Stratificare are shortlisted as one of the top 4 teams that have reached the finals of the DBS Foundation Social Impact Prize at the Lee Kuan Yew Global Business Plan Competition.
The DBS Foundation Social Impact Prize at the Lee Kuan Yew Global Business Plan Competition (LKYGBPC) will be awarded to the most innovative business plans, start-ups or early-stage ventures that address pertinent urban challenges faced by cities of today.
In addition to the evaluation criteria for the LKYGBPC, qualifying applications for the DBS Foundation Social Impact Prize are also assessed on clear identification of the social or environmental problem, creativity in addressing the identified challenge statement and stakeholders involved, ability to measure the social or environmental impact created and the scalability and sustainability of solution and impact
The award worth SGD 150,000 includes prize money of up to SGD 100,000 and post-competition support, such as:
• Access to DBS Foundation’s capacity building programmes
• Brand awareness and marketing features on DBS Foundation’s website, brand campaigns, media stories etc.
• Use of DBS premises when in Singapore for launch or community events
• Network and connection to DBS Foundation’s social enterprise alumni community and partners
Empowering personalised medicine for tomorrow through innovative diagnostic solutions
OpenGov had the opportunity to speak with Anthony Chua – CEO, Keith Chong -COO and Tiffany Lin -CRO before they has progressed to the finals to hear about their innovative solution to a problem that affects Singaporeans on a daily basis.
StratifiCare™ was founded in 2015 with the vision of empowering personalized medicine for tomorrow through innovative diagnostic solutions. They have been shortlisted for the DBS Foundation Social Impact Prize for their work on the world’s first severe Dengue prediction test.
Keith Chong, COO of Stratificare said that one of the drivers behind this solution was that Dengue was something that affected their personal lives and family. And added that he believed that being able to diagnose whether it was a severe case helped reassure patients that their diagnosis was accurate, and helped with decision-making on what the next clinical steps should be.
StratifiCare has discovered a panel of biomarkers that can determine the progress of Dengue Fever. Patients who are predicted not to progress to severe Dengue can be managed at outpatient settings, instead of bearing expenses being hospitalised.
The challenge in the clinical management of Dengue is how to accurately predict which patients will go on to develop Severe Dengue in the early phase of the disease. Their innovation will help reduce the over-hospitalisation issue faced by medical providers and relieve healthcare burden, especially in poorer Dengue-endemic developing countries.
CEO Anthony Chua said that the challenge was not to solve the problem just in Singapore, but was also a solution for neighbouring countries too. When asked about go-to-market strategy their CRO Tiffany Lin said that Singapore is their main focus at the minute, with plans to distribute into Malaysia and India in the near future.
Stratificare has reached the finals of the DBS Foundation Social Impact Prize which takes place on Friday 9th October.
To register for the awards ceremony please click here
Singapore Land Authority (SLA) has released a fully integrated 3D version of OneMap, Singapore’s authoritative national map. The tool is the certified national map of Singapore which contains the latest and most comprehensive information on Singapore’s landscape. A product of a collaboration between several government agencies, the map’s services are free to access.
The application, OneMap3D, was unveiled at the Singapore Geospatial Festival 2021, where SLA also signed separate memorandums of understanding (MOU) with the country’s logistics and real estate agencies to expand the industry’s use of OneMap.
The latest was created by converting the original format to 3D using open-source 3D geospatial technology and 3D city modelling. Initially, OneMap was first released in 2010, followed by an improved version in 2017 in 2D that included features such as real-time traffic data and an Application Programming Interface (API) for app developers.
It is built on our commitment to enhance our country’s geospatial capabilities and to provide new geospatial solutions for businesses, government and the wider public.
– Singapore’s culture, community and youth minister
OneMap is the country’s digital map service, and it is constantly updated with information from government agencies, such as where citizens can pick up a free face mask. Singapore’s Civil Defence Force also used OneMap to create MyResponder, an app that alerts all trained first responders to cardiac arrests in the area. The new OneMap3D upgrade will allow citizens to navigate through a neighbourhood in the first-person view, simulating what a route would look like in person.
As reported by OpenGov Asia, Geospatial Technology involves the use of technology for collecting and utilising geographic information. Some of these technologies include Geographic Information System (GIS), GPS, remote sensing, and geofencing.
