SlideShare a Scribd company logo
WHO SAID NOTHING IN THIS WORLD IS FREE?
The Discovery of Free Data
What would you do if you suddenly learned you were sitting on a gold mine? Well, start
digging. Odds are, you are rich in resources you probably didn’t even know you had. We call it
“free data” – a gold mine of information.
An abundance of data is captured in an automated format through the overall workflow process
each and every day. However, only a portion of these facts and figures are used for the
immediate task at hand. The rest is typically discarded. This extra information – or free data – is
actually quite valuable and could be put to use in other capacities that would streamline your
operations and save a great deal of money.
You are already collecting information for specific purposes. Now you must look deeper and
ask yourself how you can mine that data and use it elsewhere. We’ve noticed that there is free
data circulating in virtually every industry. You just need an eye to find it.
Information Mining
When is the last time you were at the airport, number 194 of the 200 people in line at your gate
– while one lone counter clerk worked to check everyone in during the ten minutes remaining
before your flight? Had that airline made use of its free data, you could have been relaxing in
the lounge with plenty of time to spare. The airline’s computer is full of information – including
how many tickets were sold. Knowing what time most travelers would arrive for their flight,
management could have easily planned to have more workers behind the counter. Free data.
How about the cash register at the fast food restaurant that logs in sales information? If this data
is saved and analyzed, the manager may notice a pattern. Maybe every Tuesday at 3:30 p.m., the
store experiences a rush. Perhaps that’s the time kids get out of school and come in for their
daily dose of French fries. (You see, the register will also have recorded information as to what
customers are buying.) Now the restaurant can forecast and schedule additional employees for
that afternoon shift. And they will be sure to have plenty of ketchup on hand to go with those
fries. Free data.
A producer of snack foods in Dallas is a prime example of a company that took advantage of
free data and made it work to their advantage. In the 1980s, this company’s trucks would retrieve
unsold items from stores and give storeowners credit for the merchandise. The information
collected on receivables was stored on a computer. One day, someone in the snack food
company’s marketing department took note that data was being gathered on which items were
and were not selling. In the meantime, raw materials – corn and potatoes – were sitting on the
railroad track, waiting to be processed. A quick analysis of this data told snack food company
personnel whether or not potato chips were selling in West Texas and if corn chips were stronger
in the southern part of the state. The Dallas plant then knew what to make and where to ship it.
Free data.
2
Taking off the Blinders
What kind of free data is floating around in your operation? You, like those in many
companies, may be pressed from an operations standpoint to reduce costs and improve profit
margins. People are investing hundreds of thousands (if not millions) of dollars in automation …
but using it with blinders on. Technology is being left on the table.
Take the example of incoming mail. Perhaps you spent a quarter of a million dollars on a
machine that sorts your mail to individual PO boxes. Great. But did you know that other valuable
information is being captured simultaneously? You can also determine your volume and the
pattern of mail by day of week or by hour. All that data is contained within your machine. Now
you can take this knowledge and start forecasting. If you know that every Monday at 8:00 a.m.,
you get 30% of your volume, you can build a staffing schedule. Free data puts you in control of
your workflow environment instead of reacting to it.
Too many companies are wasting time, energy and money on manual processes, when needed
information has already been electronically captured. A mailroom clerk, for example, will sit and
manually log the trays of mail, when the machine has already counted every envelope. Or what
about the employee who re-keys information into a computer for billing purposes? The data was
already in electronic format. It just came off the computer. But it is being entered again. Billing
may not have been the end goal when this particular automation system was purchased, so no
one thinks to mine that information. But it’s there.
Understandably, managers are focused on accomplishing their particular job – getting from
Point A to Point B in the shortest amount of time with the least amount of problems. However,
there may be a number of side paths that can lead to answers for another operation or help in a
particular area of the processing stream.
A Different Perspective
Free data is often discovered when somebody simply looks at a process from a different
perspective. They see that while information is being gathered for one purpose, it can be
effectively used for another. The zoo generates a lot of manure. But some individuals have
turned it into a business enterprise for fertilizer. Again, free data.
Our challenge is to explore the ways in which you can make more use of the data that already is
out there … right at your fingertips. Don’t let this valuable resource slip through your hands.
Grasp hold of it.
Look to see if you have information available that can be used in a different way than originally
intended. The more you train yourself to view your operation with new eyes, the more instinctive
it will become. And you will be the richer for it.

