We help companies fix broken IT projects and show others how to avoid breaking projects in the first place.
Unfortunately, it is. Here are the details. Perhaps the most definitive work on enterprise IT project failures was done by the Standish Group in 2015 when they surveyed 50,000 companies. Overall, they found that 71% of all IT projects failed to deliver expected results on time and on budget—and these were major, not minor misses. This 70% failure rate has been confirmed and/or endorsed over the last decade by several industry experts such as Gartner, IDC, HBR, 4PM, Capterra, the IEEE and others.
Now, in the interest of fairness, 70% isn’t quite as bad as it appears. Not all failures are created equal. 50%, half, of IT projects just experience some “significant” level of failure—meaning they’re way (30 – 300%) over budget, way behind schedule or way under-deliver. In other words, the system (or a big piece thereof) never does what it was supposed to do or what you wished it did—it never lived up to its promise. Only 20%, 1 out of 5, are complete and utter disasters. Total failures. Smoking craters that leave management no recourse but to write everything off.
There’s more. If a project costs over $1 Million (our definition of a big or large IT project), the odds of failure jump by 50% over the expected failure rate for a project costing less than $350,000. That means the odds of a total failure for larger projects are 30%—roughly 1 out of 3. The odds of a significant failure rise to about 65%—almost 2 out of 3. The odds of success fall to roughly 5%—only 1 success out of 20 attempts. McKinsey & Company working in conjunction with Oxford University found that 17% of enterprise IT projects, 1 out of 6, go so badly, they threaten the very existence of the organization. And Gartner has said that when it comes to Big Data and AI projects the failure rate is an even more abysmal 85%—5 out of 6 never make it out of the lab. Again, these statistics have been widely vetted and endorsed by industry experts—which is why we’re very comfortable quoting the 1 out of 20 success rate.
Yes. At first glance, the failure rate estimates from PMI (who suggests a range of roughly 14% to 19%) appear to be lower than the failure rates we cite. There are three factors that explain this apparent discrepancy. First, PMI’s annual “Pulse of the Profession” is a global survey that focuses on much larger and more mature organizations with far greater resources than is representative of the general business population. In 2019 54% of the respondent companies (2,406 out of 4,455) were over $500 million in annual revenue with 45% being over $1 Billion. By comparison, there are less than 7,000 companies in the US with annual revenues over half a billion and they represent less than 5/100th of one percent of the total number of US companies. Second, PMI tends to survey its certified members who are more experienced and better trained than the project management population overall. That said, such certified professionals represent only about 5% of all the project managers in the US. Finally, PMI looks at all projects, not just IT projects. So, while PMI’s methodology makes perfect sense when attempting to gain an understanding of the project management profession overall, it is not necessarily reflective of the enterprise IT experience in the US. One would expect to find what PMI has found—better trained professionals in better equipped organizations achieve better results.
The $100 Billion is only part of the story. There are two component costs to IT project failures—the first is more visible, clear-cut and grabs the headlines. The second is less visible, but significantly larger. The first type of costs are those related to IT projects which either fail outright or are otherwise abandoned. These require a total write-off. In the US such costs are widely estimated as falling between $50 and $150 Billion per annum. The lower number is generally regarded as being so conservative that it’s unrealistic. The higher number is thought to be closer to reality, but $100 Billion is widely regarded as the best and most defensible estimate.
The second type of failure costs is harder to both see and quantify, but research by ZDnet and the Institute of Electrical and Electronics Engineers (“IEEE”) provides some good insights. This second type of IT project failure cost comes from rework on all the systems that eventually limp into production but never do what they were supposed to do—so they have to be continually patched throughout their service life. The IEEE notes that almost 50% of a software professionals time is spent on rework rather than on work than is done right the first time. They found that for every dollar avoided up front by short-cutting the business requirements and design processes a company ultimately spends $36-$50 pre-release or go-live to fix what could (should) have been caught earlier. If the error makes it into production, the cost to remediate the issue sky-rockets to as much as 100 times what would have been the up front cost to do it right. Over the service life of the system these remediation costs add up—a bad IT project is a thief that keeps on stealing. Using 2019 IT spending estimates from Gartner along with failure rate analysis from the IEEE yields an estimate of roughly $400 Billion per annum which closely agrees with ZDNet’s separate estimate for these IT project failure costs in the US.