On the prevalence of the use of geospatial information in Singapore, organisations such as Grab manipulate this data to be able to match drivers with passengers, in real-time. There is already an everyday use of geospatial technology with the likes of GPS for navigating around. It provides location-based services such as:
- Bus explorer: for information on bus routes and arrival timing
- Landquery: Finding out land ownership and land lot information
- Schoolquery: Searching for primary schools which are located within a 1-2 km radius from a location
- Trafficquery: Live traffic information, cameras, ERP gantries and availability of parking lots
SLA Chief Executive says the MOUs with the logistics and real estate agencies are part of SLA’s efforts to collaborate with industry leaders to promote growth and opportunities through geospatial solutions.
SLA’s MOU with the property or real estate company in the real estate space will result in the development of new feature data collection and customised Application Programming Interface (API) to improve the property company’s applications and OneMap geospatial information. As per the company’s CEO, the collaboration has the potential to be a “game-changer” in the real estate industry.
In contrast, the parties will collaborate on geospatial co-innovations to improve hyperlocal and granular data at the street level for last-mile delivery under SLA’s MOU with Singapore’s logistics company. “We are delighted to be SLA’s first express logistics partner for GeoWorks,” says the CEO of the logistics firm.
He went on to say that by having the company’s drivers contribute pictorial information to enable OneMap’s accuracy and data volume, the company could potentially set a new industry operational standard by improving the entire last-mile delivery process.
The SLA and homegrown robotics and automation solution company MOU will see the trial of automated data capture with robots, limiting the time and effort from manual data capture, to develop geospatial innovation in the area of robotics and automation solutions. This collaboration will also allow SLA and the company to develop standards for robotics-ready maps and map information interoperability for compatibility across multiple platforms.
Most aspects of everyday lives as consumers or employees have been embedded by Artificial Intelligence (AI) based systems. The further advancement and increased diffusion of AI capabilities pose risks of job replacement and even concerns of what this all means in terms of being human. Singapore Management University’s (SMU)Business Partnerships unit and International Trading Institute delved into the issue of “Working with AI-Enabled Smart Machines”.
University professors and thought leaders documented 30 examples of people doing their everyday work in real-world business settings in partnership with AI-enabled smart machines. These case studies will be used in their co-authored book The Future of Work Now: People Collaborating with Smart Machines.
The case studies covered a range of industry settings including insurance and financial services, knowledge work across other service sector industries, healthcare, factory floor production, and field operations across multiple industries.
One example cited was from one of Singapore’s banks who had massive migration to data analytics starting in 2010 and their follow-on progression into using machine learning. The system was able to draw on the bank’s existing data sources and external data to evaluate the probability of fraud or financial crime.
Before using this new system, the majority of the time spent by the bank employees who were doing transaction surveillance was on data amalgamation and sorting through the alerts generated by the prior generation of rule-based systems. The latter is an earlier type of AI application, with most of these alerts being false alarms.
With the new machine-learning-based system analysing and evaluating the rule-based alerts, the transaction surveillance employees can now focus directly on the alerts identified by the system as having a high or medium probability of being an actual problem.
The employee’s work time is allocated more efficiently, as they no longer need to look at large numbers of false alarms. Additionally, they no longer need to manually amalgamate all the supporting information use to evaluate each alarm as that background data access and integration work was automated as part of the machine learning application.
Another case study was on Southeast Asia’s largest e-commerce platform. They are a digital-native born company whose business is based on AI-enabled data analytics. The case study highlighted the role of their product managers. These are the people who orchestrate the complex process of developing, phasing in and scaling new Shopee e-commerce platform capabilities and feature enhancements.
The product manager’s challenge is to do this in a way that meets business goals, satisfies customer needs, deals with the constraints and problems faced by the technology teams developing the new AI-enabled capabilities and features, and addresses the many conflicting requirements and trade-offs that arise.
The case study highlighted that while product managers are overseeing the processes of bringing AI-enabled capabilities and features of the platform to market, the nature of their role is so multi-faceted and complex that very few of their engagement management, negotiation, coordination, and decision-making tasks can be automated by these same type of AI capabilities. This product manager example illustrates one of the important ways in which human roles are required to manage the implementation of AI-based change efforts within a complex company setting.
