By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data Analytics instagram stories
    Data Analytics Helps Marketers Make the Most of Instagram Stories
    15 Min Read
    analyst,women,looking,at,kpi,data,on,computer,screen
    What to Know Before Recruiting an Analyst to Handle Company Data
    6 Min Read
    AI analytics
    AI-Based Analytics Are Changing the Future of Credit Cards
    6 Min Read
    data overload showing data analytics
    How Does Next-Gen SIEM Prevent Data Overload For Security Analysts?
    8 Min Read
    hire a marketing agency with a background in data analytics
    5 Reasons to Hire a Marketing Agency that Knows Data Analytics
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: How to Measure the Business Impact of Data Quality
Share
Notification Show More
Aa
SmartData CollectiveSmartData Collective
Aa
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
Last updated: 2009/03/26 at 7:39 PM
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…

More Read

analyzing big data for its quality and value

Use this Strategic Approach to Maximize Your Data’s Value

7 Data Lineage Tool Tips For Preventing Human Error in Data Processing
Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC
Quality Control Tips for Data Collection with Drone Surveying
3 Huge Reasons that Data Integrity is Absolutely Essential

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 quality, roi
michgoetz March 26, 2009
Share This Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai low code frameworks
AI Can Help Accelerate Development with Low-Code Frameworks
Artificial Intelligence
data Analytics instagram stories
Data Analytics Helps Marketers Make the Most of Instagram Stories
Analytics
data breaches
How Hospital Security Breaches Devastate Local Communities
Policy and Governance
analyst,women,looking,at,kpi,data,on,computer,screen
What to Know Before Recruiting an Analyst to Handle Company Data
Analytics

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

analyzing big data for its quality and value
Big Data

Use this Strategic Approach to Maximize Your Data’s Value

6 Min Read
data lineage tool
Big Data

7 Data Lineage Tool Tips For Preventing Human Error in Data Processing

6 Min Read
data quality and role of analytics
Data Quality

Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC

8 Min Read
data collection with drone use
Data Collection

Quality Control Tips for Data Collection with Drone Surveying

9 Min Read

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

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?