Taken together, the $100 Billion in IT project write-offs and $400 Billion in unnecessary system rework total $500 Billion in annual IT project failure costs.
In the last 20 years neuroscience has made some remarkable advances. We’ve learned that our unconscious mind is playing a far larger role in decision making than we previously thought. It turns out that human beings are not logical, rational actors who consciously think through decisions based on the best available information—as economists have proclaimed and business schools continue to teach. Psychologists have now convincingly demonstrated that a great deal of human behavior is either driven or significantly influenced by our unconscious minds. Economists have had it all wrong, but the business community has yet to catch up with what the scientific community now knows.
The concept of an “adaptive unconscious” was first proposed by Daniel Wagner in 2002. The idea was later expanded in Timothy Wilson’s 2004 book, Strangers to Ourselves where he explained, “The mind operates most efficiently by relegating a good deal of high-level sophisticated thinking to the unconscious, just as a modern jetliner is able to fly on automatic pilot with little or no input from the human, ‘conscious’ pilot.”
Malcom Gladwell’s 2005 book, Blink added to the popular awareness. And in 2011, the Nobel Laureate (in Economics) and Princeton psychologist, Daniel Kahneman (one of the founders of the behavioral economics movement) published a review of the research to explain in layman’s terms the stunning breadth and depth of what he describes as the two systems of our minds entitled, Thinking Fast and Slow. System 1 is unconscious and reflexive. System 2 is conscious and deliberate. These two systems are engaged in the following five automatic behaviors—of which we take little notice and over which we have no control. Click the link for each behavior to read a deeper explanation in our blog.
- Human beings have an auto-pilot for self-preservation that we never knew we had.
- We are incredibly susceptible to suggestions—both overt and covert.
- We are terrible at anticipating things we haven’t encountered before. If we don’t see it, it doesn’t exist.
- Our brains are constantly experiencing rolling brown-outs.
- We don’t work off reality. We work off our gist of reality. Others have to work off a gist of our gist.
No. The EPA Checklist is project management model agnostic. It is a framework for articulating and defining the execution strategy of the business—for capturing what the business wants to do, so that all of the things the business needs to do to accomplish that mission (aka business requirements) can be identified. The EPA Checklist works as well with a Waterfall project as it does for an Agile project.
Quickly. We can only move as fast as you do, but if you take our questions seriously, and answer them promptly, we’ll know within a couple of days whether we can help you. No multi-week discovery sessions. If we can’t help you, we’ll tell you and we’ll leave.
Alternatively, if we think we can help, we’ll lay out next steps to unearth and document the execution strategy of your business or the specific business process in question. At first glance many will feel that such work is unnecessary—that they’ve already got that documentation under control. But by the end, they’re usually amazed at the critical details that are surfaced that they had completely overlooked. (Click here and here for a couple of great examples of what two clients missed.) If you decide to proceed, this next phase usually takes no more than 2-3 weeks (elapsed time) per process—again, assuming your organization (or team) is engaged and responds promptly.
Where things go from here can vary depending upon your specific organization and engagement, but the model of short, discrete phases with tangible deliverables at the end of each phase is the model for how we like to work. We don’t believe in endless engagements. We’re not here to do things for you. We’re here to teach you how to do what we do and then move on. We’ll always be available to provide coaching or answer questions if you need help, but we’re talking about your business, not ours. Only you and your team can execute your mission.
In a phrase, pattern recognition. We see things very quickly that others never do. More importantly, we know from decades of experience what to do to address an issue once it’s been identified. Making a decision to work with us boils down to a decision about time and money. If you’ve got all the time in the world, and money is no object, then by all means—reinvent the wheel and learn things for yourself the hard way. If, however, time and money are tight, then you might want to consider talking to a coach who can show you the ropes.