Going back to objectives II

What happens when people at the ‘grassroots’ level of a system tries to solve a system problem, or deal with the symptoms and consequences of a systemic issue? How often have we asked this question and consider how pervasive such a problem archetype is in our modern society?

Corporate change and transformation department should be framing questions this way to uncover projects they can work on. Far too often, there are departments operating at ‘corporate’ or ‘strategic’ level of the company just trying to find easy-wins lurking around the organisation to create some kind of change project. The small projects that affect one or two stakeholders can be better dealt with by themselves. Collecting problem statements on the ground may not be the best because ‘the ground’ tend to contextualise problems within their own scope of work or scope of influence. When they do point out something that is more systemic, it is overwhelming or that they point to merely a symptom of underlying problems.

The corporate strategy department needs to hunt down problem statements by considering first what is the objectives that the company is trying to achieve overall, and what are some of the internal elements of the company that is hindering it from achieving its objectives. That would be more useful corporate change. Solving problems that prevent what existing department perceives as hindrance from them doing ‘their work’ may not always be optimal because ‘their work’ can be a function of the existing silos of an organisation and not exactly meeting the overall objectives of it.

Economics of whatever

In my line of work as a strategy consultant, I sometimes work on techno-economic studies. Using a combination of statistical analysis, forecasting techniques and calculations, we estimate various different cost trajectories, and examine the economics of something. It could be a project, a technology, or a decision that a company is trying to undertake which has some cost impact and some benefits somewhere else.

In economics, we can only perform estimates when we assume all else equal. That’s the only way to perform proper sensitivity analysis. When you change more than one parameter, then you’d call it a scenario analysis. There are infinite possible scenarios when there is infinite parameters to shift or parameters with continuous range of possibilities. So when we model the economics of something, we’d always be varying something that we think we have control over, or that we expect will be changing in the near term, and see the effects on the economics.

Yet we often think that the economics of a technology or something will remain the same unless something drastic happens. More often than not, economics of technologies shift when various players in the market make different investments, either in the underlying technologies, manufacturing capacity for the gears and components, or simply into research and development. The actions of many different parties can have a collective impact of making the economics work when at first it doesn’t seem to work.

When we critique the economics of a new innovation or project, we often forget we are comparing them against the status quo where many are already very well-invested into. The years, decades and even centuries of using a technology, manufacturing it, creating complex supply chain and auxiliaries around the status quo. It is naturally hard to beat. But what is critical about a new technology is that the incremental investments can make a large impact, small changes to scale can also make a difference. Coordination and changing expectations play a big role.

Will the economics of new innovations change overnight? Unlikely, but they typically change faster than you and I can work out the math for the economics of it.