Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: How to Measure the Business Impact of Data Quality
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > CRM > How to Measure the Business Impact of Data Quality
Business IntelligenceCRMData MiningData VisualizationPredictive Analytics

How to Measure the Business Impact of Data Quality

michgoetz
michgoetz
6 Min Read
SHARE
So, you want to invest in data quality but you need to prove ROI before you get the resources. Intuitively you know that data quality is impacting your business. How to measure that to make a case is the test.

Many businesses focus on data elements that are easy to see and understand like company and contact information. However, as obvious as some of these elements may be, they don’t always lead to the highest bang for the buck. Data elements have priority levels within processes depending on the desired business outcome. In addition, data elements have dependencies outside of how the information comes into the system. You need to take this into account as you conduct your business analysis and map your data across your business processes.

During business analysis it pays to establish a foundation that validates recommendations and shows ROI through case studies. You can do this through data analysis and pilot programs. Data analysis can be applied through meta data segmentation within processes where you look at the existing state of the data. You can also improve portions of the data and perform the segmentation and analysis…

So, you want to invest in data quality but you need to prove ROI before you get the resources. Intuitively you know that data quality is impacting your business. How to measure that to make a case is the test.

Many businesses focus on data elements that are easy to see and understand like company and contact information. However, as obvious as some of these elements may be, they don’t always lead to the highest bang for the buck. Data elements have priority levels within processes depending on the desired business outcome. In addition, data elements have dependencies outside of how the information comes into the system. You need to take this into account as you conduct your business analysis and map your data across your business processes.

During business analysis it pays to establish a foundation that validates recommendations and shows ROI through case studies. You can do this through data analysis and pilot programs. Data analysis can be applied through meta data segmentation within processes where you look at the existing state of the data. You can also improve portions of the data and perform the segmentation and analysis.

These steps will prepare your case but will also help establish dashboards to allocate resources for future projects.

1) Identify the processes you think are most impacted by poor data quality. The processes should be tied into key business functions. For instance, in marketing you may want to look at lead qualification and management. Processes that are well defined and have a tangible link to businesses objectives work best as they are most likely mature and revenue has been tied to them.
2) Pinpoint smoking guns in the processes. There are bound to be several points in a process that are key indicators of success where data quality has negatively impacted the outcome. Your business analysis will or should show this clearly. These smoking guns should be called out clearly in the processes. What you should determine is which data elements are impacting the most and can be easily focused on or addressed.
3) Select data quality issues that you can segment the process into influence tracks. This step is critical to measurement. You need to dissect the process to create scenarios of what good vs. bad looks like in process outcomes. In the lead management process suggested earlier, it could be the point where you would qualify a lead to move into the sales pipeline.  
4) Measure performance success with good quality vs. poor quality data. At this stage you should be able to run an analysis that shows the difference in process outcomes and performance when you run scenarios between good quality data and poor quality data.  

The real benefit is that at this stage you’ve provided the dashboard to measure improvements to the business. Rather than wait until the data quality projects are completed, this provides the foundation for predicting where you will get the most impact from your investments. Instead of focusing solely on metrics that measure the completeness, accuracy, and uniqueness of records, you can focus on how these metrics within processes influence business outcomes. Now you have a case for linking data quality with ROI.

TAGGED:data qualityroi
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

data analytics and truck accident claims
How Data Analytics Reduces Truck Accidents and Speeds Up Claims
Analytics Big Data Exclusive
predictive analytics for interior designers
Interior Designers Boost Profits with Predictive Analytics
Analytics Exclusive Predictive Analytics
big data and cybercrime
Stopping Lateral Movement in a Data-Heavy, Edge-First World
Big Data Exclusive
AI and data mining
What the Rise of AI Web Scrapers Means for Data Teams
Artificial Intelligence Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Days Without A Data Quality Issue

8 Min Read

Tweety Bird and Aha! Moments

4 Min Read

DQ Alert: Easy Savings by Removing Dups

3 Min Read

Microwavable Data Quality

4 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?