“The implementation of new technologies, products, or business models that represent a dramatic departure from the current state of the art in the industry”
J Birkinshaw, J Bessant, R Delbridge”
What constitutes innovation?
In terms of human behavior regarding the idea of innovation, there are several types of innovation that are defined by people, by companies, by experts in the field. Only the innovations defined by experts in the field are reliable and truthful. Innovations defined as such by individuals who are leaders, but not experts in the field, such as most CEOs on down to nearly all managers, are “innovations” identified as such by unreliable sources. Innovations within the company setting are either true, mocked or imitated, perception-based, or non-existent.
First, there is true innovation. The discovery of something that is unique in almost every aspect. True innovations are so different that they often make people turn in another direction, either because they do not understand the innovation, or do not understand the field that it applies to enough to generate a valid opinion.
The second kind of innovation is that false, faux- or mock-innovation, that “innovation” that you think you have uncovered or discovered, but which is reality is only halfway there to being a true innovation. Let’s say that of 10 companies, there are a number of companies that consider themselves to be innovative compared to the rest, and try using their accomplishments to make such statements. As an outsider, listening to this, you give those companies the benefit of the doubt for the moment and ask them for more details about these discoveries, only to find that they have essentially done nothing new, and perhaps even modified what’s already out there to such an extent that the only thing innovative about what was accomplished was the new order in which the same old steps and related activities were placed.
A third kind of innovation is perception-based innovation. This innovation is simply called an innovation for the sake of labeling it as such. Companies that perform these behaviors do so due to the benefits of this advertising. They may have had an innovation in the past that they initially developed, and wish to retain some of the appreciation and respect once generated from that discovery. They use the term innovative to continue to market the company as it was several generations earlier, when the truth is the company has fallen so far behind that it is neither innovative nor does it currently have the capacity to be innovative again in the near future.
The fourth kind of innovation is basic non-innovation. It is the lack therefore of innovation, in the present or recent past.
In the book Diffusion of Innovations by Rogers, he assigns a generous value to the percent of a group that can be considered “innovators.” In general this value is fairly high, but still could be truthful to some extent. In any large company, there are employees who will match the requirements for being innovative, but due to corporate stepladders or poorly trained or quid pro quo human resources employees never manage to be fully utilized by their company. Currently, the majority of companies are within the central 68% of the bell curve above, meaning they are unlikely to see an opportunity once it arises. Add to this the 16% laggards group and we have 74% borderline productive on down to potentially failing companies. Early adopters are normally the best companies out there in the business world, but are hard to identify due to their similarities and sometimes lower activities and appearance when compared with their competitors.
How do today’s innovations fit into the Big Picture?
Source for image: SKS7000 Management VitalSource eBook for Northcentral University. 2013.
Now a company can be innovative in one direction and not be innovative in another. This is the status quo for businesses. In the case of a big industry for example, there are many ways to be innovative, and many ways to experience innovations in several ways. A company can for the most part be partially innovative, producing faux- or mock-innovative inventions or creations that are merely just reshuffled remains of past failures produced by other corporations’ either separately, or as part of the discovery of your chief competitor’s traits within the marketplace.
One company for example could be innovative in how it packages a product for mailing, and so advertise that as a part of its offering, but generate limited sales and so have no opportunities to take advantage of that new discovery. Another company in turn could have a product that is in very high demand, but which has no way of meeting those demands for the moment, unless this new product for shipping is used. So the second company reinvents the invention of the first company, applies it to its own product, which is now a success as a result, and due to these changes, Company 2 get credit for re-inventing Company 1’s discovery.
In terms of innovation type and quality, Company 1 is the true inventor or innovator, and Company 2 the synthetic innovator, capable of resynthesizing the same in its favor. In the illustration below that company could be anywhere in Majority or Laggards groups. If one were to come up with a need for something better than what Company 2 was providing as its innovation, it may not be possible for Company 2 to produce such a product, because none of its inventors understand the basis for how such a new technique was discovered in the first place. The least successful Company 2 is after an innovation has developed, the close to the Laggard group it is.
