by 42% of respondents.
Manual data work is not sustainable in our on-demand digital age. The limitations of error-prone manual work make automated master data management a compelling option to address data issues.
#3. Subpar Customer Experiences
Customers expect friction-free experiences over every touchpoint when engaging with your business. Many favor brands that understand their preferences, anticipate their needs, and deliver personalized experiences.
That ideal is at risk if you have siloed and inconsistent data on your customers, whether you serve B2C or B2B markets, or both. Bad customer data can manifest in many ways:
- You might disappoint a customer by shipping a product to an old address that wasn’t updated in your warehouse management system.
- Your customer service team can leave customers frustrated if they don’t have a full view of a customer’s order history.
- Customers may roll their eyes if your email marketing team keeps offering discounts on a product that customer bought at full price just a few weeks ago.
Repeated missteps can undermine customer trust and loyalty. That discontent gets amplified if and when customers share their unhappy experiences in reviews or social media. Businesses can suffer reputational damage and declines in Net Promoter Score (NPS), which in turn can deter would-be investors.
The impact of poor data quality on customer experiences is the second top concern in Experian’s survey, cited by 39% of respondents. In the same study, 85% of respondents indicated that poor quality contact data for customers negatively affects operational processes and efficiency.
True customer centricity requires a 360-degree view of your B2C and B2B customers across all channels. Achievable with master data management, a 360-degree view gives you a competitive advantage that delights your customers, builds trust, and leads to long-term brand loyalty.
Sidestepping Data Land Mines With Boomi DataHub
If bad data is allowed to proliferate, you risk other impacts as well:
- You may be leaving money on the table because cross-sell and upsell initiatives miss the mark.
- Regulatory compliance may be jeopardized because mission-critical data doesn’t align in your core systems.
- Onboarding new employees or partners can be slow and labor-intensive, slowing time to value and leaving subpar first impressions.
- An acquisition may not deliver swift value because you can’t readily reconcile new data with existing information in your systems.
Boomi DataHub provides an elegant way to sidestep such land mines. Recognized as a “Champion in Master Data Management” by Software Reviews, powered by InfoTech, Boomi DataHub:
- Consolidates data from multiple systems into a central hub
- Generates “golden records” representing a single source of truth
- Highlights exceptions for manual intervention
- Propagates high quality data back to source systems
As a cloud-native solution with low-code development, Boomi DataHub can be deployed in weeks, versus the months often needed with a legacy MDM solution. Simplicity of deployment is one reason why many of Boomi’s approximately 20,000 customers implement Boomi DataHub after they’re up and running with core Boomi integration services.
To learn more, download our executive brief, “Trust or Bust: Why Trusted Master Data is Vital to Your Business,” and visit our Boomi DataHub capability page.