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Tips for banks to reach all ages in Africa

DEWALD NOLTE, VP Business at Entersekt, offers some tips on how African banks can attract and retain customers, despite their age to ensure they are preparing for future generational expectations.  

As mobile internet connectivity grows, African youth are fast embracing the opportunity to connect, converse and transact on the web.

According to the GSMA (Mobile Economy Report 2015), mobile internet penetration in Sub-Saharan Africa was expected to reach 38% by 2020. This has largely been driven by lower costs of smartphones, which the GSMA says have decreased by 20% since 2008. A rapidly growing local app market and easy access to games and social media have captivated the youth market.

Although the Millennials generation is a Western construct, African youth (18 to 34) – particularly the urban youth – are displaying similar online behaviour patterns to their counterparts in developed countries. And, while the older generations may accuse them of being driven by a need for instant gratification, the youth’s expectation of simple, fast and always-on service is shifting how organisations design their offerings.

Banks, meanwhile, have built their credibility by portraying themselves as the bastions of the economy, institutions designed to protect your money, with caution built into their organisational DNA. While this is important, of course, it isn’t something that necessarily attracts their fastest growing potential customer base.

Here are five pointers to help African banks attract and retain customers, no matter what their age, and to ensure they are preparing for future generational expectations.

1. Prepare to be compared

At the very outset, it’s important for banking institutions to understand that the younger generations are swiftly getting used to having information at their fingertips.

Research published by Pew Research Centre (2015 Global Attitudes Survey) shows that African youth are jumping at the opportunity to engage online. In Tanzania, those aged between 18 and 34 are 17% more connected to the internet than their elders. This climbs to a significant 31% in both Nigeria and Kenya. The research also shows that the connected youth are active on social media on a daily basis.

Social media is being used to ask questions and to make comparisons based on experience. Price comparison websites are also making it easier to make informed decisions.

This significantly changes the dynamic of how the youth choose products and interact with brands. It is obvious then, that banks will need to change the way they engage with the younger generation.  Designing for a frictionless experience must be priority.

2. Just make it work

User experience becomes a key issue when servicing customers across generations.

Based on their engagement with global sites, the connected youth have an expectation that everything must work immediately, offer real value, in a seamless experience.

While the younger generations have a better understanding of technology, continued literacy challenges and multiple regional dialect demographics adds complexity to the user interface served up by financial institutions. Complex security terms such as phishing and pharming can cause mistrust of the service. In many instances, this lack of understanding may lead to customers avoiding digital channels altogether, which in turn drives up the cost of delivery for the banks.

Making use of technology that appears exceptionally simple to the user takes away the fear factor. When it comes to authentication, banks must guarantee their customers’ protection against phishing and other digital fraud vectors without the costly and clumsy use of one-time passwords. These may give the appearance of good security, but they are less effective and overly complicated, particularly for those accessing services on their phones. Removing complexities at the very outset of the transaction resonates with both the older and younger generations.

3. No one reads anymore 

No generational cohort reads lengthy warnings or instructions. People will click through to the end of an instalment or process without actually being fully aware of the details – or this may again increase their mistrust of the service. Moreover, in our experience, when an organisation uses text-heavy instructions, abandonment rates shoot up. When communicating instructions, the “keep it simple” rule reigns supreme.

4. Markets are not the same

Companies also need to understand that new markets work very differently. What may have worked in Botswana, may not be obvious to those in Kenya. People use and engage with technology, language and each other differently in every market. This includes generational quirks.

Banks will need to tweak their user engagement depending on where they are operating. Working with partners who have experience in a region allows a bank to learn from their experiences, which can save time and costly mistakes.

5. Innovating for future generations

We see a lot written about banks becoming simple transaction pipes. To avoid this, they must adapt in order to provide better value for their customers.  This can be achieved in three ways:

  1. A simple user authentication, which has excellent security, is a great way to build trust with customers.
  1. Once this is in place, you can confidently open up your channels and add new services.
  1. Banks can then begin leveraging their merchant network in order to start on-selling their products to their customers – essentially becoming an aggregated merchant platform. By nurturing trust, banks are able to capitalise on a captive customer base and bring to bear vast economies of scale.

The complexities of catering across borders and language barriers and for different generations with different user expectations are enormous. However, if banks invest in technologies that are simple, seamless and flexible, they can not only ensure all age groups form trusting, lasting relationships with them, but also take an important step towards building new revenue opportunities for the future.

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Now IBM’s Watson joins IoT revolution in agriculture

Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production

IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.

By 2050, the world will need to feed two billion more people without an increase in arable land [1]. IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.

Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”

New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.

Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.” 

The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 [2]. Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.

The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.

Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.

IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.

The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.

[1] The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”

[2] Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10


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What if Amazon used AI to take on factories?

By ANTONY BOURNE, IFS Global Industry Director for Manufacturing

Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.

At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.

If Amazon did factories

If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.

Manufacturing with knowledge

Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.

In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.

As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.

Knowledge for manufacturing

For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.

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