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: Intelligence Input = Sales Output
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 > Intelligence Input = Sales Output
AnalyticsBusiness IntelligenceData VisualizationData WarehousingPredictive Analytics

Intelligence Input = Sales Output

Ray Major
Ray Major
6 Min Read
SHARE

As true today as it was 50 years ago? 

Time capsules can be interesting. They can also be humbling. More on that in a moment. 

Contents
  • As true today as it was 50 years ago? 
  • As true today as it was 50 years ago? 

As true today as it was 50 years ago? 

Time capsules can be interesting. They can also be humbling. More on that in a moment. 

Time CapsuleWhen we hear time capsule, most of us think of a dented iron box filled with photos, knick-knacks and documents buried under the cornerstone of the courthouse in a Midwestern hamlet.   

Those doing the burying often specify the amount of time the capsule is to remain in the ground. In some cases, the timespan must remain undefined. For example, four well-known time capsules are “buried” in space. The two Pioneer Plaques and the two Voyager Golden Records were attached to spacecraft for the benefit of music-loving space-travelers in the distant future. Will they prefer Chuck Berry to Mozart? Inquiring minds want to know. 

More Read

CRANberries: Keep up-to-date with R packages
Tips for the KDD challenge :)
What is the Best Organization Chart for Performance Management?
AI Technology is Changing Outbound Calling for Better or Worse
What the Ebola Crisis Has Taught Us About Big Data

A fifth space-bound time capsule, the KEO satellite, to be launched circa 2016, will carry individual messages from Earth’s inhabitants addressed to earthlings around the year 52,000, when it is due to return. Setting aside navigation and language issues, I suspect DVD player parts will be hard to come by then, even on Craigslist. Good luck with that. 

There’s another type of “time capsule” that I want us to consider: the scholarly article from decades past. (And now we’ve reached the humbling part of the story). 

In my experience many tech professionals, especially the executive ranks, consider themselves forward-thinkers, early adopters, one or two steps ahead, dispensers of wisdom. “If companies or consumers would just take our advice and buy our product or license our app, businesses would run better, people would be happier.” Or some variation on that theme. 

Well, it’s indeed rather humbling to discover thinkers who, 50 years ago, understood with great clarity what we today believe is perceptive, advanced stuff. Especially when they really nail it! 

If you follow my musings, you know that one of my most cherished tenets in BI is that data is dumb and people are smart. It’s only through the consistent, rigorous application of human intellect that data can be transformed into better decision-making. Business Intelligence tools are the bridge…the bridge to understanding and then predicting. I considered this point of view modern and progressive, even a little ahead of its time.

I was perhaps even a little smug. Until I read something from 1964. Ouch! 

McKinsey & Company has been publishing some “classics” recently, and what follows is an excerpt from a “trends” article by John Louth*. 

The dominance of the customer 

It is nearly a truism that the needs and wants of the consumer are the critical issues today in creating new products and services, and developing the accompanying plans to merchandise them at a profit. But this trend—the first on my list—is still in process of evolution. 

The need to understand and anticipate future customers is bound to become even more essential than in the past, because the end users of almost every company’s products are shifting in makeup, location, and number at an ever-increasing rate. 

The significance of this to senior marketing executives is twofold: First, they cannot—indeed, they must not—assume that yesterday’s customers will be available tomorrow. Second, they had better be certain that they have adequate sources of market information. Unless they can keep up with what is happening to their markets, the whole company’s selling effort may ultimately be directed at the wrong people with the wrong products and at the wrong time. 

This is what a marketing vice president I know meant when he said, “My company’s sales output can’t be any better than my intelligence input.” 

That final quote says it all. The (so I thought) modern Business Intelligence value proposition delivered brilliantly. Dramatic. Crisp. Logical. Timeless. 

Thank you Mr. Louth and McKinsey for the time capsule. We carry on the work you started.  

* John D. Louth was a principal in McKinsey’s San Francisco office and specialized in problems of organization, marketing, and sales management. This article, based on a presentation he made to a West Coast marketing-executives group in 1964, appeared in the autumn 1966 issue of McKinsey Quarterly. It was adapted for the Quarterly with permission from Dun’s Review, which had published an earlier version in April 1966.

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

IBM’s New Retail Tools How you shop: what it…

1 Min Read

Momentum for Enterprise Mobile Apps – Workday, Salesforce.com and Box.net

6 Min Read

Pssst … How Much Money For Your Personal Data?

8 Min Read

Top Trends in Cloud Innovation

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.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

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?