<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=1128054299183456&amp;ev=PageView&amp;noscript=1">
Skip to content

Einstein vs. Ford: IT Strategies for the Modern Era

In December of last year, a contributor for Forbes published an article regarding the state of infamous, enterprise IT failures of the past year. Healthcare.gov (courtesy of CGI), MyCalPay (a nine year $250 Million flop courtesy of SAP), and Deloitte’s unemployment benefits project for California all made the list. While the statistics regarding the CIO responses are eye opening (81% indicated the same failure has occurred multiple times!), the author misses the fundamental point. He concludes by quoting Henry Ford saying, “Failure is simply the opportunity to begin again, this time more intelligently.”

However, at Kinetech we maintain that the status quo has got to change. Taxpayers, shareholders, and business leaders must demand more from their IT providers. Albert Einstein famously quipped, “Insanity is doing the same thing over and over again and expecting a different result.”

So next time you are contemplating an IT upgrade or installing a new system, do not make the same mistake of thinking a configured “out-of-the box” solution is the best approach. Choose Kinetech and let us show you how an agile IT implementation can drive success.

Mendix-1.png
9 Pro Tips for Starting with Mendix
Image of kinetech
kinetech

This post originally appeared on Mendix.com November 12th, 2013. Thanks to Mendix’s continued rapid growth (109% in the first half of 2013 alone), we ...

Digital Transformation Solutions for Financial Services: 5 Low-Code Strategies
Image of Richard Eastley
Richard Eastley

When I began a significant digital transformation project for a regional U.S. bank, low-code technology was not on my radar, and the financial ...

The New Trend Your Competitors Are Using to Steal Insurance Customers
AJ Emmanuel

Insurance is a highly competitive industry driven by data quality and your company’s ability to leverage that data via predicative risk models. ...