As organizations transition from being data‐driven to reason‐driven in the era of Autonomous Transformation, one of the most entrenched paradigms that will need to shift is individual organizational linear return on investment calculations and required justification in order to receive funding.

This economic paradigm follows the logical, data‐driven concept that organizations should only invest in initiatives that can rigorously demonstrate the path to return on investment with a certain timeline. One of the organizations I have been a part of required the demonstration of 10 times the investment within three years, or the initiative would not be funded.

This kind of requirement naturally leads an organization down the path toward maintenance mode, and when experts and leaders conceive of acts of creation or transformation that will not be able to justify investment within this paradigm, but that they feel are important to the evolution of the market or their own careers, this construct naturally propels these kinds of groups out of the organization to build the idea from scratch and without oversight.

This focus on achieving short‐term, measurable results narrows the aperture to incremental improvements, to the exclusion of strategic investments that may not yield immediate benefits. This has systemic roots, as it is based on and reinforced by individual and organizational economic incentives for which leaders and managers are held accountable in quarterly and annual performance reviews. However, this short‐sighted approach can have negative long‐term effects, especially regarding latent economic potential, as demonstrated in Figure 16.1.

This illustration demonstrates that profit follows a similar natural arc as gravity. Focusing on achieving the highest possible profit in the short term threatens long‐term profitability and limits economic potential.

It took Amazon, ranked the fifth most valuable public company in the world at the time of this writing, nine and a half years before it reported its first profitable quarter.¹

Most are used to the idea of a startup working toward profitability, but there are examples of organizations making long‐term investments, such as Microsoft's search engine, Bing, which was launched in 2009, reported its first profit in 2015, and in 2023, has become a central component to Microsoft's long‐term artificial intelligence strategic partnership with OpenAI.

If we were to create a list of products and services in our daily lives that would not exist if someone had not decided to sacrifice short‐term profit, it would fill up many pages. A review of the past such as this is often met with hindsight bias, defined as “the tendency, upon learning an outcome of an event, to overestimate one's ability to have foreseen the outcome.”² An alternative exercise would be to imagine a list of the products and services that might exist if someone had decided to sacrifice short‐term profit.

These kinds of strategic bets are being made, but against the system, and at great personal risk for those who have argued for and made them. If the system could be transformed to provide an accounting framework that, in practice and not just theory, differentiated between investments in short‐term and long‐term value, measuring for the latter in directional milestones and reason, which requires trust in human reasoning and not only computation, organizations can take a strategic step toward disentangling from the mechanistic worldview of the Industrial Revolution, engineering social systemic dynamics to support a more human future, which would fundamentally transform the way organizations create and sustain value in the market.

Linear versus Exponential Value in the Case of Capability

The paradigm of short‐term, linear return on investment calculations, in the context of technology, plays a significant role in inhibiting long‐term value for two primary reasons.

First, technological capabilities are interdependent. Investments in the context of technology, as illustrated in Figure 16.2, lay the groundwork for future initiatives that would not be possible without the initial investment, but that are not traditionally included in the return‐on‐investment calculation.

Second, technological capabilities span functions and suborganizations, but justifications are traditionally based on individual use cases within a specific organization. If Organizations A and B could both benefit from investments in building data science capabilities, for example, and in the absence of preexisting data science capabilities within the organization, the investment justification for Organizations A and B, each taken separately, might both be rejected. Taken together, however, the development of the capability for one organization could significantly reduce the cost for the second organization, rendering a net positive impact to the overall organization.

In the context of justifying the development of technological capability, new economic models need to be developed that account for the long‐term, systemic impact of the proposed capability across the entire organization, as opposed to only accounting for the localized, short‐term impact to a part of the system.

In the context of Autonomous Transformation, leaders who have gone through the process of solving for the future of their industry and how their organization can best serve its core function within that future will then need to set a strategy, through a process such as organizational reasoning, to leverage acts of creation and the processes of reformation and transformation to realize that vision.

When this strategy has been set, if it is sieved through the rest of the organization, unchanged from the average worldview and processes of organizations in today's context, what emerges out the other side of that process may be unrecognizable.

Figure 16.3 was created to facilitate conversation, together with Figures 16.1 and 16.2, to shift this economic paradigm over time. Once a desired future has been determined, and a strategy has been developed, if the organizational process then proceeds to use an analytic process to break down each individual initiative required to reach that future, aggregating the return on investment of each individual initiative to attempt to model and understand the return on the whole transformation, this figure can serve to illustrate the need to “buy the whole staircase.”

When architecting a home or a skyscraper, architects are not expected to model out and justify the expense of each individual step that makes up a staircase. For each level of the home, there needs to be a way to travel from one level to another.

If an organization has determined that they want to climb to a higher tier of value creation, the same holds true for them. This does not mean that they cannot make strategic and tactical choices in how they design and build “the staircase,” but the conversational pivot from the analysis‐based “step” to the synthesis‐based “staircase” may be required to justify and account for investing in and reaching the long‐term, transformational goal of the organization.