The threat is not about AI taking away human jobs. The real threat is when people choose not to team with AI. Organisations need to learn how to capitalise on what AI can do, go beyond just thinking about simple labour displacement and manpower cost savings, and find ways to use the technology to create value in ways that lead to new demand and correspondingly to new employment opportunities.
As reported by OpenGov Asia, AI is becoming more sophisticated at doing what humans do, but more efficiently, quickly, and cheaply. Scientists from Singapore’s Nanyang Technological University (NTU) and clinicians from Tan Tock Seng Hospital (TTSH) have used artificial intelligence to create a new method of screening for glaucoma.
The central banks of India and Singapore plan to link their digital payments systems to enable instant, low-cost fund transfers. The two sides will connect India’s Unified Payments Interface (UPI) and Singapore’s PayNow in a major push to disrupt the cross-border transactions between the two nations that amount to over US$1 billion each year.
The move is targeted for operationalisation by July 2022, both nation’s central banks said earlier this week. Users on either of the systems will be able to make transactions with one another without having to sign up to the second platform. When implemented, fund transfers can be made from India to Singapore using mobile phone numbers, and from Singapore to India using UPI virtual payment addresses (VPA). The experience of making a PayNow transfer to a UPI VPA will be similar to that of a domestic transfer to a PayNow VPA, noted the Monetary Authority of Singapore in a press statement.
UPI is an instant real-time payment system that facilitates inter-bank transactions developed by the National Payment Corporation of India (NPCI). It has become the most popular way users in India transfer money to one another and to businesses, a news report stated. The system, adopted by scores of local and global firms, is now processing over 3 billion transactions each month. Singapore’s PayNow also enables peer-to-peer funds transfer service, available to retail customers through participating banks and non-bank financial institutions (NFIs). It allows users to send and receive instant funds from one bank or e-wallet account to another in Singapore by using just their mobile number, Singapore NRIC/FIN, or VPA.
The Reserve Bank of India, the country’s central bank, described the project as a significant milestone in the development of infrastructure for cross-border payments between India and Singapore. It noted that the linkage closely aligns with the G20’s financial inclusion priorities of driving faster, cheaper, and more transparent cross-border payments. The linkage builds upon the earlier efforts of NPCI International Private Limited (NIPL) and the Network for Electronic Transfers (NETS) to foster the cross-border interoperability of payments using cards and QR codes, between India and Singapore. It will further anchor trade, travel, and remittance flow between the two countries.
Earlier in August, India’s Prime Minister, Narendra Modi, launched a new digital payment system called e-RUPI. It is a QR code or SMS string-based e-voucher, which is delivered to the mobile of the beneficiaries. The users of this seamless one-time payment mechanism will be able to redeem the voucher without a card, digital payments app, or Internet banking access at the service provider. Any government agency and corporation can generate e-RUPI vouchers via their partner banks.
As OpenGov Asia reported, the e-RUPI initiative will be one of the programmes launched over the next few years to limit touchpoints between the government and the beneficiary and ensure that the benefits reach their intended beneficiaries in a targeted and leak-proof manner. The vouchers are person- and purpose-specific, which means that if they are released by the government COVID-19 vaccinations, for instance, then they can be redeemed only for that. It also ensures that the payment to the service provider is made only after the transaction is completed. Being pre-paid in nature, it assures timely payment to the service provider without the involvement of any intermediary. E-RUPI is expected to be a revolutionary initiative for ensuring a leak-proof delivery of welfare services.
By increasing government expenditure on healthcare and rapidly increasing demand for innovative medical technologies, Singapore medical devices market is expected to grow quickly, according to a leading analytic company.
Singapore aims to provide smart healthcare to people with the help of novel technologies, which is helping the country to withstand the impact of COVID-19 on its healthcare system. This report reveals that the Singapore healthcare market is a strongly growing market in the Asia-Pacific region, with a focus on health technology and research and development.
Telemedicine, electronic health records, patient solutions, medical diagnostics, health management solutions, personal health and fitness, and medical education are some of the areas where technology plays a major role.
The report reveals that government initiatives such as Diagnostics Development (DxD) Initiative and the Smart Nation initiative will support the increased demand for medical devices by the rapidly ageing population to drive the market in Singapore.
