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Mobile money to ring changes at AfricaCom

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Mobile money and the way it has enabled African societies to evolve into a wider economic inclusion is one of the main topics that will come under discussion at this year’s upcoming AfricaCom conference in Cape Town.

Mobile Money – or making payments via your cell phone – is becoming the great differentiator in African societies, to such an extent that it has evolved into a tool for wider economic inclusion and social enablement.

In his annual ‘Gates News’ newsletter Microsoft founder, Bill Gates, wrote about the impact that smartphones and mobile banking would have in the next 15 years. He said “digital banking will give the poor more control over their assets and help them transform their lives and by 2030, two billion people who don’t have a bank account today will be storing money and making payment with their phones”.

Sub Saharan Africa currently hosts 52% of all live mobile money deployments worldwide. This statistic clearly shows a significant need for quality mobile financial services within the African – and global – society. It’s this need that has created the huge business opportunity for Mobile Money. A handful for African operators have led the way in addressing these societal needs by developing interoperable services. At the same time they’ve leveraged a broader reach to customers and built a robust business from their mobile money verticals.

Innovations in Tanzania have led the way for interoperability. Operators such as Tigo, Airtel, Zantel, and now Vodacom’s M-Pesa service have initiated a new wave of collaboration between their respective mobile money services.

At AfricaCom 2015, the continent’s largest Telecoms, ICT and tech event, delegates will have the opportunity to engage with expert speakers discussing the key issues embodying the direction and evolution of this pioneering industry.

Adam Thompson, Africa and Middle East, Com World Series Head of Content, said: “High level representatives from all the leading companies in the mobile money business will be speaking at AfricaCom in the Mobile Money stream. Along with all other tier one operators they will be focusing on many themes, including interoperability during the continent’s most focused and relevant meeting for professionals in mobile financial services.”

Discussion topics will included:

Achieving interoperability through mobile financial services

Developing relevant and profitable Mobile Financial Services

Learnings on launching payments via an OTT

Chief regulatory panel – nurturing innovation whilst maintaining regulation

Further dialogue around the interoperability between mobile operators and banking services; mobile money and convergence with traditional merchant payment systems; and the evolution of nano-finance through mobile will also form part of this leading-edge theme.

Thompson said: “If you are a network operator in the mobile money space, a financial institution operating mobile services, or regulator from telecoms or banking sectors, register for your complementary pass to Mobile Money and AfricaCom today. You’ll learn how to reach a broader range of people across multiple regions, while maintaining high service quality. The discussions will share insight on how to launch and scale interoperable mobile money services; identify and share best practices, guidelines and processes while engaging regulatory support.”

AfricaCom, now in its 18th year, brings together senior decision-makers from the entire digital ecosystem, from all over Africa. Last year the conference was attended by 9000 digital movers and shakers, with more than 375 of the worlds most innovative brands showcasing their products and services at the event. 2015 is expected to exceed this number and is anticipated to be the best place on the continent to learn how to engage your customers in an every changing digital market, and make the best of this global marketing trend – the future of marketing.

Speakers at this event will include; Asif Aziz of Expresso Telecom Group, Fredrik Jejdling of Ericsson, Li Peng of Huawei, Willem Hendrickx of Alcatel-Lucent, Dr. Harry Gombachika of Malawi Telecommunications Limited, Mariam Altman of Telkom, Mark Shoebridge of Uganda Telecom, Biola Edun of Etisalat Nigeria, Nic Rudnick of Liquid Telecom, Dominique Baron of Horus Telecom, Sherry Zameer of Gemalto.

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Smart grids needed for Africa’s utilities

Power utilities across Africa should rethink their business models and how they manage and monetise their assets to keep pace with the changing energy ecosystem, says COLIN BEANEY, Global Industry Director for Asset-intensive and Energy and Utilities at IFS.

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Africa’s abundant natural resources and urgent need for power mean that it is one of the most exciting and innovative energy markets in a world that is moving rapidly towards clean, renewable energy sources. The continent’s energy industry is taking new approaches to providing unserved and underserved communities with access to power, with an emphasis on smart technologies and greener energy sources.

Power systems are evolving from centralised, top-down systems as interest in off-grid technology grows among African businesses and consumers. And according to PwC, we will see installed power capacity rise from 2012’s 90GW to 380GW in 2040 in sub-Saharan Africa. Power utilities are needing to rethink their business models and how they manage and monetise their assets to keep pace with the changing energy ecosystem.

Energy and utilities providers are transforming from centralised supply companies to more distributed, bi-directional service providers. They can only achieve this through the evolution of “smart grids” where sensors and smart meters will be able to provide the consumer with a more granular level of detail of power usage. This shift from an energy supplier to “lifestyle provider” will require a much more dynamic and optimised approach to maintenance and field service.

African companies must thus embrace digital transformation as an imperative. This transformation begins by embracing enterprise asset management to improve asset utilisation. The subsequent steps are enhancing upstream and downstream supply chain management; resource optimisation; introducing enterprise operational intelligence; embracing new technologies such as the Internet of Things, machine learning, and predictive maintenance; and becoming a smart utility.

Embracing mobility to drive ROI

Getting it right is about putting in place an enterprise backbone that accommodates asset and project management, multinational languages and currencies, new energies and markets, visualisation of the entire value chain, and mobility apps. Mobile technologies that support the field workforce have a vital role to play in driving better ROI from utilities’ investments in enterprise asset management and enterprise resource planning solutions.

Today’s leading enterprise asset management solutions feature powerful functionality for mobile management of the complete workflow of work orders – from logging status changes and updates, from receiving and creating new orders to concluding the job and reporting time, material and expenses. Such solutions are easy to deploy and intuitive for end users to learn and use.

