Posts Tagged ‘early adopter’

Deep

October 10, 2020

Today, I wrote this entry on my other blog:

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Strategy as Tires: Explanations change. When you add a deeper layer, explanations become deeper long before that depth shows up in the classroom..

Computing is done in layers. We usually program in a higher-level language. We might program in the assembly language for a specific microprocessor. The code in that higher-level language was translated into assembly language at the microprocessor-level. A program called a compiler takes care of that. Or, you wrote your program at the assembly level yourself.

Some engineers that design microprocessors work at the bit-slice level. This is where you define the components of the microprocessor. This level is still code. The next layer is physical or silicon.

This is historic. I have not worked at the silicon level. I have not worked at the firmware level. But, one of my bosses programmed at the bit-slice level. I programmed in various assembly and higher-level languages. I’ve written an SQL-based application. If I need it, it happens. But, do we still do bit-slice work? Probably not.

Technology moves on. It leaves layers behind. It leaves explanations, aka theories behind. And, all those cords and boxes, that hardware that piles up in our closets, the newest new, most amazing stuff back then, fades away.

As marketers, our role is to contextualize some new theory, some discontinuous innovation into a category, a company, a product, a market, an industry, and some economic wealth. Swap out some words like service and product, and eliminate the things that continuous innovation does not do, and you have arrived at where were we are today. We talk about our expectations of economic gains from innovations in its past discontinuous innovation days. But, we only do continuous innovation. And, we only do it for cash, not economic wealth.

We are working as marketers at a layer less deep.

Those layers of computing in my example turn up in other places as well. It turns up in math. I’m reading Elliptic Tales. I’ve watched some videos on pre-calculus algebra. Graphing has changed. If the numerator and the denominator of an equation have a common factor, you don’t just cross them out. You do the substitution and solve for the y-value. Then, you put a hole at that point at (x,y). Then you cross those two factors out.

That is working at the equation level. There is a group level under the equation. Then, there is the set level under the group. It is set-theoretic topology moves that hole from the set into the torus representing the equation. Layers. Deeper. Lateral.

Each of those layers started with the founding new theory, a discontinuous innovation. The old-new rhetorical approach works with continuous innovation, but the new-old rhetoric starts from scratch and builds a new ontology from scratch without regard to the existing ontology. Eventually, the new is rewritten so it makes sense to those being left behind by the new theory. That new theory is much older by that point.

Each layer had its own technology adoption lifecycle (TALC). Once a layer reaches the late mainstreet phase of its TALC, it enters the K-12 classroom. School mathematics is about 100 years behind university mathematics. Statistic is similar.

We like to think about the TALC as moving left to right over time. Maybe we should try turning it on its side so the B2B early adopter are just above the technical enthusiasts.

Here I have illustrated the layers as being adopted. One complication is that each carrier has its own zero layer. In the device phase, the telcos have their own zeros for their level of task sublimation, while their customers have a much simpler level of task sublimation. Each layer defines its own level of task sublimation’

I’ve divided the cloud phase into vertical application and horizontal applications. The cloud providers did that. Vertical applications were easier to migrate to the cloud, while the horizontal applications were much harder, or impossible to migrate. Those horizontal applications are being rewritten by the product-led growth companies to fit the SaaS paradigm.

The large black arrow is about the cannibalization of the IT horizontal phase resulting from the migration of the money from early mainstreet to the horizontal cloud. The white area in the early mainstret phase is the money lost to the cannibalization. This migration is also shown by the small black arrow. The TALC is changing shape. But, be warned here, the cloud is where the category goes to die. Quantum computing will have its own TALC. It will not be a continuous innovation.

The TALC, as shown in grey, represents the total addressable market. Growth means that you move across the TALC faster, but you only have so many prospects. Growth is short-term thinking.

I didn’t show was how task sublimation moves us down the market and how each layer defines its own place in the market. Task sublimation reduces the revenues, while increasing market size, but does not by itself, constitute a down market move. You are forced to go there. Sublimating the tasks delivered in an application means rewriting the application significantly.