As another example of bad innovation based claims in the industry, consider a common claim made by an unknown percentage of companies out there trying to market their services. Successful discoveries must go from their creator, to the team for successful testing and prototyping, and from there become a company product. In the work setting, any company that takes more than a year to go from the beginning of Phase 2 to the production phase of Phase 3 is operating too slowly for the product to remain ahead. Once the team work begins, at most 6 months should be allowed to pass before the prototype is put out into the marketplace. CEOs, VPs, Directors and managers who fail to allow these new discoveries to become productive in well under a year are simply too locked into their current state, too dependent upon the past.
Take for example Insurance Company A, which likes to claim it is highly innovative. It successfully markets itself as highly creative in the information out there abouts its servics and products, and need for future employees who are equally innovative. Well, Insurance Company A also likes to claim that it is very much like the other bid 25 out there, Insurance Companies B through Z. So, how do we know which one are innovative and which are not?
From SKS7000 Management Vitalsource eBook for Northcentral University:
In his follow-up book, The Innovator’s Solution, Christensen outlines a process called the disruptive growth engine, which all organizations can follow to more effectively respond to disruptive innovations in their industry. This process has the following steps:
1. Start Early. To gain the greatest opportunities, become a leader in identifying, tracking, and adopting disruptive innovations by making these processes a formal part of the organization (i.e., budgets, personnel, and so on).
2. Executive Leadership. To gain credibility as well as to bridge sustaining and disruptive product development, visible and credible leadership is required.
3. Build a Team of Expert Innovators. To most effectively identify and evaluate potential disruptive innovations, build a competent team of expert innovators.
4. Educate the Organization. To see opportunities, those closest to customers and competitors (e.g., marketing, customer support, and engineering) need to understand how to identify disruptive innovation
Companies that are on the back side of the eight ball lack innovators. They have simply not used a broad minded technique for finding new employees, and have struggled to maintain a status quo for their industry at large. Most companies require these teams because they are by rule in that central group of non-innovative companies, the ‘Majority’ noted in the figure above.
Relating all of this to the two examples give, Insurance Companies A and B, something about Insurance Company A has to stand out for it to succeed. It has to be able to claim, market and prove just how much and why it is so different.
I many contemporary situations, we see this happening daily. When we are looking for a new place to work, we will probably see it even more. Companies like to include in their descriptions of themselves that they tend to be innovation. When all of them do this, there is something wrong with the statistics. That many companies cannot all be that innovative. This means that someone, or some HR talent searchers, or some company designing these advertisements, is exaggerating.
Most companies try to do this, like Insurance Company A, by demonstrating outcomes of work, or providing some sort of evidence for the success of the program. In addition, that company may claim it accomplished each of these tasks without much hesitancy or lack of evidence.
But once you inquire into this claim of novelty and innovation, you find that not all of these features exist, and so, this company is very likely a false advertiser, engaged in faux- or mock-innovative processes and therefore lacking certainty in the discovery. Most companies that claim “innovation” and are not known for being an inventor of something new, are simply not innovators.
With time you may find out that this practice is pretty much the standard in the business world nowadays. Many like to make great presentations, claiming incredible results and highly unique outcomes, when in fact they lack any substantiated proof in the end. This means that you’ve been had by yet another example of great corporate advertising. Something that is not focused as much on overall corporate ability, skills, techniques, creativity or innovation skills, as it is on outward appearances.
Going back to the multiple companies model I am applying this logic to, based on statistics, if there are 26 companies out there, Insurance Companies A through Z, the bell curve suggest that one of these could be a true innovator. The trick then becomes trying to identify that single innovative companies that exists as the outlier. You may not find one this first time through however. One company constitutes 1/26th of the companies, or about 3.8%. The likelihood for true innovation is actually less than 1%, so this company may not fit the bill for being a true innovator.
So, if you double your search to reviewing the top 52, now the chances of one company meeting these requirements constitutes a little bit less than 2% of the total companies out there. You are closer to being likely to find the innovator, but still not beneath that <1% requirement for true innovations to exist.