More Related Content

Similar to Free Data

10 things that make companies unproductive
10 things that make companies unproductive10 things that make companies unproductive
10 things that make companies unproductive
Charles H Strange
 
An Insight Into the Differences Between Data Mining and Machine Learning
An Insight Into the Differences Between Data Mining and Machine LearningAn Insight Into the Differences Between Data Mining and Machine Learning
An Insight Into the Differences Between Data Mining and Machine Learning
Andrew Leo
 
Embracing data science
Embracing data scienceEmbracing data science
Embracing data science
Vipul Kalamkar
 
Gerenral insurance Accounts IT and Investment
Gerenral insurance Accounts IT and InvestmentGerenral insurance Accounts IT and Investment
Gerenral insurance Accounts IT and Investment
vijayk23x
 
Data dynamite presentation
Data dynamite presentationData dynamite presentation
Data dynamite presentation
W. David Stephenson
 
Big Data - CRM's Promise Land
Big Data - CRM's Promise LandBig Data - CRM's Promise Land
Big Data - CRM's Promise Land
Danny Camprubi Douglas
 
How Accounts Payable Automation and Agility Drive Long-Term Business Producti...
How Accounts Payable Automation and Agility Drive Long-Term Business Producti...How Accounts Payable Automation and Agility Drive Long-Term Business Producti...
How Accounts Payable Automation and Agility Drive Long-Term Business Producti...
Dana Gardner
 
Data-Driven Enterprise off Your Beat - Matt Wynn - Lincoln, Nebraska, NewsTra...
Data-Driven Enterprise off Your Beat - Matt Wynn - Lincoln, Nebraska, NewsTra...Data-Driven Enterprise off Your Beat - Matt Wynn - Lincoln, Nebraska, NewsTra...
Data-Driven Enterprise off Your Beat - Matt Wynn - Lincoln, Nebraska, NewsTra...
News Leaders Association's NewsTrain
 
Make data more human
Make data more humanMake data more human
Make data more human
Debashish Jana
 
BBDO Proximity: Big-data May 2013
BBDO Proximity: Big-data May 2013BBDO Proximity: Big-data May 2013
BBDO Proximity: Big-data May 2013
Brian Crotty
 
Big Data
Big DataBig Data
Big Data
BBDO
 
141900791 big-data
141900791 big-data141900791 big-data
141900791 big-data
glittaz
 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
Gerard McNamee
 
Comparative Study of Improved Association Rules Mining Based On Shopping System
Comparative Study of Improved Association Rules Mining Based On Shopping SystemComparative Study of Improved Association Rules Mining Based On Shopping System
Comparative Study of Improved Association Rules Mining Based On Shopping System
Eswar Publications
 
A Human Touch in Machine Learning
A Human Touch in Machine LearningA Human Touch in Machine Learning
A Human Touch in Machine Learning
Conal Sathi
 
Data science training in hyderabad
Data science training in hyderabadData science training in hyderabad
Data science training in hyderabad
Kelly Technologies
 
3 Mitos de Big Data revelados
3 Mitos de Big Data revelados 3 Mitos de Big Data revelados
3 Mitos de Big Data revelados
Data IQ Argentina
 
Converting Big Data To Smart Data | The Step-By-Step Guide!
Converting Big Data To Smart Data | The Step-By-Step Guide!Converting Big Data To Smart Data | The Step-By-Step Guide!
Converting Big Data To Smart Data | The Step-By-Step Guide!
Kavika Roy
 