Singapore’s public and private healthcare expenditure, which accounts for about 5.3% of GDP in 2020, is expected to exceed 8.5% in 2030. This increase can be attributed to the Singapore government’s focus on raising the healthcare expenditure driven by the growing consumption of healthcare services by the general population.
Medical Devices Analyst stated that the Research, Innovation and Enterprise Plan (RIE2025), launched by the Singaporean government, holds a budget of around US$19bn with ‘Human Health and Potential’ as one of the major areas of focus. The plan is expected to strengthen the medical devices industry in the country.
To keep up with advances in biomedical science and encourage the development of new clinical treatments, The Ministry of Health, in partnership with Agency for Science, Technology and Research (A*STAR) and other governmental bodies, have increased their focus on investing in clinical and translational research.
Singapore provides universal health coverage to citizens and permanent residents. Almost 80% of the healthcare cost is subsidised by the government. Polyclinics in Singapore are also adopting new technologies such as virtual systems, and this is making healthcare delivery more accessible and affordable, especially during the pandemic.
Using a virtual system, the attending nurse enters the details of the patient’s medical condition, and the computer algorithm in the device will recommend required tests and consultation with specialists at the National Heart Centre, Singapore. This will provide faster service to patients while eliminating incidental costs that accompany hospital visits, and help the physician attend to more patients each day.
Adherence to the ASEAN Medical Device Directive’s (AMDD) basic policies is expected to be followed by all ASEAN countries in the next few years. The AMDD system for registering and assessing medical devices requires ASEAN countries to follow uniform classification criteria for medical devices. This will provide medical device companies with a common market of more than 600 million people.
There has been an obvious and significant rise in the development and deployment of transformational technologies in the healthcare system during the pandemic in Singapore, and this demonstrates the commitment of the country in achieving its aim of providing technology-driven healthcare solutions to its citizens
As reported by OpenGov Asia, Digital Monitoring Solution is one of the examples of Singapore’s innovation in medical devices. The Digital Monitoring Solution is an affordable and fully integrated smart health platform comprising a tamper-proof smart wearable, mobile app, geofence locator, remote monitoring dashboard and automatic alerts.
The solution provides a holistic 360-degree view for round-the-clock monitoring and detailed record logs of a seafarer’s well-being, combining key vitals tracking (temperature, heart rate, SPO2, activity level and sleep patterns), highly accurate indoor geofencing with automated geofence quarantine monitoring and health symptoms monitoring. It analyses and triangulates information collected and can detect abnormalities and assess risks.
The complexity and rise of data in healthcare mean that artificial intelligence (AI) will increasingly be applied within the field. Several types of AI tools are already being used by patients and providers of care, as well as life sciences companies. Diagnoses and treatment recommendations, patient engagement and adherence and administrative activities are the most common types of applications. Although there are many cases where AI can perform healthcare tasks as well as or better than humans, implementation issues will prevent large-scale automation of healthcare professional jobs for a long time.
AI is becoming more sophisticated at doing what humans do, but more efficiently, quickly, and cheaply. Both AI and robotics have enormous potential in healthcare. AI and robotics are increasingly becoming a part of the healthcare ecosystem, just as they are in daily life.
Scientists from Singapore’s Nanyang Technological University (NTU) and clinicians from Tan Tock Seng Hospital (TTSH) have used artificial intelligence to create a new method of screening for glaucoma. According to a joint news release from NTU and TTSH, the disease is the leading cause of irreversible blindness worldwide, affecting 76 million people by 2020.
The AI-enabled method developed by NTU and TTSH employs algorithms to distinguish normal optic nerves from those with glaucoma. This is accomplished by analysing “stereo fundus images,” which are multi-angle two-dimensional (2D) retinal images that are combined to form a three-dimensional (3D) image.
The AI method had a 97% accuracy in diagnosing glaucoma when tested on stereo fundus images from TTSH patients undergoing expert examination, according to the institutions. The new screening method developed by NTU and TTSH employs a set of algorithms to analyse stereo fundus images captured as pairs by two cameras from different perspectives.
Using two images ensures that if one image is of poor quality, the other image can “usually compensate” and the system can maintain its accuracy, according to the researchers. As per the researchers, the automated glaucoma diagnosis method could be used in less developed areas where patients do not have access to ophthalmologists.
