Pattern Recognition: The 6 Reasons Why Corporate Innovation Fails

This is repetition. I am not the first to make these observations, nor would I ever claim to be the last. As it happens, I have spent an inordinate amount of time, though, in the last year having this conversation over and over again. I now consider myself qualified to claim to notice what might be conveyed as obvious pattern recognition. What I am trying to do is convey this in a straightforward, succinct manner that every senior executive should be able to read and understand in 3 minutes. No beating around the bush. This is aimed at you. So here goes.

One: The people driving the innovation are not disconnected from corporate influence. Every project starts somewhere. In corporations, many of them are championed by executives. Almost every medium and large and especially extremely large corporation has their share of politics and bureaucracy. It’s OK – it happens, and you are not alone. But if that project that is taking three times as long as you would expect, it may be suitable for killing. That’s OK too, but when the team driving it is likely to say, “but Dave (the SVP) really wants this,” we all know what happens. People are people, and they will act in line with their own well-being. When the corporate politics are a part of the innovation effort, it almost always does more harm than good. I have had countless discussions with internal innovation people who have lamented that very thing in painful detail. There are good ways to combat this, but it can be a struggle to get there.

Two: The focus is primarily on uncovering innovation instead of commercializing it. Almost every CEO on every earnings call talks about the pace of change in their market and the imperative to innovate or be killed. They’re right. The pace of change is only increasing, and whatever market XYZ CEO is in, it’s changing fast. But the focus is so often more on “finding” new innovation than it is on “commercializing” it. Building the concept deck, creating the demo, and running the pilots are the easy part. The heavy lifting is in hardening the solution and making it scalable and sustainable for a long market life, complete with all the processes and infrastructure that are needed beyond the prototype, then crafting and executing the required go to market plan. If you have an internal innovation operation, and you find yourself or your teams doing victory dances in the end zone after the successful pilot, stop it. You are rewarding the wrong outcomes. Smile nicely and be encouraging, but don’t spike the ball at your own 30-yard line. You just got a first down. You haven’t scored.

Three: The focus is often on, and prioritized in the context of, the core business. If you have multiple projects in your internal innovation effort, and your business gets pressured by earnings and the need for near term results, the digital disruption project is probably going to be the first to go. The project projecting to give a 2% lift in a key $3.5B a year division over the next 3 years equates to net additional income of $210M. If you can cut your innovation spend in half, from $50M to $25M in tough times, then that project looks great, and cutting the other disruptive project is an easy call. Was it really going to generate even $10M over the same period? The truth is, nobody knew what it would generate. But that’s probably not going to get you where you want. That’s what Blockbuster and Kodak did. There are ways to deal with this but putting your head in the sand isn’t one of them. The easy call isn’t always the right call. This is where really understanding better where the market is headed and embracing instead of rejecting market forces can be a huge asset.

Four: The people on the team driving the innovation are not usually entrepreneurs who have “been there and done that.” I have a friend who characterizes this in the following way: “When you go through a cohort and do the workshops, they show you how to read a balance sheet and tell you about certain best practices of product management and how to present your deck to investors, but when you walk out of the door, and you get punched in the face; that’s when you figure out what your chances of making it really are.” Entrepreneurs commercializing solutions get “punched in the face” every day. I can recount an unbelievable list of nuanced issues and curve balls that account for those countless edge conditions. That’s life in the trenches. The reason surgeons do a residency is because they need to apply what they learn in med school in the company of other experienced surgeons. It helps keep them from killing people. Obviously, in our case, the experienced surgeons are the entrepreneurs who have “been there and done that.” It is a massive mistake to underestimate that value.

Five: The team lacks the deep IoT expertise, and more specifically, the holistic understanding of cyber-physical systems to deliver commercial grade transformative solutions. IoT is tough, and it is a core part of cyber-physical transformation. It is also an amazingly holistic proposition. That means it’s not enough to understand:

  • The chipsets or the communication choices;
  • The security options or the data privacy, data ownership, or data governance considerations;
  • The tiered architecture and the critical role of the edge in the context of an enterprise IoT architecture; and
  • The overwhelming imperative for separating the creation of the data from the consumption of the data and the filtering, aggregating, and enriching the dataset and then the relevant propagation of all or part of that atomic or derived data, to the right constituent in the right time in the right way so the value of the IoT data and other contextualized enterprise and third party data can be optimized to make your Artificial Intelligence and Machine Learning models and other analytic stack functions as truly effective as possible (because when your underlying data is sub-optimal, so are the results from your analytics).

Yes, all that is not enough. Why? Because you also must understand the relationships between the decisions you make for each element. These decisions have ripple effects across the architecture. This is not to suggest enterprise IoT people or operational technology teams are staffed with uninformed underachievers by any stretch of the imagination.  Rather, it points to the significant complexity that makes this level of understanding difficult to come by, yet no less essential. A very large and increasing percentage of innovation is cyber-physical innovation that requires this level of comprehension. That is hard to come by, and it is really important. This is also why there are so many IoT pilots and so few enterprise wide production IoT solutions.

The challenge is not to be or partner with or sell to a corporation that has a well-defined Information Technology architecture that uses IoT Solutions. The challenge is to be or partner with or sell to corporations that have a well-defined Enterprise IoT Architecture. The difference is huge.

Six: The idea of painful objectivity is hard to come by, and this keeps good ideas from succeeding quickly, but worse, this leads to bad ideas taking way too much time and money to fail. And most do. This is directly tied to the first issue of corporate influence, although lacking objectivity is not the exclusive domain of corporate innovation. Many, many startups die for this reason. In fact, most startups fail, and most are due to lack of execution, not due to a bad idea. But when objectivity is compromised, whether due to a team that wants to please an ill-informed executive, or whether they are overly optimistic  inexperienced entrepreneurs brimming with confidence, giving up their teaching job to pursue this idea that will practically “sell itself” in route to them becoming the next Steve Jobs, the end result is often failure. Kidding yourself into thinking an irreversible trend is just a “blip” will kill you. Thinking the selling price will be 2X market because you have a “cool user interface” will kill you. So many, many things will kill you when you have anything less than 100% objectivity. But most don’t come close. And coincidentally, most startups, be they independent entrepreneurs, or corporate innovation efforts, fail.

One thing is certain: the progression to the cyber-physical world is not going away. The imperative to innovate is not going away. The average tenure of companies in the S&P 500 is projected to drop from 33 years in 1965 to 14 years by 2026. Think about that for a second. The world is changing faster and faster, and for corporations, that can be the cause of death or the opportunity for greater prosperity. The executives running the companies and the boards governing the companies need to understand this in spades. If that’s you, then good for you. It is unlikely the net effect of your actions will be neutral. You will either make it better, or you will make it worse. Objectively speaking, that is absolutely in your control. And what an opportunity it is.