Data Management Strategies - Speakers Notes
Data Management Strategies - Speakers NotesData Management Strategies - Speakers Notes
Data Management Strategies - Speakers Notes
Micheal Axelsen
 
Suburbia Sales Booklet (2019)
Suburbia Sales Booklet (2019)Suburbia Sales Booklet (2019)
Suburbia Sales Booklet (2019)
Menno Vlietman
 

Similar to Free Data (20)

10 things that make companies unproductive
10 things that make companies unproductive10 things that make companies unproductive
10 things that make companies unproductive
 
An Insight Into the Differences Between Data Mining and Machine Learning
An Insight Into the Differences Between Data Mining and Machine LearningAn Insight Into the Differences Between Data Mining and Machine Learning
An Insight Into the Differences Between Data Mining and Machine Learning
 
Embracing data science
Embracing data scienceEmbracing data science
Embracing data science
 
Gerenral insurance Accounts IT and Investment
Gerenral insurance Accounts IT and InvestmentGerenral insurance Accounts IT and Investment
Gerenral insurance Accounts IT and Investment
 
Data dynamite presentation
Data dynamite presentationData dynamite presentation
Data dynamite presentation
 
Big Data - CRM's Promise Land
Big Data - CRM's Promise LandBig Data - CRM's Promise Land
Big Data - CRM's Promise Land
 
How Accounts Payable Automation and Agility Drive Long-Term Business Producti...
How Accounts Payable Automation and Agility Drive Long-Term Business Producti...How Accounts Payable Automation and Agility Drive Long-Term Business Producti...
How Accounts Payable Automation and Agility Drive Long-Term Business Producti...
 
Data-Driven Enterprise off Your Beat - Matt Wynn - Lincoln, Nebraska, NewsTra...
Data-Driven Enterprise off Your Beat - Matt Wynn - Lincoln, Nebraska, NewsTra...Data-Driven Enterprise off Your Beat - Matt Wynn - Lincoln, Nebraska, NewsTra...
Data-Driven Enterprise off Your Beat - Matt Wynn - Lincoln, Nebraska, NewsTra...
 
Make data more human
Make data more humanMake data more human
Make data more human
 
BBDO Proximity: Big-data May 2013
BBDO Proximity: Big-data May 2013BBDO Proximity: Big-data May 2013
BBDO Proximity: Big-data May 2013
 
Big Data
Big DataBig Data
Big Data
 
141900791 big-data
141900791 big-data141900791 big-data
141900791 big-data
 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
 
Comparative Study of Improved Association Rules Mining Based On Shopping System
Comparative Study of Improved Association Rules Mining Based On Shopping SystemComparative Study of Improved Association Rules Mining Based On Shopping System
Comparative Study of Improved Association Rules Mining Based On Shopping System
 
A Human Touch in Machine Learning
A Human Touch in Machine LearningA Human Touch in Machine Learning
A Human Touch in Machine Learning
 
Data science training in hyderabad
Data science training in hyderabadData science training in hyderabad
Data science training in hyderabad
 
3 Mitos de Big Data revelados
3 Mitos de Big Data revelados 3 Mitos de Big Data revelados
3 Mitos de Big Data revelados
 
Converting Big Data To Smart Data | The Step-By-Step Guide!
Converting Big Data To Smart Data | The Step-By-Step Guide!Converting Big Data To Smart Data | The Step-By-Step Guide!
Converting Big Data To Smart Data | The Step-By-Step Guide!
 