So you once again double your number reviewed to 104 Insurance Companies. Now you have a likelihood of finding that “outside the box” thinker required for ingenuity to exist. In fact, having explored more than 100 companies now for this process, you can be more certain about your prior suspicions as well, the conclusion that the top 26 and the top 52 were false (faux) innovators, making claims that could not be truly demonstrated to be signs of innovation.
If we double that 104 once more, to 208, we further validate our conclusions about where innovation exists and who or what Insurance Company either produced or owns it.
This last statement is the level at which my argument for the lack of innovative epidemiological research now existing in the big business medical world. At the various levels that currently exist within the health care economics, industry world, there are no innovators out there. A lot of claims for such, but none that truly exist.
The ability to predict people’s health is the innovative process referred to on this page. There are a lot of companies that monitor population health, and report it in various ways using graphs, histograms, line drawings, virtual probability synthesizers and prediction tools, monte carlo modeling techniques, fuzzy logic, and eCloud cuboid OLAP data modeling tools, but none of these produce a tool that tells you exactly where the problem lies and where to begin your projects designed to make people healthier.
The focus today is on industry and income, and where the money is best spent to generate the most satisfactory revenues. Big businesses are into the financing of health care in order to improve upon financial gains, not necessarily to make people healthier by knowing where the specific problems lie.
Healthy People Innovations and NPHG
So how does one know if he/she has created or is into some newly innovative strategy?
The worst place to be with innovations is so far ahead you still need to test your innovation, and even after testing find that the regular businesses do not understand the value of the new discovery.
There is a unique class of innovations known as disruptive innovations. The fit into this category of being able to develop some convincing evidence, but are unable to get the general audience to either understand the value of the innovation, or to be smart enough to foresee its potential impacts on the future. Most businesses, nearly all, lack any leadership able to look far ahead into the future. Only a few companies are out there that have accomplished this. In the Insurance industry, it is the business that developed the methods your company is using that is the innovator. For the computer-internet worlds, it is the inventors of the first computers, the first internets, the first ways to engage in rapid worldwideweb activities that are the innovators, all the rest of us are followers, and those who buy into this early, they are the supporters.
The following table pulled from a textbook on business strategies states the following about true innovators and movers of this disruptive technology, and the followers of this new technique:
TABLE 1. Typical Progression and Effects of Disruptive Innovations on an Industry
1. First mover introduces a new technology. It is expensive, focusing on a small number of high-performance, high-margin customers.
2. Over time, the first mover focuses on improving product capabilities to meet the needs of higher-performance customers in order to continue to reap the highest margins.
3. Later entrants, using a disruptive innovation, have an inferior market position, focusing on lower-performance, lower-margin customers.
4. Over time, later entrants focus on incremental product improvements to serve the needs of more lower-performance customers, also focusing on cost efficiencies to offset lack of margins with economies of scale.
5. As the market matures, all products improve, competition increases, and margins diminish; the first mover rarely learns the efficiencies of the later entrants and is entrenched in high-margin business practices; the first mover’s market share rapidly erodes as that of the later entrants rapidly grows.
6. Ultimately, the later entrants’ products meet or exceed the requirements for the vast majority of the marketplace, they “win” with efficient, low-cost business processes demanded by the majority of the marketplace.
From SKS7000 Management VitalSource eBook for Northcentral University. 2013.
From 1997 to 2004, the ability to produce a valuable technology with NPHG was limited by the technology, storage space, availability of rapid processing tools and techniques, availability of sufficient data to experiment with, and lack of need and interest in whatever new tool or methodology was developed. In 2004, the IT world was more capable of managing the data and the ability to test new algorithms more available along with the needed data. The opportunities for this arose with federal government ftp sites where large amounts of data were stored. From that point on it was possible to mine for whatever you needed to produce whatever you wanted, in whatever way you wanted so long as you had the software capabilities.
Around 2007/8, the ability to take on extremely large datasets came to be. At the time, the term “Big Data” wasn’t used. In 2009, the first Big Data products were produced in Big Data fashion, not just as prototype programs, but as repeatable measurement methods that could be run efficiently. The following is where NPHG sits today, still ahead of the bulk of the profession, and several thousand maps and experimental runs into the product development process. Limiters now are based on executive intelligence and willingness of companies/executives to take risks with these new processes.