In recent issues, we’ve examined some of the major challenges we’re facing as we enter the millennium’s third decade and the key role knowledge-based enterprises will play in shaping our future. For example, in our world of nearly 8 billion minds and growing, natural resources such as metals and minerals are being consumed at more than twice the rate of population growth, according to the OECD (Organisation for Economic Co-operation and Development). And we’ve previously discussed the unrelenting growth in energy demand, which also exceeds the rate of population growth by roughly the same amount.
It is true that there is an abundance of oils, metals, and minerals. It’s just that every marginal drop or ounce becomes progressively more difficult, and more expensive, to extract and process. That’s simply the reality. If we are to solve these challenges, we need to look at them from the perspective of the global economy as a wholly integrated system. With that in mind, let’s take a look at three socio-economic models which have been in play in varying degrees over the past 2 centuries: linear, sustainable, and regenerative.
The linear model
The linear model represents a one-way path from extraction through production, consumption, and disposal. Economies of scale reign supreme, as long as supply and demand continue their seemingly endless upward trajectory. In the past 10 years alone, the total amount of raw materials extracted from the earth has grown by more than 26%, from 65 billion to 82 billion metric tons.
This level of growth leaves a substantial wake in its path. According to the World Bank, roughly 2 billion metric tons of municipal solid waste are generated annually worldwide. This number is expected to increase to 3.4 billion met- ric tons by 2050. Currently, only about 13% of that waste is recycled and 5.5% is composted, while up to 40% is either dumped or openly burned. This brings a wide range of risks, from wild swings in prices and availability up and down the supply chain, to political instability and harmful impacts on health and the environment.
But nothing remains linear forever. What goes up eventually comes down, or at the very least, levels off. For example, in the manufacturing sector, opportunities to increase efficiency still exist, but the gains are largely incremental, producing marginally less savings. In the agricultural sector, productivity is growing more slowly than ever before, accompanied by declining soil fertility and crop nutritional value.
This occurs as an unintended consequence of increased efficiency, as energy use and resource depletion actually accelerate due to increased availability and lower costs. On a macro level, most would agree that the linear model cannot continue indefinitely. Which leads us to..
The sustainable model
For many, the sustainable model means focusing on renewable energy and recycling, both of which are rapidly expanding industries. However, both face formidable challenges. We’ve written previously about the ever-increasing amount of total BTUs expended in order to produce a single BTU of renewable energy. And according to Columbia University’s Earth Institute, the global recycling market for plastic alone is projected to grow by $14.74 billion over the next 3–4 years. But recycling is still hampered by cross-contamination, which is why you’re often asked to separate your recyclable items by placing them into separate bins.
Cardboard recycling is a good example of not only the added costs of contamination, but also the losses associated with reductions in both fiber volume and quality during each successive recycling loop. This impacts the recovery rate, which, according to a recent McKinsey report, stands at less than 50% worldwide. Clearly, there’s room for improvement. Japan achieves an average recovery rate of slightly less than 80%. What does Japan know that the rest of the world doesn’t? In fact, much of the knowledge about recycling is highly localized and remains unshared. As a result, too much effort is wasted through unnecessary repetition of trial and error—making it appear an excellent opportunity for applying KM.