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
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
    data mining to find the right poly bag makers
    Using Data Analytics to Choose the Best Poly Mailer Bags
    12 Min Read
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
    car expense data analytics
    Data Analytics for Smarter Vehicle Expense Management
    10 Min Read
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Which is more important? Rearview mirrors or windshield?
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 Visualization > Which is more important? Rearview mirrors or windshield?
Data VisualizationPredictive Analytics

Which is more important? Rearview mirrors or windshield?

GaryCokins
GaryCokins
5 Min Read
SHARE

A popular pair of PowerPoint slides used by business conference speakers first displays a distant car behind in the rearview mirror of an automobile followed by a second PowerPoint of the same auto’s windshield view with a big oncoming truck directly in your lane – beep-beep! I am conflicted with this not so veiled message. I passionately embrace the increasing emphasis on forecasting outcomes and its value to narrow the uncertainty of the future. But this implies knowing and understanding the past is of much less informational value. There is substantial value in both views – the past and the future.

I agree with the symbolism that the rear view mirror implies that events have already happened, so they are already behind you and can not be affected. But this message to only look forward is distorting. I personally like having rearview mirrors, and when driving I glance at them often. I want to see what types of vehicles are behind me and what rate they may be speeding up on me.

Why does understanding the past have importance too? There is much to be gained from analyzing trends and drawing inferences from the past. A trend starts back in time but it ends with last …

More Read

Analytics: Not About Saving Time
“We are witnessing a seismic shift in information technology — the kind that comes around every…”
#14: Here’s a thought…
Because It’s the Weekend: Visualizing Ocean Currents
Business Rules Forum

A popular pair of PowerPoint slides used by business conference speakers first displays a distant car behind in the rearview mirror of an automobile followed by a second PowerPoint of the same auto’s windshield view with a big oncoming truck directly in your lane – beep-beep! I am conflicted with this not so veiled message. I passionately embrace the increasing emphasis on forecasting outcomes and its value to narrow the uncertainty of the future. But this implies knowing and understanding the past is of much less informational value. There is substantial value in both views – the past and the future.

I agree with the symbolism that the rear view mirror implies that events have already happened, so they are already behind you and can not be affected. But this message to only look forward is distorting. I personally like having rearview mirrors, and when driving I glance at them often. I want to see what types of vehicles are behind me and what rate they may be speeding up on me.

Why does understanding the past have importance too? There is much to be gained from analyzing trends and drawing inferences from the past. A trend starts back in time but it ends with last moment you checked. Collectively that information is nearly real-time. An inference is a conjecture that allows you to deduce what is going on, and in many cases our wonderful human brain can instantly draw conclusions about what it all means to respond with a next action. If I am driving in the fast lane, the passing lane, of the German autobahn, and I see a BMW approaching me; then I should shift to the slow lane (where you are foolish to not mainly drive in anyway).

In some cases, such as with profit and cost analysis of products and customers, the historical absolute data is less important than the relative relationships. The relationships are essential for modeling the future.

In some cases your inference and subsequent alternative actions needs to be validated. This is where the symbolism of the windshield comes in. The ability to project what-if scenarios is powerful because then you can select the best alternative – strive for optimization. As the emphasis shifts from traditional control to better planning, there is increasingly more being written and discussed about predictive analytics and risk management. Professor Tom Davenport’s book, Competing on Analytics, is an excellent source to learn more. However, there are many flavors of analytics, including segmentation analysis and complex pattern recognition, so do not equate Davenport’s message to be only predictive analytics are important. There is rich information from understanding history too.

TAGGED:modelingpredictive analytics
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

student learning AI
Advanced Degrees Still Matter in an AI-Driven Job Market
Artificial Intelligence Exclusive
mobile device farm
How Mobile Device Farms Strengthen Big Data Workflows
Big Data Exclusive
composable analytics
How Composable Analytics Unlocks Modular Agility for Data Teams
Analytics Big Data Exclusive
fintech startups
Why Fintech Start-Ups Struggle To Secure The Funding They Need
Infographic News

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

retail data
Big Data

Managing Seasonal Fluctuations in Retail with Analytics

5 Min Read
Fintech companies
AnalyticsBig DataPredictive Analytics

3 Ways Fintech Companies are Using Big Data to Beat the Banks

6 Min Read
predictive analytics limitations
AnalyticsExclusivePredictive Analytics

Is Predictive Analytics Revealing Unexplored eCommerce Niches?

6 Min Read

PAW: Predictive Modeling for E-Mail Marketing

7 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 is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

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?