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
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The Case Against Triage
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Quality > The Case Against Triage
Data QualityDecision Management

The Case Against Triage

MIKE20
MIKE20
5 Min Read
SHARE

In an episode of the popular American TV show ER, an alcoholic patient with political connections is moved to the top of a liver transplant list. One of the staff’s doctor’s voices his outrage after catching the patient sneaking in a few drinks prior to the operation. The doctor doesn’t believe that the patient is worthy of the transplant, as he’ll just destroy another liver better served or someone else–i.e., a non-alcoholic.

Contents
  • The Usual Suspects
  • Simon Says
  • Feedback

I often think about that episode and related questions:

In an episode of the popular American TV show ER, an alcoholic patient with political connections is moved to the top of a liver transplant list. One of the staff’s doctor’s voices his outrage after catching the patient sneaking in a few drinks prior to the operation. The doctor doesn’t believe that the patient is worthy of the transplant, as he’ll just destroy another liver better served or someone else–i.e., a non-alcoholic.

More Read

The “Four Layer” Model Applied to Unstructured Content
How to Integrate Finance and Operations by Leveraging Cloud Storage
Business (NOT) as Usual: 3 Big Business Intelligence Predictions for 2015
Is There One “Right” Strategy to Implement Business Intelligence?
Big Data. New Physics.

I often think about that episode and related questions:

  • Is the hospital enabling the alcoholic’ dependency?
  • Would “tough love” send a message that the individual has to change his behavior–or face death?
  • Is there an incentive for people to cease engaging in destructive behavior if they know that they themselves will have to bear the consequences?

The same holds true for the world of data management. In Why New Systems Fail, I write about how many times consultants have to save the day for their clients–or at least try. When things break bad, organizations often call in people like me to save the day. And sometimes we do. (As a result, some of us consultants have a Superman Complex, although I like to think that I usually keep my ego in check.)

So, we show up and try to fix things. I can’t help but wonder: Are we consultants enabling our clients’ difficulties? Are we really solving their problems?

Note that I am not advocating refusing to do the work that clients are paying us consultants to do. I am simply going to make the argument that, by constantly bailing out employees and organizations with lax data management practices, consultants may in fact be enabling the very problems that organizations are hiring us to solve.

The Usual Suspects

In my experience, most data management and quality problems stem from:

  • poorly trained or lazy employees
  • poor documentation for business processes
  • inadequate internal controls
  • redundant or overly complex internal systems
  • a culture that tolerates errors
  • poor performance management
  • weak senior leadership

In other words, rarely do discrete and external events such as a software bug or rogue end user cause major problems. The seven culprits identified above do not fall into the “easily fixable” category, at least in the long term. As such, the consultant(s) that triage the situation do very little to prevent the same problem(s) from recurring.

In fact, by heeding our clients’ calls, we consultants might even be increasing the chances of recurrence. Why? Because we show that we can often work our magic and return things to normal states without the organization or its employees making any fundamental changes to their behavior, processes, or systems. While consultants aren’t cheap, depending on the engagement, a $200,000 USD cost may in fact be less expensive than changing the organization’s culture or replacing ineffectual CXO’s–much like getting a new liver is “easier” than entering Alcoholics Anonymous.

Simon Says

Look, it’s always tempting to believe that the solution is an external entity, be it a consultant, acquisition, or piece of technology. Why do you think that, particularly in the United States, sales of weight loss products are growing by so much? It’s just simpler to try and find salvation in a pill than watching what you eat and exercising a few times per week.

The burnt hand teaches best. Sometimes, organizations that experience major data management problems ought to try and solve them on their own.

Feedback

What say you? Are there merits of not fixing organizational data management problems?

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

data migration risk prevention
Best Approach to Risk Management for Data Migration in Data-Driven Businesses
Big Data Data Management Exclusive Risk Management
AI in branding
How Data Analytics and Data Mining Strengthen Brand Identity Services
Big Data Exclusive
Hidden AI, a risk?
Hidden AI, Real Risk: A Governance Roadmap For Mid-Market Organizations
Artificial Intelligence Exclusive Infographic
unusual trading activity
Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
Analytics Exclusive Infographic

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Image
AnalyticsBig DataBusiness IntelligenceData ManagementData QualityExclusiveJobs

Why the Chief Data Officer is the Hottest Job of the 21st Century

4 Min Read
Image
Big DataData MiningData Quality

Data Mine or Data Yours? Info Wars and the Escalating Arms Race

3 Min Read

Look Beyond Traditional Pharma Sales Data

4 Min Read
Image
AnalyticsCollaborative DataCommentaryData QualityExclusiveModelingPolicy and GovernanceStatisticsTransparency

When Ideology Reigns Over Data

6 Min Read

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

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?