“A portable AI-powered tool, which we envision our screening model to eventually take the form of, could also help to tackle the problem of poor access to primary healthcare and errors in differential diagnoses,” said a doctor who heads the glaucoma service at the National Healthcare Group Eye Institute at TTSH.
The team is now testing their algorithms on a larger dataset of patient fundus images taken at TTSH. They are also “looking at how the software can be ported to a mobile phone application so that, when used in conjunction with a fundus camera or lens adaptor for mobile phones, it could be a feasible glaucoma screening tool in the field,” NTU and TTSH said.
OpenGov Asia reported, even as Singapore and much of the world is turning the corner on the pandemic, it is driving the adoption of transformative technologies in healthcare. In the last year, it was the intense and unrelenting pressures of the pandemic that ultimately proved to be the most potent agent of change for digital transformation in healthcare.
The necessary elements of this transformation—the required infrastructure—are rapidly coming to maturity. It starts with the increasing availability of health data from connected devices. It is unleashed by the increasing sophistication of technologies like Artificial Intelligence (AI), hybrid cloud and automation.
An autonomous vehicle (AV) glides along a road at low speed, its movement seemingly independent. It gradually accelerates, while cameras and sensors installed around it are primed to signal alerts when obstacles are nearby.
A one-stop command centre called a Robot Operating System (ROS) dictates the AV’s movements. The ROS is a collection of tools and libraries which simplifies the task of designing, testing and implementing complex and robust robotics applications. As a middleware, it enables connectivity between multiple front and back end applications. In this case, it allows engineers to send ‘messages’ to the AV to toggle parameters like speed, camera angle and range of sensors.
While ROS is more commonly deployed as an advanced industry tool, students at the Singapore Institute of Technology (SIT) have been getting their feet wet by operating the software. With robots becoming increasingly commonplace in healthcare, manufacturing, food preparation and the military, ROS has also been growing in popularity. This prompted SIT to introduce ROS as a learning aid for students.
Theoretical classes are combined with one-hour practical lab sessions, which familiarise students with robotics technology and how it can be used in robotic platforms and design. The classes also better prepare second-year Mechatronics Systems and third-year Computer Engineering students for advanced subjects in university, and when they enter the workforce.
We use ROS to spark students’ interest in robot applications, as well as broaden their understanding of electronic components and how complex robotic systems work. There is a high demand for engineers who can develop ROS applications, so we want to encourage students to discover more about the real-world applications of the software.
– Senior Professional Officer
The hands-on approach involves designing complex systems using simulations, then implementing them on an actual robot or electric AV. Students first explore the simulation platform enabled through ROS, where they can synchronise different sensors, motors and cameras to enable functionalities such as mapping, localisation, navigation and visualisation. Once simulated testing is completed, students deploy the actual action on the robot or AV.
One lesson would entail students testing how camera visuals will appear indoor and the effect on camera visibility. In another class on motors, students would change code on the command to control the speed of the motor. Build up an understanding of robotics-related hardware takes an entire trimester.
Once students have a firm grasp of what makes up a robotics system, they will then embark on a one-and-a-half-hour lab session during their final class to learn how ROS glues everything together. The challenge in using ROS is being able to have an overview of the entire platform and how it can be used to design a product, instead of getting caught up in individual components.
As reported by OpenGov Asia, Robots have the potential to transform policing in the same way that they will change healthcare, manufacturing and the military. It is plausible that some police robots in the future will be artificially intelligent machines capable of using legitimate coercive force against humans. Police robots may reduce the risks to officers by removing them from potentially dangerous situations. Those suspected of committing crimes may also face less harm if robots can help police conduct safer detentions, arrests and searches.
To address this, two robots will be patrolling the Toa Payoh Central neighbourhood in Singapore as part of a three-week trial as of 5 September, looking for errant smokers, unlicensed hawkers, motorbikes and e-scooter riders on sidewalks and gatherings that exceed the current group size limits.
The robots are designed to alert public officers in real-time to these offences since they will be equipped with cameras that have a 360-degree field of vision and can see in the dark. They will also be able to broadcast and show warnings warning people about the dangers of such behaviour.