Importantly for organisations operating in parts of the continent with poor telecoms infrastructure, connectivity is not an issue. The solutions work offline and synchronises when network connectivity is available. Users can work on any device—laptops, tablets, and smartphones—commercial or ruggedised.

By ensuring that field technicians have easy access to information and processes, the mobile solution enables technicians and maintenance engineers to easily do the following tasks:

·         Create a new work order on the fly and log new opportunities

·         Access both historical and planned work information when requested

·         Permit customers to sign when the job is completed

·         Capture measurements and inspection notes on route work orders

·         Create new fault reports on routing

·         Facilitate documentation through photo capturing

·         Provide easy access to technical data and preventive actions.

The power of mobility allows the engineer to be the origin of all data capture on a service event. They can easily inquire on asset history, record parts used or parts needed for repair, record labour hours, and expenses as they occur, and any notes of repairs performed. When coupled with workforce management tools, such solutions unlock significant productivity gains for utilities who are trying to get the most from their workforce and assets.

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How machine learning can save your life

Over 11000 people died during the 2014-2016 Ebola outbreak in West Africa.The virus hopped between Guinea, Leone, Nigeria and Liberia, before making its way to the UK and US. But what would have happened if analysis and machine learning stepped in to help solve the problem, asks ANESHAN RAMALOO of SAS.

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Over 11000 people died during the 2014-2016 Ebola outbreak in West Africa.The virus hopped between Guinea, Leone, Nigeria and Liberia, before making its way to the UK and US. But what would have happened if analysis and machine learning stepped in to help solve the problem, asks ANESHAN RAMALOO of SAS.

But what if we could have predicted the outbreak months before it happened, buying us time to take proactive measures to contain it and curb its spread?

With access to overwhelming volumes of data, the computational power needed to store and analyse this data in real time, and sophisticated algorithms that can find patterns in the data and alert authorities to health problems before they become, well, problems, pandemics don’t have to be as devastating as they have been in the past.

In fact, with advanced data analytics, we can better manage any disease – long-term, short-term or pandemic – resulting in better patient treatment, more efficient use of resources and cost savings.

It’s been done before.

By analysing data from social media, blogs, online forums and keyword searches, we were able to predict the 2012-2013 US flu season three months before the Center for Disease Control (CDC) issued its first official warning.

Imagine the impact if the same analytical power was applied across the entire healthcare spectrum – not only on a national and global level, but right down to the individual level.

Data evolution

In the past, health workers relied on manually intensive, paper-based systems to record infections and deaths during disease outbreaks. Not only was it easy for errors to slip through but because the data was anecdotal and historical, authorities did not get a complete understanding of the reach and impact of the outbreak.

During the Ebola outbreak, the CDC adopted a mobile data collection system that enabled health workers to instantly submit information to a database via text messages. This low-cost method of information gathering not only resulted in fewer errors but also allowed analysts to draw up detailed maps of population movements, which made it easier to understand how the disease was likely to spread, and where to set up treatment centres.

While this was certainly an improvement on the paper-based systems of old, the drawback was that mobile data was historic and did not provide researchers with the ability to track developments and population movements in real time.

Data-driven action

But mobile phones are just one source of data. Today, health authorities can overlay thousands of data sources – including social media, health and physician reports, keyword searches, media reports, transactional data from retailers and pharmacies, airline ticket sales, geospatial data and more – to not only better manage diseases and outbreaks when they do happen, but to see them coming months in advance – and what could happen if we don’t act on the information.

By mining structured and unstructured data, we can track the movements of infected populations and who they come into contact with; we can measure the success of containment policies, education campaigns and treatments – and what to do if they’re not working; we can determine the effect of weather and other environmental factors on the spread of diseases.

Never before have we been able to act on information to save lives, not just during pandemics but through better understanding and treatment of diseases.

Personalised treatment

Until now, standard treatments for diseases such as cancer and HIV have been applied to all patients, regardless of their unique profiles and with little understanding as to why some people respond well to certain treatments and others don’t.

But by analysing and creating ‘medical maps’ of individuals that take into account their anatomy, physiology, DNA, RNA and chemical composition, doctors can prescribe personalised treatments that have a greater chance of success.

There are many other benefits of data analysis in healthcare:

·        Personalised treatment can result in fewer hospital admissions and can produce faster results and better experiences for patients;

·        By better understanding the impact of lifestyle and diet on health, medical aid providers can educate their members with the aim of improving their health, which could result in cost savings for both the provider and the member;

·        Governments can use data to develop proactive approaches to protecting and promoting public health, to prioritise services and to find ways to cut costs so that they can provide healthcare to more citizens.

·        By sharing data and results from clinical trials and combining that data with academic, patient and industry data, medical researchers can better understand the genetics of viruses, why some strains are more deadly than others, and why some people are more resistant to viruses. This could spark innovation and generate new insights that ultimately improve treatment and outcomes.

AI and machine learning

As the use of intelligent algorithms, machine learning and natural language processing becomes more entrenched in advanced data analytics, technology will increasingly supplement the skills of humans to produce faster and more accurate medical diagnoses.

We’re already seeing successful applications of artificial intelligence (AI) in predicting relapse in leukaemia patients and in distinguishing between different types of cancer.

Machine learning can extract valuable insights from unstructured data like clinical notes and academic journals to provide even larger datasets that will transform the medical industry into a proactive front against diseases.

There are plenty of doomsday theories about how machines will supersede our intelligence and rise against us. But there aren’t enough stories about the potential of data analytics, AI and machine learning to supplement human skills and knowledge to drastically changes lives for the better – and even save them. Right now, it’s looking more likely that machines will actually help us to live longer – and I don’t know many people who would object to that.

 

  • ANESHAN RAMALOO, ‎Data Scientist and Senior Business Solutions Manager at SAS.
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