ONCE UPON A TIME

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ONCE UPON A TIME

By W H Inmon

Once upon a time IBM was king of the hill in technology. Once upon a time IBM’s mainframes and data bases and operating systems ruled the world.

But look around. Today IBM is an also ran when it comes to innovation in technology. So how did IBM go from being king of the hill to being an also ran? There were many steps in the downfall of IBM. Here are some of them

1)?????IBM told the world that it needed a new data base management system – DB2. It wasn’t enough that competitors told the world that it’s IMS was old and hard to use. IBM made matters worse by agreeing with them then producing a technology that was even more opaque and more difficult to use than IMS. IBM compounded the mistake by trying to make DB2 be a single technology that served all the purposes in the world, rather than a specialized technology.

2)?????IBM’s adventures with the repository. Many years ago – when IBM ruled the roost – IBM told managers not to buy industry repositories because IBM was coming out with one that would be the “industry standard”. This conversation went on for six years or so. Then one day IBM announced there was not going to be a repository after all. IBM lost a lot of credibility with this misstep. It was reported that IBM spent $100,000,000 on the development of the repository that never made a penny for IBM.

3)?????IBM and the pc. When Microsoft came along, IBM treated Microsoft as if they were a pesky fly on the wall that needed to be swatted away. Today Microsoft is bigger than IBM. Who is the fly on the wall now?

4)?????IBM told the managers of the world that still listened to them that Big Data was coming. IBM operated on the assumption that there was a wealth of information just waiting to be discovered in their piles of data. IBM and the world discovered that all data is not equal. Some data has much more business value than other data. So the basic premise of finding amazing value in Big Data was proven false, painfully and expensively by IBM’s customers. One wonders if those customers even remember who sold them on Big Data in the first place?

5)?????IBM’s Watson had great success in defeating Ken Jennings and Roger Craig on Jeopardy. This was a spectacular coup. Anyone who can do that must be talented because Jennings and Craig are plenty smart. But the success with Watson and Big Blue on Jeopardy did not translate back to business problems. The kind of logic used to master Jeopardy questions was not the same kind of logic that the business person needs to make business decisions.

6)?????IBM and data science. IBM attempted to negate the need for a data warehouse by telling the world that what we needed was data science, not a data warehouse. So a small army of expensive, academic, highly educated data scientists were leashed on the world. And soon those data scientists were turned into data administrators and data garbage men/women because the data that they needed to operate on simply was of such poor quality that data science did not work as advertised.

7)?????IBM and NLP. IBM noticed that there was a lot of value wrapped up in text. So they turned to universities to learn how to manage text. The problem was that the people in the universities they turned to had never built a commercial system before. The people that IBM had turned to were good at writing papers, teaching classes, and studying language. But they weren’t good at creating a commercially viable product.

8)?????Once upon a time IBM had close contact and control for their customers. Then one day IBM found that these support people cost a lot of money. So IBM made the strategic decision to lessen the account control that they had. In the short run this did improve IBM’s bottom line. But in the long run, it opened the door to Oracle, SAP, Microsoft and others. And those others rushed into that open door.

Once upon a time there was this saying – you never get fired if you choose IBM. Today the saying is – you probably will get fired if you choose IBM.


Bill Inmon lives in Denver Colorado with his wife and his Scotty dog Jeb. Jeb gets his daily exercise and if Jeb doesn’t get his walks, he lets everyone know. Jeb knows who runs the household.

Vishwajit Danke

Data & AI Governance -Principal Consultant

2 年

Bill what is your opinion on the future of Cognos

Will Potter

Will Potter, Principal Data Consultant, Best Practice driven Information & Data Architecture, Data Governance, Data Management, AI/ML driven Data Analytics solutions.

2 年

Bill, I have been in IT for 43 years now most of it in Data, as usual a very spot on assessment!!

Ed Wolfe

Business Intelligence & Data Warehouse Analyst | IT Consultant | Critical Thinker | Certified FOREST RIM? Textual ETL? & Data Analyst | Creative Writer | Editor | Proof-reader | Middle Eastern & North African Studies

2 年

Once upon a time The world was sweeter than we knew Everything was ours How happy we were then But somehow once upon a time Never comes again

Joe Reis

Data Engineer and Architect | Best selling author and course creator | Recovering Data Scientist ? | Global Keynote Speaker | Professor | Podcaster & Writer | Advisor & Investor

2 年

Good read Bill Inmon. These days, I can think of many companies where you’ll lose your job for buying IBM. At a minimum you’ll get a lot of weird looks, like you’re wearing a hair shirt.

What are your thoughts on the homemade pasta machine that is infosphere Datastage?

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