We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The Quality Gap: Why Being On-Time Isn’t Enough
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > The Quality Gap: Why Being On-Time Isn’t Enough
Uncategorized

The Quality Gap: Why Being On-Time Isn’t Enough

JillDyche
JillDyche
6 Min Read
The Quality Gap: Why Being On-Time Isn’t Enough
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

In which Jill advocates behavior changes, starting at the top. But not for you. No, you’re fine. Just for other people.

BiggestLoserLogo

The biggest problem in business today is that everything is date-driven and not quality-driven.

There, I’ve said it. And a few dozen of my past and current clients are now sidling up to their laptops to shoot me an e-mail asking me if this blog is about them. (The answer is Yes It Is And You Know Who You Are.) Seriously, this is a problem everywhere, yet despite the wholesale crises it precipitates it’s actually getting worse.The root cause of this problem is the old bugaboo of perception. “Progress” is usually measured by speed-of-delivery, not fitness-for-purpose or conformance to requirements or streamlined processes or any of those other quality maxims. We’ve all heard a variation of the following:

“Just [complete the work] so I can get it into my status report for this [week/month/year].”

More Read

A Company is like a Sphere
A Company is like a Sphere
Healthcare.gov Orders Up 100TB of Cloud Storage
Food Safety Bill Ricochets Around Web
The Circle of Quality
Data-Driven Business Processes Essential for Optimization

So that project manager’s boss is now satisfied that the team is getting things done instead of abusing flex time or work-from-home policies. Meantime the campaign went to a saturated segment. Product prices no longer match across divisions. Account managers are confused about territory assignments and are cannibalizing sales. And the Feds have just left a message for your CFO.

You have to name it to claim it. (I learned this from watching The Biggest Loser the other night.) So herewith, the five main reasons for this phenomenon:

1: The measurement conversation isn’t baked into project initiation. In our BI, MDM, and data governance projects we make sure that this is part of the requirements phase. But practitioners aren’t the only people who need to have this conversation. Business executives and managers should be proactive about their quality criteria during ideation or (at the latest) in the business case. This not only elucidates delivery steps, it makes scoping so much easier.

2: The “effort delusion”, that anachronistic WASP-y assumption that many people working hard will yield positive results. There’s a monkeys-on-an-island analogy here that I’ll refrain from making. But as many before me have aptly observed working hard simply isn’t enough.

3: No one closes the loop. Imagine how many companies have invested in quality programs, data quality automation, business analysis skills, TQM and SixSigma training and other improvements yet continue to fail to reconcile the project’s original objectives from its delivered outcome. Instead, projects endure scope creep or are delivered as a shadow of their original vision. Closing the loop between original vision and ultimate deliverable is a learned and practiced behavior. Instead, mediocre projects drive a flurry of fix-and-maintain activities that would have been unnecessary had they been delivered right the first time, and ultimately far more costly.

4: Failure to define realistic delivery increments. This is Project Management 101. Or is it? The problem here is that the people doing the scoping are often not those on the hook to deliver the goods. I’ve seen project managers idling in the doorways asking programmers to rattle off their tasks, then randomly assigning time-to-completion. It doesn’t work that way. Or it shouldn’t.

5: The economic climate has made people paranoid. There, I’ve said it. And a few dozen of my past and current clients…oh, nevermind. You’ve seen it yourself. People go into delivery hyperdrive and start producing at all costs. (“Just load the data into the database—we’ll worry about whether it’s usable later.”) Worse, they cover their collective asses while spinning stories of their productivity, backing into post-facto project plans and pointing fingers when people ask questions.

Maybe if we understand the root causes, we can fix the problem. (Thanks for that one too, Bob and Jillian!)  Or maybe we’ll just stay on the couch and keep chomping away, occasionally groping for the remote control so we can get something different just by pressing a button.

TAGGED:data quality
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article compares four AI visibility agencies that help brands appear accurately in AI-generated
4 Best AI Visibility Agencies for Brands Competing in AI-Driven Search in 2026
Artificial Intelligence Exclusive
Flat editorial illustration: The article describes an AI safety incident where an agent bypassed sandbox controls by exploiting D
OpenAI Pauses Advanced AI Work After Agent Bypasses Sandbox Controls
Artificial Intelligence News Security
Flat editorial illustration: The article explains that training robots for physical interaction requires three distinct data cate
Physical AI: What Data Do You Need to Train a Robot?
Artificial Intelligence Exclusive Robotics
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
Analytics Big Data Exclusive Software

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Missed It By That Much
Uncategorized

Missed It By That Much

6 Min Read
Sun Tzu and the Art of Data Quality
Uncategorized

Sun Tzu and the Art of Data Quality

6 Min Read
The Big Question In Big Data Is...What's The Question?
AnalyticsBest PracticesBig DataBusiness IntelligenceCollaborative DataData ManagementData MiningData QualityData VisualizationData WarehousingDecision ManagementPredictive AnalyticsSentiment AnalyticsSocial DataSocial Media AnalyticsSoftwareStatisticsText AnalyticsUnstructured DataWeb AnalyticsWorkforce AnalyticsWorkforce Data

The Big Question In Big Data Is…What’s The Question?

7 Min Read
Stop Justifying Data Quality Programs and Do the DQ Work Already!
Uncategorized

Stop Justifying Data Quality Programs and Do the DQ Work Already!

5 Min Read

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

Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
5 Great Tips for Using Data Analytics for Website UX
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?