While I drew this figure, the chasm problem presented itself. So I wanted to make the cham clear. There are the B2B early adopters. Their applications sell into their vertical. That is where Geoffrey Moore’s chasm happens. There are also B2C early adopters. That is where Malcom Gladwell’s chasm happens. In the former, you capture three degrees of separation from the early adopter, and engage in personal selling to the first two degrees. Sales reps hate the third degree. In the latter, it is just a matter of doing the typical product marketing approach. The latter prospects use media to learn their new technologies. These are apples and oranges. When marketers fail, it’s always the chasm. Discontinuous innovations face the chasm. Continuous innovations do not face the chasm.

Vertical markets have media so like Gladwell’s late mainstreeters, they are accessible via standard marketing approaches. But the market for the early adopter’s product visualization is limited to their competitors doing exactly same jobs to be done. They are on the same branch of the same subtree of the industry classification scheme. They do not have trade journals.

I have used the standard TALC here. The software mediated model might show the carrier and carried content layers more clearly. I left that to the two columns of numbers on the left. Every layer has is crossing the TALC at its own pace. VC’s want immediate returns, so we can hardly innovate these days. Billions might take twenty-five years. Yeah, VCs say no to that.

Taking a new layer to market, the discontinuous innovation involved will replace the underlying technology of existing jobs to be done. Still, it does the same jobs to be done that we are already doing. We were already doing SEM before the internet took over those jobs to be done. The new underlying constraints will have to be discovered for many years to come.

Enjoy!

I need some comments. I can only talk to a wall for so long. And I need some traffic over on my Strategy as Tires blog. Come over and take a look. Thanks.

Bijection

July 27, 2020

Yesterday, while reading about infinity in Eric Schechter’s Georg Cantor (1845-1918): The man who tamed infinity, I came across a figure that sums up much about software products. A bijection is a particular kind of mapping between sets. So well get mathematical with the next figure for a moment before we get back to the points of this post. The figure is a multiplication table. The terminology is about domains vs codomains in mappings. Outside the range, if an arrowhead points to them, they are in the domain, otherwise, they are in the codomain. One-to-one is trickier than it looks in this figure. A bijection is both surjective and injective. I’ll stop there.

So, on to the next figure. I’ll annotate it for product manager purposes in the later figures.

A product starts at an origin (O). That origin is in a generative space. Some effort is expended to put some functionality A out there beyond O. We’ll call the line AO a job to be done. Similarly, functionality B is delivered to do another job to be done, the line BO. The thick line AB represents the extent of the functionality delivered in the first release.

Notice that the figure is comprised of three triangles. That is three instances of my triangle model.

Now we’ve revised our software. Functionality A has improved been improved by the work done during segment AA’. Similarly BB’. Some of the functionality was left unchanged, but changed due to improvements in the infrastructure. Those improvements moved some of the constraints that limited what was done in the first release. You can think of the pink area as part of the performance area freed up by the loosening of those constraints.

Notice that we did not revise the sortables of the system. We innovated continuously.

A new theory is replacing the prior theory that served as the base infrastructure at the origin, O1. The new theory gave rise to a new infrastructure that a vendor built from a new origin, O2.

In the prior release, some functionality was discontinued. Its job to be done is shown continuing as a red line. The software no longer helps a user do that job to be done. It still needs to be done. Another job to be done, the red circle, emerges on its own job to be done line from the origin, O1. The users keep asking for the ability to do that job to be done. That demand is shown as a red line running from the demand to the function that is provided in the subsequent release.

In the subsequent release, the new technology is substituted as the means to provide the jobs to be done including the new one, and the one that was no longer supported in the prior release. These substitutions bend the jobs to be done lines and replace the former origin.

The jobs to be done lines now point to a new future. The prior jobs to be done lines point to a former future.

With a discontinuous innovation, the discontinuity happened at the ontological level of the new theory. The discontinuous innovation is brought to market in the bowling alley where new applications are brought to life without regard to the underlying technology. The early adopter had a product visualization and a value proposition. The point was to achieve that value proposition.

Discontinuous innovations might give rise to new job to be done, but discontinuous innovations must continue to the prior jobs to be done. When we didn’t need horses, drunks still needed to get home.

A discontinuous innovation has its own set of parameterized constraints. Replacing constraints changes the area where the job involved is approached and performed. The constraints of the prior technology prevented access to some of the performance area/volume. Keep Goldratt’s theory of constraints in mind, behind every constraint, is another constraint. That’s the stuff of continuous innovation. Behind every discontinuous innovation is, hopefully, a long series of continuous innovations. Behind the birth of every category is the long life of the category. Discontinuous innovations birth categories.

