Whilst the need for growth is accepted as a way of reducing social inequality and improving the chances of a dignified and socially inclusive society, we cannot continue to do that in a way driven by the need for ever more acquisitions of goods. That method is an inherently wasteful use of resources, and skewed towards over consumption in more developed countries. There has to be better, more inclusive ways of growing, and I suggest that one could be through the Circular Economy, which involves resources and capital goods reentering the system for reuse instead of being discarded, thus saving on production costs, promotes recycling, decreases waste, and enhances social performance.
When CE models are combined with IoT, internet connected devices that gather and relay data to central computers, efficiency skyrockets. Because finite resource are depleting, the future economy is destined to become more circular. The economic shift toward CE will undoubtedly be hastened by the already ubiquitous presence of IoT, its profitability, and the positive public response it yields.
Unlike the linear economy which is a “take, make, dispose” model, the circular economy is an industrial economy that increases resource productivity with the intention of reducing waste and pollution. The main value drivers of CE are (1) extending asset use cycle lengths (2) increasing asset utilization (3) looping/cascading assets through additional use cycles and (4) regeneration of nutrients to the biosphere.
The Internet of Things is the inter-networking of physical devices through electronics and sensors which are used to collect and exchange data. The main value drivers of IoT are the ability to define (1) location (2) condition and (3) availability of the assets they monitor. By 2020 there are expected to be at least 20 million IoT connected devices worldwide.
The nexus between CE’s and IoT’s values drivers greatly enhances CE. If an institution’s goals are profitability and conservation, IoT enables those goals with data big data and analysis. By automatically and remotely monitoring the efficiency of a resource during harvesting, production, and at the end of its use cycle, all parts of the value chain can become more efficient.
When examining the value chain as a whole, the greatest uses for IoT is at its end. One way by which this is accomplished is through reverse logistics. Once the time comes for a user to discard their asset, IoT can aid in the retrieval of the asset so that it can be recycled into its components. With efficient reverse logistics, goods gain a second life, less biological nutrients are extracted from the environment, and the looping/cascading of assets is enabled.
One way to change the traditional value chain is the IoT enabled leasing model. Instead of selling an expensive appliance or a vehicle, manufacturers can produce them for leasing. By embedding these assets with IoT manufacturers can monitor the asset’s condition; thereby dynamically repairing the assets at optimal times. In theory the quality of the asset will improve, since it is in the producer’s best interests to make it durable rather than replaceable.
Many sectors are already benefiting from IoT in resource conservation. In the energy sector, Barcelona has reduced its power grid energy consumption by 33%, while GE has begun using “smart” power meters that reduce customers power bills 10-20%. GE has also automated their wind turbines and solar panels; thereby automatically adjusting to the wind and angle of the sun. In the built environment, cities like Hong Kong have implemented IoT monitoring for preventative maintenance of transportation infrastructure, while Rio de Janeiro monitors traffic patterns and crime at their central operations center.
Despite the many advantages there are numerous current limitations. Due to difficulty in legislating for new technologies, Governmental regulation lags behind innovation. For example, because Brazil, China, and Russia do not have legal standards to distinguish re-manufactured products from used ones, cross-border reverse supply-chains are blocked. Reverse supply chains are also hurt by current lack of consumer demand , which is caused by low residual value of returned products. IoT technology itself generates major privacy concerns. Questions arise like: who owns this data collected? How reliable are IoT dependent systems? How vulnerable to hackers are these assets? Despite the prevalence of IoT today, with 73% of companies invest in big data analytics, most of that data is merely used to detect and control anomalies and IoT remains vastly underutilized. Take an oil rig for example, it may have 30,000 sensors, but only 1% of them are examined. Underutilization of IoT in 2013 cost businesses an estimated 544 billion alone.
Even with these current barriers, because of the potential profits and increased social performance, the future implementation of an IoT enhanced CE is bright. As government regulation catches up and technology improves, recycling and conservation will become more profitable and reverse supply chains can proliferate. When the ownership of collected data is finally clearly defined by laws, then the interoperability of IoT data can take hold to increase its efficiency. Estimates are that the potential profits from institutions adopting CE models could decrease costs by 20%, along with significant waste reduction.
Problems can be, and need to be, overcome, once the need for a more inclusive and fairer solution becomes the imperative, and the old capitalist model is reimagined into something that gains buy in through all societies, such that institutions gain long term benefits and regain much of the trust they have lost in their quest for narrow gains. Corporate life needs to be much more win-win and much less a zero sum game to ensure its, and societal, long term survival.
About the author:
Mark Esposito is a socio-economic strategist and bestselling author, researching MegaTrends, Business Model Innovations and Competitiveness. He works at the interface between Business, Technology and Government and co-founded Nexus FrontierTech, an Artificial Intelligence Studio.