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Prepare to go predictive

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In our current digital age, insights into AI applications like machine learning can help businesses deliver ‘big value’ from their data. With this innovation, are South African businesses optimising their data resources, asks FRANS CRONJE.

In our current digital age, insights into Artificial Intelligence (AI) applications like machine learning can help businesses target the right customers and deliver ‘big value’ from their data. With this innovation at our fingertips the question arises, are South African businesses optimising their data resources?

It is important to consider why companies started collecting data.

Historically, data has been collected to report back upon either for legal requirements such as fulfilling Audit requirements, or for their own internal monitoring purposes. This legacy still influences many companies in what data they collect and how they store it. The result is that much of the data held by companies is not ready for predictive modelling and machine learning.

Subsequently, it should not be surprising that much of the innovation in predictive analytics and machine learning is driven from younger companies that were built when cell phones, laptops and easy access to the internet were commonplace.

An important consideration when it comes to data is the wide range of opportunities it enables, particularly for service-related industries which can use it to identify consumer preferences and, in turn, help in detecting where products or services can be improved. Almost every industry can benefit from compiling and building data from the education, transportation and consumer products sectors, to businesses in electricity, oil and gas, healthcare and consumer finance like banking and insurance.

Ultimately, instead of relying on intuition, companies who handle their data correctly can embrace predictive decision-making approaches, which – when coupled with automation – can provide cost savings as well as profit gains.

So how can businesses get the most out of their data? Considering data from the predictive point of view can help businesses realise how to improve their data management. When taking this perspective, it is easy to identify the veracity of system log data is really valuable or overwriting data to provide a current snapshot of the data can mean the data is no longer valuable for predictive modelling.

The problem and solution should take the company’s unique environment and challenges into account. How fast does a result need to be returned, where does the data arrive from and at what frequency?

We prefer co-location modes of consulting with our clients which helps us understand each client’s domain and allows us to create a solution that can be delivered relatively quickly through a small team.

In terms of whether or not such capabilities can – or should – be out-sourced or developed internally, many organisations simply do not have the internal skills to implement machine learning applications. However, there have been developments locally to address this gap.

DataProphet is one of several collaborators involved in the design of the Postgraduate Diploma in Data Analytics and Business Intelligence which will be offered by the Faculty of Economic and Management Sciences at the University of the Western Cape from January 2017.

  • Frans Cronje, Managing Director for DataProphet.

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UN calls for electronics overhaul to beat e-waste

Seven UN entities have come together at the World Economic Forum to tackle the escalating scourge of electronic waste.

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Seven UN entities have come together, supported by the World Economic Forum, and the World Business Council for Sustainable Development (WBCSD) to call for an overhaul of the current electronics system, with the aim of supporting international efforts to address e-waste challenges. 

The report calls for a systematic collaboration with major brands, small and medium-sized enterprises (SMEs), academia, trade unions, civil society and associations in a deliberative process to reorient the system and reduce the waste of resources each year with a value greater than the GDP of most countries. 

Each year, approximately 50 million tonnes of electronic and electrical waste (e-waste) are discarded — the weight of more than all commercial airliners ever made. In terms of material value, this is worth 62.5 billion dollars– more than the GDP of most countries.  

Less than 20% of this is recycled formally. Informally, millions of people worldwide (over 600,000 in China alone) work to dispose of e-waste, much of it done in working conditions harmful to both health and the environment. 

The report, “A New Circular Vision for Electronics – Time for a Global Reboot,” launched in Davos 24 January, says technologies such as cloud computing and the Internet of Things (IoT), support gradual “dematerialization” of the electronics industry.  

Meanwhile, to capture the global value of materials in the e-waste and create global circular value chains, the report also points to the use of new technology to create service business models, better product tracking and manufacturer or retailer take-back programs.  

The report notes that material efficiency, recycling infrastructure and scaling up the volume and quality of recycled materials to meet the needs of electronics supply chains will all be essential for future production.  

And if the electronics sector is supported with the right policy mix and managed in the right way, it could lead to the creation of millions of decent jobs worldwide. 

The joint report calls for collaboration with multinationals, SMEs, entrepreneurs, academia, trade unions, civil society and associations to create a circular economy for electronics where waste is designed out, the environmental impact is reduced and decent work is created for millions. 

The new report supports the work of the E-waste Coalition, which includes: 

  • International Labour Organization (ILO); 
  • International Telecommunication Union (ITU); 
  • United Nations Environment Programme (UN Environment); 
  • United Nations Industrial Development Organization (UNIDO); 
  • United Nations Institute for Training and Research (UNITAR); 
  • United Nations University (UNU), and 
  • Secretariats of the Basel and Stockholm Conventions (BRS). 