I found the original figure an interesting way to visualize a roadmap. Enjoy!































Tipping Point

July 18, 2020

Revised on 8/5/2020. The revisions appear in purple text.

In one of the author talks on YouTube, the diffusion of innovation came up. It was mentioned by more than one author. I can’t cite the speaker. Sorry about that. But, one of them mentioned that the tipping point (TP) was between 15 and 18 percent after the percentage breakdown of the technology adoption lifecycle (TALC).

So I wanted to see where the tipping point happens. So I walked through the the TALC and annotated where that tipping point happens. I did this relative to discontinuous innovation. There is a tipping point for continuous innovation, but it would matter where you start.

So it all starts with a figure.

Technical enthusiasts (TE) are the experts on the relevant theory. That theory can be related to either carried content, or carrier. They live, think, and play in the subject domain. In this figure I drew my Software as Media model of the TALC. The carried content is shown above the x-axis. The carrier is shown below the x-axis. The discontinuous innovation might be carrier, but it could be carried content instead.

Notice that these technical enthusiasts are not B2B early adopters. The Gladwell model is limited to continuous innovation in B2C the late main street phase (LMS). I don’t know the Gladwell percentages. But, the TEs are 2.5% of the total addressable market.

One key aspect of the TALC is that the total addressable market never changes. You have a projection. That projection might be a rough estimate. But, unless you go upmarket or downmarket, the total addressable market is fixed. You won’t be able to determine the phase you are in unless you have a good number for total addressable market. Issues like antitrust law, and crossing the mean of the TALC involve the accuracy of your estimate.

But, growth does not change our total addressable market. Growth means consuming that market faster. When a category dies, it has consumed its addressable market.

The tool I used to graph the percentages is found here. There are other tools there as well.

The x-axis points are defined in terms of standard deviations. It assumes a standard normal. Those assumptions can be changed.

Revised 8/7/2020.

Graph A adds the technical enthusiast phase (TE) and the vertical (V) phase. The vertical phase adds 13.5 percent to the 2.5 percent of the technical enthusiasts phase. The early adopters (EA)s are members of the vertical, so they are a subpopulation within the vertical phase. The bowling alley is a managerial feature, not a phase. Likewise, the chasm is a managerial feature. The chasm is where the product built for the client engagement is sold into the vertical market. A market leader for that vertical market will emerge.

Notice that the vertical market does not reach the tipping point maximum of 18 percent. The technical enthusiasts do not matter in the tipping point calculation. The vertical gets you near the tipping point, but not quite. This is shown in graph B. The tipping point is indicated by the red vertical line and the red text. When I drew the figure, I used the technical enthusiasts in the calculation but realized as I wrote this that they are below the line, aka carrier people, rather than customers. They influence buyers but do not themselves buy. But, both populations together don’t get us to the tipping point maximum. You have to have sold into the vertical phase (V). That is done in the tornado (T), another managerial feature, but that is not shown in graph B.

In graph B, the tipping point graph, the vertical line running from graph A to graph C separates the vertical phase (V) from the horizontal phase (H). I labelled this several times along the vertical line. the horizontal is frequently called the IT horizontal, but it can be any horizontal in a company. HR, for example, is a horizontal function used by all the other organizational components. These horizontals comprise the early main street phase (EMS or EM).

The tornado is another managerial feature. It happens at the entry of the vertical phase. It is here that the tipping point maximum is reached. Seats and dollars are the goal here. Selling here is critical. Selling here is not like sales outside the tornado. Time matters. The bowling alley delivered much of the population that will tips everyone else.

Graph C tells us about the 34 percent of the total addressable market that comprises the horizontal. About 29% of this market is sales that happen after the tipping point.

Graph D tells us about the late main street (LM) or (LMS) phase. It sells to the next 34% of the market. It also talks about the last phase, the laggards that comprise the last 16 percent of the market. The laggard phase has been divided into the laggard and phobic phases. I took the laggard phase to be the device phase. And, I too the phobic phase as the cloud. Notice that neither of these phases should be considered just carrier focused phases. The carriers multiply.

Just keep the tipping point in mind. Know where you are entering the TALC. Know how much of the TALC, how many phases will be traversed in you efforts to tip the populations you are serving.

Enjoy!