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The ABC of GDPR for SA

SA companies doing business with EU customers need to consider making changes to their data privacy and oversight processes to conform to new regulations being implemented next year.

South African companies doing business with European Union (EU) customers need to consider making changes to their data privacy, technology and oversight processes in the wake of new privacy rules. On 25 May 2018 new privacy rules formed by the EU will be implemented. The General Data Protection Regulation (GDPR) will replace the Data Protection Directive 95/46/EC.

The new rules will apply to the ‘processing’ of ‘personal data’ by “controllers” and “processors” based in the EU, as well as those located outside of the EU if they provide services and goods to EU customers. The GDPR will also apply to all organisations processing and holding personal data of subjects residing within the EU.

“The GDPR will impact many South African and other organisations across the African continent,” Busisiwe Mathe, Risk Assurance Cyber and Privacy leader, PwC Southern Africa says. “Businesses that do not comply with the GDPR face a potential of up to 4% fine of global revenues, increasing the need for organisations to plan for and implement necessary changes to demonstrate good in the eyes of individuals and regulators.”

South African organisations are awaiting the Protection of Personal Information Act (POPIA). The POPIA is likely to be fully enacted in South Africa in early 2019 and comments on POPIA draft regulations closed on 7 November 2017.

Once POPIA is fully enacted, responsible parties and operators in South Africa, processing personal information will have to comply with POPIA as well as potentially having to comply with the GDPR. The GDPR was introduced by the EU more than a year ago and organisations have been given less than two years to comply with them.

POPIA is South Africa’s first piece of comprehensive data protection legislation. It aims to give effect to the constitutional right to privacy by introducing measures whereby personal information processed by organisations is fair, responsible and conducted in a secure manner.

Mathe adds: “Compliance with POPIA will be a challenge for many organisations. The POPIA compliance journey will require organisations to consider many features within their organisation and strategic vision.” The GDPR and POPIA have many commonalities but also a number of differences, one of the most significant being that POPIA includes “juristic” (business) entities in the definition of personal information – this will significantly increase the scope of personal information and provide additional challenges to comply with POPIA.

“After May next year, EU companies that deal with SA can only do so if POPIA is in place or if the SA companies can satisfy their EU partner that they have adequate rules and policies in place regarding data protection.”

Rav Hayer, Financial Services GDPR Lead, PwC UK adds: “Organisations will have to provide clarity on how customer data is collected and stored. Any breaches of data must be communicated within 72 hours to the responsible regulator, wherever the breech occurred and the subjects reside. ”

The GDPR penalties can be up to 4% of an organisation’s global annual turnover whereas POPIA has a maximum R10 million fine or time behind bars.  GDPR penalties are much higher than POPIA. The GDPR penalties stand to hurt companies more financially than POPIA if they ignore them. The reputational damage and loss of customer trust are however important business imperatives to comply with POPIA regardless of the significantly lower fines.

In a recent survey conducted by PwC, nearly all of the respondents (92%) considered compliance with the GDPR a top priority on their data-privacy and security agenda in 2017 – with over half of respondents saying it is “the” top priority and 38% saying it is “among” top priorities. The GDPR Preparedness Pulse Survey examines preparedness and why companies are willing to spend $1 million or more on GDPR readiness plans.

PwC surveyed 300 Chief Privacy Officer, Chief Information Officers, General Counsels, Chief Compliance Officers, and CEOs in US, UK, and Japanese companies about their GDPR programmes.

Only 8% of UK companies have finished all their preparations compared to 22% of US companies. “This is likely to be because the US‘s data privacy regulation is currently a lot more stringent than the UK. In the past the ICO hasn’t been as firm as US regulators as our data privacy law isn’t currently enforceable,” Hayer adds.

While many organisations have already begun this process with a range of compliance efforts, many are still in the assessment phase. But despite their status in preparing to comply with the new regulations, most US Companies are already planning to invest in GDPR. According to survey respondents, over three in four (77%) companies plan to allocate $1 million or more on GDPR readiness and compliance efforts – with 68% saying they will invest between $1 million and $10 million and 9% expecting to spend over $10 million to address GDPR obligations.

Survey results also found that information security enhancement is a top GDPR initiative. While much of the discussion has focused on the law’s privacy-centric requirements, information-security obligations figure prominently in GDPR plans of US companies. Among the 71% who have begun GDPR preparation, the most-cited initiatives in flight are information security, privacy policies, GDPR gap assessment and data discovery.

What should you focus on if you haven’t started your GDPR programme?

PwC found that 5% of UK companies have not started preparing for the GDPR. With less than seven (7) months until the compliance deadline, these organisations risk regulator fines, litigation costs, and lost contract opportunities.

The biggest risk for organisations is likely to be third parties, so it is essential that organisations check that their third party contracts are GDPR compliant, Hayer comments.

How much can organisations expect to spend on their GDPR programme?

Of those companies that have completed their GDPR programme, 40% of US, UK and Japan reported spending more than $10 million. The pattern of increased spending was consistent regardless of company size.

Driving competitor advantage – The GDPR and investor relations

The survey found that some companies see their GDPR programs as a potential differentiator in the market. Among companies who believe they have finished their GDPR programmes, 38% have engaged their investor relations departments, an indicator that they hope to highlight early compliance to help drive competitive advantage.  These companies should also look to extend this confidence out to their customers to strengthen customer trust in their business and also test their position in advance of the GDPR going live.

“The ‘compliance journey’ involves innumerable challenges and the task is complicated. Entities may find that they have difficult choices to make about their priorities moving forward. Making changes to ensure compliance with the GDPR will require considerable resource investments and lots of planning,” concludes Hayer.

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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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