Return on Investment breaks Feature Injection.

For many years I have focused on value as the driver of IT development. “Break the model” is the part of Feature Injection that tells us to look for examples that do not fit within the “Olaf” (Model). For some time I’ve been aware that there are examples of development investment that do not fit nicely within the Feature Injection process. These examples have been at the edge of my peripheral vision. I’ve been aware of them but almost subconsciously ignored them because they do not fit in the model. This is exactly the bias that “Break the Model” attempts to address.

What are they? Improvements to the inputs and processes (expecially non functional requirements). Obvious they are valuable but they do not deliver value to the user as we know all of the value in a system comes from consuming the output. i.e. The outcome.

According to the definition of Feature Injection, all value comes from the output which is true, however improving inputs and processes also brings benefit to the user which is also true.

I have been considering a number of successful companies which do not have an obvious source of income. For example, twitter and instagram. For these companies, they value increasing the number of people who have installed their software (network size) and the amount that people use their network (network activity).

Users of an application will probably download it because it is valuable to them.

The amount of usage will depend on the return on investment of the application. This is a function of the value of the application (which is in it’s output) and the investment they need to make in order to get that value.

The investment from the users perspective is determined by the effectiveness of the inputs and processes. From the users perspective, the investment takes many forms, some of which are:

• Money ( to buy the software / service )
• Time ( How long you must work to get the value you seek )
• Mental investment ( How much brain power is required to derive the value)
• Delay ( How long you must wait for the value )
• Frustration ( How easy and forgiving the application is to use. Whether the app play “snakes and ladders” with the user. )
• Training ( How much time and effort must be invested learning to operate the application )
• Transferability ( Whether the investment is transferrable to another context or application )
• Specialisation.

This leads to an extension of the rules for generating business value.

Development generates business value when it reduces the investment that a user needs to make in order for them to acheive the value they desire.
This is an addition to the existing definition rather than a rewrite. It also means that Feature Injection will need an additional step so that it becomes.

1. Hunt the value (i.e. Increase value)
2. Inject the features
3. Break the model
4. Reduce the user’s investment.

Example – Cameras*.

Cameras have no independent value in the process of image making. The value of a camera is to capture images that can be shared with others across time and location. The value is in the images that are viewed at some later date.

The value in the process has never changed. The value is in the viewing of the images. If we cannot view the image, then the camera could easily be replaced with a stone with loss of value to value stream.

In the early days of cameras a low quality photo image would be created by a very expensive process that involved learning optics, chemistry and building a dark room. This meant that the process was limited to a very small number of people who only captured very high value images (The Queen’s Wedding and Coronation).

The photo production process was automated but still specialist. This meant that people could use a camera to capture images but there was a delay of days to recover the images. The cost of investment was reduced so we could capture images of lower value (Normal people’s wedding’s, birthdays and holidays).

One of the problem with the process was a lack of forgiveness. You never knew whether your images had been captured. This changed with the introduction of the Polaroid Camera which provided instant feedback. You could now take photos until you got it right.

The electronic camera wiped out much of the production process and thus cost of the images.  (Now every day events could be captured).

The internet and social media sites wiped out the remaining cost of getting the images in front of your intended viewers. (Even trivial events can be shared at very little cost).

This has lead to an exponential increase in the number of captured images.

Feature Injection was broken. It failed to properly incorporate non functional requirements related to inputs and processes in the investment decision process. We can fix this now and start to look for more examples that do not fit.

*Deliberately chosen to get a response from @Cyetain