The Coalition is supported by the World Business Council for Sustainable Development (WBCSD) and the World Economic Forum and coordinated by the Secretariat of the Environment Management Group (EMG).  

Considerable work is being done on the ground. For example, in order to grasp the opportunity of the circular economy, today the Nigerian Government, the Global Environment Facility (GEF) and UN Environment announce a 2 million dollar investment to kick off the formal e-waste recycling industry in Nigeria. The new investment will leverage over 13 million dollars in additional financing from the private sector.   

According to the International Labour Organization, in Nigeria up 100,000 people work in the informal e-waste sector. This investment will help to create a system which formalizes these workers, giving them safe and decent employment while capturing the latent value in Nigeria’s 500,000 tonnes of e-waste. 

UNIDO collaborates with a large number of organizations on e-waste projects, including UNU, ILO, ITU, and WHO, as well as various other partners, such as Dell and the International Solid Waste Association (ISWA). In the Latin American and Caribbean region, a UNIDO e-waste project, co-funded by GEF, seeks to support sustainable economic and social growth in 13 countries. From upgrading e-waste recycling facilities, to helping to establish national e-waste management strategies, the initiative adopts a circular economy approach, whilst enhancing regional cooperation. 

Another Platform for Accelerating the Circular Economy (PACE) report launched today by the World Economic Forum, with support from Accenture Strategy, outlines a future in which Fourth Industrial Revolution technologies provide a tool to achieve a circular economy efficiently and effectively, and where all physical materials are accompanied by a digital dataset (like a passport or fingerprint for materials), creating an ‘internet of materials.’ PACE is a collaboration mechanism and project accelerator hosted by the World Economic Forum which brings together 50 leaders from business, government and international organizations to collaborate in moving towards the circular economy. 

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Matrics must prepare for AI

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students writing a test

By Vian Chinner, CEO and founder of Xineoh.

Many in the matric class of 2018 are currently weighing up their options for the future. With the country’s high unemployment rate casting a shadow on their opportunities, these future jobseekers have been encouraged to look into which skills are required by the market, tailoring their occupational training to align with demand and thereby improving their chances of finding a job, writes Vian Chinner – a South African innovator, data scientist and CEO of the machine learning company specialising in consumer behaviour prediction, Xineoh.

With rapid innovation and development in the field of artificial intelligence (AI), all careers – including high-demand professions like engineers, teachers and electricians – will look significantly different in the years to come.

Notably, the third wave of internet connectivity, whereby our physical world begins to merge with that of the internet, is upon us. This is evident in how widespread AI is being implemented across industries as well as in our homes with the use of automation solutions and bots like Siri, Google Assistant, Alexa and Microsoft’s Cortana. So much data is collected from the physical world every day and AI makes sense of it all.

Not only do new industries related to technology like AI open new career paths, such as those specialising in data science, but it will also modify those which already exist. 

So, what should matriculants be considering when deciding what route to take?

For highly academic individuals, who are exceptionally strong in mathematics, data science is definitely the way to go. There is, and will continue to be, massive demand internationally as well as locally, with Element-AI noting that there are only between 0 and 100 data scientists in South Africa, with the true number being closer to 0.

In terms of getting a foot in the door to become a successful data scientist, practical experience, working with an AI-focused business, is essential. Students should consider getting an internship while they are studying or going straight into an internship, learning on the job and taking specialist online courses from institutions like Stanford University and MIT as they go.

This career path is, however, limited to the highly academic and mathematically gifted, but the technology is inevitably going to overlap with all other professions and so, those who are looking to begin their careers should take note of which skills will be in demand in future, versus which will be made redundant by AI.

In the next few years, technicians who are able to install and maintain new technology will be highly sought after. On the other hand, many entry level jobs will likely be taken care of by AI – from the slicing and dicing currently done by assistant chefs, to the laying of bricks by labourers in the building sector.

As a rule, students should be looking at the skills required for the job one step up from an entry level position and working towards developing these. Those training to be journalists, for instance, should work towards the skill level of an editor and a bookkeeping trainee, the role of financial consultant.

This also means that new workforce entrants should be prepared to walk into a more demanding role, with more responsibility, than perhaps previously anticipated and that the country’s education and training system should adapt to the shift in required skills.

The matric classes of 2018 have completed their schooling in the information age and we should be equipping them, and future generations, for the future market – AI is central to this.

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