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
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    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
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Less Dogma Equals Better Decision Making
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 Warehousing > Less Dogma Equals Better Decision Making
CommentaryData ManagementData WarehousingDecision ManagementExclusiveMobilityPolicy and Governance

Less Dogma Equals Better Decision Making

paulbarsch
paulbarsch
5 Min Read
Image
SHARE

Image

 

 

Image

More Read

Human Centered Design
How Human Centered Design and Big Data Are Merging in 2017
Increasing Importance of Governed Data Access
AI Technology Helps eCommerce Brands Optimize for Mobile
Healthcare Cloud to Grow Exponentially in US by 2020
What are Advanced Segments in Google Analytics and Why You Should Use Them

 

 

Unless you’re Donald Trump—a fellow who’s always right, even when he’s wrong—there’s not much benefit to dogmatism. That’s because some of the biggest breakthroughs come as a result of challenging assumptions; especially those that are commonly accepted. Even better, it’s important to put processes, systems and people in place to constantly provoke our pre-conceived notions and help ensure we’re ready to jump on opportunities as they arise.

Today’s facts are ripe for the picking. After all, Lord Kelvin’s famous statement; “Heavier-than-air flying machines are impossible” or Thomas Watson’s 1943 declaration; “I think there is a world market for maybe five computers” show us that what’s true today, may not be true tomorrow.

For example, when Netflix’s stock tanked in 2011 as Amazon introduced its own video service, pundits declared “Netflix has already picked all the low-hanging fruit”. In the same year, when its stock dropped 52%, Netflix was declared just about dead. Meanwhile, online video growth and smart devices connected to the internet kept marching on. Today, Netflix is worth more than CBS! And any investor who stuck with Netflix through those tumultuous years racked up an appreciation of 100% or more!

To seize new opportunities, executives need to constantly review their articles of faith—or convictions of how the world works. The challenge, however is that too many of today’s leaders “like what they like” and “know what they know”. New and valuable information is often declared anathema or quickly discarded, especially when it contradicts an already stated direction or opinion.

Moreover, our information systems aren’t helping very much. That vaunted “single source” of truth—whether enterprise data warehouse in the early 2000s or enterprise data lake today, still looks far from reality, especially as today’s data lakes are mostly used as data dumping grounds from which various LOB data marts import spurious and questionable data sets. And this, of course, leaves us with an opportunity to find data sets or evidence that matches what we already believe.

This is dangerous territory we’re charting. Our inability to challenge ingrained assumptions, coupled with poor data quality will lead to some risky and possibly disastrous decisions in the near future. Add to the mix “smartest guys in the room” executive hubris syndrome, and you have an Enron-type stew in the making.

There are solutions. First, realize that the obstinate mind is not your friend. Financial Times columnist John Kay has it right when he says; “To admit doubt, to recognize that one may sometimes be wrong, is a mark not of stupidity but of intelligence.” Realize that what is true today could be upended tomorrow, especially as technology rapidly accelerates and markets develop and advance.  A flexible approach then is warranted.

Second, keep in mind that the single source of enterprise truth is worth the journey. An enterprise data lake with consistent, governed and secured data should be a source for multiple downstream facilities. These data management efforts will help prevent the “I have my facts”, “you have yours” syndrome that’s way too prevalent in today’s business environments.

Third, for top level leaders, it’s important to build a culture where it’s OK to challenge ideas, ask questions and take risks. P&G’s new CEO David Taylor has it right where he says; “I learned that part of the role as leader is to create space for everything including disagreements, conversation, dissension and agreements, and come to really appreciate messy meetings where (we can) disagree respectfully.” When people know that their job isn’t on the line for sharing their opinion, new and better ideas have a place to develop.

Finally, even though it’s contrary to Bayesian methods, go back to well-traveled paths—or areas declared dead by the pundits—and look for undiscovered value. Areas where “everyone knows” the market has moved on. This way, while everyone else is focused on the “next big thing”, you might just find a secret goldmine that can power your profits for another three to five years.

 

TAGGED:risky business
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (60)
How Finance & BI Teams Choose Accounting Software
Big Data Business Intelligence Exclusive
Why the AI Race Is Being Decided at the Dataset Level
Why the AI Race Is Being Decided at the Dataset Level
Artificial Intelligence Big Data Exclusive
image fx (60)
Data Analytics Driving the Modern E-commerce Warehouse
Analytics Big Data Exclusive
ai for building crypto banks
Building Your Own Crypto Bank with AI
Blockchain Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Image
AnalyticsCloud ComputingCommentaryData WarehousingExclusiveRisk Management

Building Information Technology Liquidity

4 Min Read
Image
AnalyticsCommentaryExclusiveModelingPredictive AnalyticsWorkforce AnalyticsWorkforce Data

The Math Says Yes, But Human Behavior Says No

6 Min Read
Image
CommentaryExclusiveHardwareITNew ProductsRisk ManagementSoftware

The High Cost of Low Quality IT

5 Min Read
Image
Big DataCloud ComputingCommentaryExclusiveITRisk Management

Adapting to Winds of Change

3 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
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

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?