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The Spreadsheet Maturity Cycle – Managing Spreadsheet Series: 2 of 5

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Spreadsheets have been around for a long time. In many ways, the common spreadsheet has emancipated the end user from the control of the IT organization. In a word the spreadsheet provides autonomy of processing to the end user.

And in nearly every organization, the spreadsheet has spread like wildfire. But there is a recognizable, predictable phenomenon that occurs in organizations. Organizations go through a highly predictable maturity cycle when it comes to spreadsheets. Fig 1 depicts that Spreadsheet Maturity Cycle –

On day 1, the organization has all of its technology needs serviced by the IT organization. On day 1 dissatisfaction grows with IT because of the promises made that are never filled. The IT organization turns into such a labyrinth that nothing useful ever comes out of it.

On day 2, the spreadsheet and personal computers appear. At first no one even notices them. But their availability and affordability are such that soon they find their way into the corporation.

On day 3, the spreadsheet starts to proliferate. One department sees what another department is doing and decides to do it themselves. Soon there are all sorts of spreadsheets to be found in the organization.

On day 4, there are spreadsheets everywhere. Some departments have people who do nothing else but build spreadsheets.  In some organizations, there are ten times the number of spreadsheets as there are people. There are so many spreadsheets that no one has any idea what the real numbers are for the corporation. Furthermore, different organizations defend their spreadsheet as if the numbers on the spreadsheet were the Gospel.

On Day 5 someone notices that there is plenty of data to be found in the corporation but no BELIEVABLE data to be found. The same data appears in different spreadsheets with a different value in each place. Trying to make an informed decision based on spreadsheet data becomes a nightmare. Someone suggests that data integrity may be important.

On day 6 the appropriate spreadsheet data is identified and is committed to a data base. Now the corporation has believable data.

In truth most organizations are in day 4. Fig 2 depicts day 4 –

Fig 2 is suggestive of spreadsheet Hell. There are spreadsheets everywhere and no believable data anywhere.

Fig 3 shows the dilemma –

In one spreadsheet the value for a number is shown to$23. In another spreadsheet, the same value is shown to be $4531. In another spreadsheet the value is $0.

When management has to make a decision, they have no idea where to turn.

Finally one day someone wakes up and say – “Enough of this insanity.” It is recognized that spreadsheets give the end user autonomy. But the long term effect of the autonomy is chaos. And trying to run the corporation on chaos is not a winning proposition.

It is at that point that some spreadsheet data is turned into corporate data. The likely candidates for spreadsheet data being turned into corporate data are –

  •   Formal spreadsheets
  •  Recurring spreadsheets

The spreadsheets that are the most viable candidates are those spreadsheets where there is the highest business value.


Bill Inmon – the “father of data warehouse” – has written 57 books published in nine languages. Bill was named by ComputerWorld as one of the ten most influential people in the history of the computer profession. Bill lives in Castle Rock, Colorado.

Bill’s latest book is TURNING TEXT INTO GOLD, Technics Publications, a book that shows how text can be turned into business value. TURNING TEXT INTO GOLD is available on Amazon.com.

Also Read: ANALYTICS INDIA SALARY STUDY 2020 – BY AIM & JIGSAW ACADEMY

PS: The story was written using a keyboard.
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William Inmon

William H. Inmon (born 1945) is an American computer scientist, recognized by many as the father of the data warehouse. Bill Inmon wrote the first book, held the first conference (with Arnie Barnett), wrote the first column in a magazine and was the first to offer classes in data warehousing. Bill Inmon created the accepted definition of what a data warehouse is - a subject oriented, nonvolatile, integrated, time variant collection of data in support of management's decisions.
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