Data Management Strategies - Speakers Notes
Data Management Strategies - Speakers NotesData Management Strategies - Speakers Notes
Data Management Strategies - Speakers Notes
 
Suburbia Sales Booklet (2019)
Suburbia Sales Booklet (2019)Suburbia Sales Booklet (2019)
Suburbia Sales Booklet (2019)
 

Free Data

  • 1. WHO SAID NOTHING IN THIS WORLD IS FREE? The Discovery of Free Data What would you do if you suddenly learned you were sitting on a gold mine? Well, start digging. Odds are, you are rich in resources you probably didn’t even know you had. We call it “free data” – a gold mine of information. An abundance of data is captured in an automated format through the overall workflow process each and every day. However, only a portion of these facts and figures are used for the immediate task at hand. The rest is typically discarded. This extra information – or free data – is actually quite valuable and could be put to use in other capacities that would streamline your operations and save a great deal of money. You are already collecting information for specific purposes. Now you must look deeper and ask yourself how you can mine that data and use it elsewhere. We’ve noticed that there is free data circulating in virtually every industry. You just need an eye to find it. Information Mining When is the last time you were at the airport, number 194 of the 200 people in line at your gate – while one lone counter clerk worked to check everyone in during the ten minutes remaining before your flight? Had that airline made use of its free data, you could have been relaxing in the lounge with plenty of time to spare. The airline’s computer is full of information – including how many tickets were sold. Knowing what time most travelers would arrive for their flight, management could have easily planned to have more workers behind the counter. Free data. How about the cash register at the fast food restaurant that logs in sales information? If this data is saved and analyzed, the manager may notice a pattern. Maybe every Tuesday at 3:30 p.m., the store experiences a rush. Perhaps that’s the time kids get out of school and come in for their daily dose of French fries. (You see, the register will also have recorded information as to what customers are buying.) Now the restaurant can forecast and schedule additional employees for that afternoon shift. And they will be sure to have plenty of ketchup on hand to go with those fries. Free data. A producer of snack foods in Dallas is a prime example of a company that took advantage of free data and made it work to their advantage. In the 1980s, this company’s trucks would retrieve unsold items from stores and give storeowners credit for the merchandise. The information collected on receivables was stored on a computer. One day, someone in the snack food company’s marketing department took note that data was being gathered on which items were and were not selling. In the meantime, raw materials – corn and potatoes – were sitting on the railroad track, waiting to be processed. A quick analysis of this data told snack food company personnel whether or not potato chips were selling in West Texas and if corn chips were stronger in the southern part of the state. The Dallas plant then knew what to make and where to ship it. Free data.
  • 2. 2 Taking off the Blinders What kind of free data is floating around in your operation? You, like those in many companies, may be pressed from an operations standpoint to reduce costs and improve profit margins. People are investing hundreds of thousands (if not millions) of dollars in automation … but using it with blinders on. Technology is being left on the table. Take the example of incoming mail. Perhaps you spent a quarter of a million dollars on a machine that sorts your mail to individual PO boxes. Great. But did you know that other valuable information is being captured simultaneously? You can also determine your volume and the pattern of mail by day of week or by hour. All that data is contained within your machine. Now you can take this knowledge and start forecasting. If you know that every Monday at 8:00 a.m., you get 30% of your volume, you can build a staffing schedule. Free data puts you in control of your workflow environment instead of reacting to it. Too many companies are wasting time, energy and money on manual processes, when needed information has already been electronically captured. A mailroom clerk, for example, will sit and manually log the trays of mail, when the machine has already counted every envelope. Or what about the employee who re-keys information into a computer for billing purposes? The data was already in electronic format. It just came off the computer. But it is being entered again. Billing may not have been the end goal when this particular automation system was purchased, so no one thinks to mine that information. But it’s there. Understandably, managers are focused on accomplishing their particular job – getting from Point A to Point B in the shortest amount of time with the least amount of problems. However, there may be a number of side paths that can lead to answers for another operation or help in a particular area of the processing stream. A Different Perspective Free data is often discovered when somebody simply looks at a process from a different perspective. They see that while information is being gathered for one purpose, it can be effectively used for another. The zoo generates a lot of manure. But some individuals have turned it into a business enterprise for fertilizer. Again, free data. Our challenge is to explore the ways in which you can make more use of the data that already is out there … right at your fingertips. Don’t let this valuable resource slip through your hands. Grasp hold of it. Look to see if you have information available that can be used in a different way than originally intended. The more you train yourself to view your operation with new eyes, the more instinctive it will become. And you will be the richer for it.