About waste

In 1995, Michael Porter (yes, that Michael Porter) wrote that “every consumption of resources made by a company, if it doesn't go into the final product that is sold on the market, is a loss of efficiency”. And to be honest, that’s really hard to argue against – because one is spending money on a resource that will not add value to the customer. And that’s why one designs for purpose – you should develop your products to maximize the impact (aka value added) to your customer (but not a “nail” beyond it).

Now, there is another really cool dimension about this sentence from Porter. If you look at it with your sustainability lenses on, you find that he could be advocating for circular economy. Because, if I am a company, and I want to take the best out of the circular economy, what I have to do is to try to save resources, or to recover, reuse, recycle the materials that otherwise are going to be lost. If it doesn't go to the final consumer, it doesn't get any value from the market, and is just waste.

In the end, it all starts with design – 80% of a product’s environmental impact is locked there. But also the most of the value one will add to the customer. And it is not a matter of balancing these two things – it is a matter of aligning them.

P.S.- Want an example, look at the great Skip Quick Wash launch all over Europe.

Business differentiators

A few years of experience in tech environments and I can tell you one thing: I am really convinced that technology is enhancing the importance of human skills as business differentiators.

Most people think of decisions as right or wrong, 1 or 0, all or nothing. But decision is more complex - right or wrong are probably not the best way to look at them.

Decision making is about managing a range of outcomes. Of balancing or hedging outcomes within a range of probabilities. That’s essentially for two reasons:
- no decision should be looked at in isolation. There is usually no single “press of a button”. There are many decisions that are taken on a project (or strategy) that should be looked at as a system - and that gives you variables that you can play with to manage desired outcomes and risk.
- And then there is implementation. And implementation of the decision is key for success, for the desired outcome. I have seen (probably) bad decisions that produced great results, because the whole team (including the decision maker) performed brilliantly and made it work.

So, my stance is that decisions should always be looked at systemically, their outcomes as a range and implementation as key for success of any strategy or project.

P.s - And “timing” is a whole new book…

This is a battle we can't lose

Recently, Chris Wedding pointed out that “If we only talk about climate change in terms of protecting ecosystems and future generations, we have already lost the battle.” He points out that we need to change the approach to the tremendous impact climate change is already inflicting on us. Now!

This makes sense. The human brain was essentially designed (or, more precisely, has evolved) to solve immediate, urgent dangers – we automatically prioritize those, even if we desire to tackle the longer term challenges. So, bringing forward the huge health, living conditions and economical costs that we are already experiencing from climate change is an imperative – from a communication standpoint. You want to win the climate change battle? Change the perspective from “future” to “now”!

P.S- If you want figures, let me just point out the 820 Billion usd the US population spends annually on health costs (+ lost wages) because of pollution and climate change (this comes from a Morgan Stanley study). In Europe, the tally sums 140000 preventable deaths from climate change over the past 40 years (over 9000 of which in Portugal – that also lost €13.5Bs in the same period) – these figures coming from the European Environment Agency).

Can we scale up love?

Can we scale up love?

We all have our own ways of developing innovation. Last week, at a Nova SBE Haddad Entrepreneurship Institute event I got to know a singular one - and "love" is at its heart.

The Patient Innovation Bootcamp by EIT Health and Carnegie Mellon University focuses on scaling up medical and care solutions that patients and their close partners developed for their own health problems. Solutions that people developed for themselves and loved ones, to solve serious medical issues and that those people tested on themselves - and, that they believe can solve the same problems in other people.

There are "electronic eyes" developed by parents for their vision-impaired children. There is a story of a deadly cardiac diagnosys on a smart engineer that considered it "just a plumbing problem". There are serious problems - and people that faced them head-on and decided they wanted to share their solutions with the world.

The Patient Innovation Bootcamp ( https://lnkd.in/dHy8Ja2m

) helps these innovators to scale up their solutions. In a way, I really do think they are "scaling up love" - is that possible?

Long-term targets

We all have targets, right? And we all know we should keep those targets short -termed to ensure their relevance, that they are easy to track and to ensure progression.

But that underestimates the magic of thinking long-term and setting additional targets that way - the short-term targets ensure progression, but "to what?", right? After all, as we Portuguese say, "Rome and Pavia weren't made in a day".

Bill Gates has a different way to put it: "Most people overestimate what they can do in one year but underestimate what they can do in ten years".

So, go forth - think about where you (or your project) want to be in 5 to 10 years time... and set them as your long-term targets and objectives.

Hallucinations

In the AI realm, a "hallucination" is a terrible thing. It is generally described as an output that lacks a basis - meaning that it is inaccurate. The AI system tries to give you the right answer for your question / prompt, but, for some reason, it lacks the right reasoning or data and gives you their best guess.

An example (from an IBM lecture): the AI database has been trained up until mid 2022 and you ask about a planet that has been discovered in January 2024. The system might generate a fictional, scenario-based and factually inaccurate answer based on its understanding of astronomy and scientific discoveries.

There are some user-side techniques to mitigate hallucinations. One of them is that you should check the database of the AI system (in my example, you should have a look at the cutoff date of the system). But probably the most powerful ones are to use prompt engineering techniques and tools, that work on the way you present your questions / prompts and guide the AI system through it.

Is it magic?

“Any sufficiently advanced technology is indistinguishable from magic” - Arthur C Clarke

And I think that is exactly what you feel when you use a generative AI tool for the first time. There is that slight thrill of excitement followed by an afterthought - “how far can this go?”

We don’t have an answer for that yet. We know though that we are in the driving seat. We know that the success of companies and ventures in the next ten years will depend on how they drive that triple transformation that has been put in motion, combining AI, Sustainability and People. So... Let’s go - let’s master magic ;) !