The development, integration and adoption of information management and governance frameworks are a necessity, especially in an era where the quality of data collected is more important than ever. As information is a strategic asset, governments need to protect, leverage and analyse both structured and unstructured information to better serve and meet mission requirements.
Public sector leaders need to lay the groundwork to correlate dependencies across events, people, processes and information to establish data-driven organisations to accomplish their mission. This is why creating effective information and data governance strategies, policies and frameworks to drive the quality, accuracy and availability of insights are essential.
With recent advancements in data analytics, business intelligence, Machine Learning and Artificial Intelligence, governments can better predict and anticipate problems more accurately rather than react to them.
While this is not new, the difference today is the regularity, accuracy and consistency delivered made available with the current power of analytics. Massive data sets, millions of pages of unstructured text and information stored across silos and borders can now be analysed to identify patterns, forecast trends and mitigate problems.
Data analytics allows governments to see the bigger picture – understand where to increase efficiencies, cut waste, improve policies and monitor budgets.
Public sector agencies are working to radically improve their operations and services – driving the need to structure, collect and store data that will improve analysis and offer better actionable insights. Therefore, there has never been a more important time for data collaboration and a single source of truth.
The Singapore public sector has been leading the charge in digital transformation and data analytics in the region. The nation has developed new infrastructure to digitally industrialise the management, governance and use of data to support and scale data transformation initiatives.
In the world of data democratisation, breaking down information silos is the first step toward user empowerment. This can only be done with reliable analytics tools capable of desegregating and connecting previously siloed data, making it manageable from a single place. Governments need to be more intuitive to sense and respond to new technology opportunities that could drive digital transformation in times of constant change.
HyperIntelligence – a relatively recent concept – is about making data available to the staff to ensure convenience, access and safety. Considered the future of Data Analytics, it relies on trusted sources and personalising information for specific roles within the company. The future of Data Analytics is to provide critical data insights for specific keywords on all web applications.
To effectively leverage data insights to deliver citizen-centric services, data and analytics are crucial for government agencies. While it cannot be used to solve every challenge in society today, it is a great step in the right direction.
This was the focal point of the OpenGov Breakfast Insight on 10 September 2021 – a closed-door, invitation-only, interactive session with Singapore’s top government agencies. This session aimed to provide the latest information on how government agencies can use data analytics to drive mission outcomes.
Finding Partners to Leverage Data Analytics
To kickstart the session, Mohit Sagar, Group Managing Director and Editor-in-Chief at OpenGov Asia delivered the opening address.
Data on a global scale has taken on an entirely different dimension and Singapore is no different. In fact, compared to other countries in the region, the nation is well ahead of the curve and leads in data analytics. The public sector has spent huge amount of money on technological innovations.
While Singapore collects massive amounts of data, quantity alone is not enough to make informed decisions. Where, how and when is critical as is how the data is structured and made uniform. For better and more relevant data, information silos need to be broken down. Democratisation, integration and sharing will all be key to bettering citizen services and enhancing citizen experience.
To democratise data, the public sector needs to empower its entire workforce – from top to bottom. For the most part, data is often only accessible to people in higher positions or specific departments, creating disparity and lacunae. The information gap must be bridged with appropriate empowerment – be it through awareness, training or skill up-gradation.
Access to large data sets is essential for a government’s digital transformation journey. Of course, data in and of itself is not the end goal – data must serve as a tool to derive understanding that enables effective decision making. Actionable insights from analytics will ultimately enrich the citizen experience.
In closing, Mohit emphasised the importance of partnerships that could help leverage data analytics for an organisation. By working with the right people, a company can accelerate its digital journey towards effective digital transformation.
Global State of Enterprise Analytics
Kyung-Whu Chung, Director, Sales Engineering, APAC, MicroStrategy spoke next of the criticality of quality of data in digital transformation. To set the context, Kyung Whu revealed that a recent survey showed that 94% of respondents say that Data and Analytics are important to their business growth and digital transformation. While this may be obvious, it bears more elaboration and explanation.
There are huge benefits for organisations to use data analytics, including improved efficiency and productivity. Better data analytics leads to faster and more effective decision-making and, ultimately, results in better financial performance. Data analytics also assist organisations to identify and create new promising products and services.
While benefits are clear internally, there are advantages for the consumer as well. Customer satisfaction and experience are both critical for a company to thrive was the key. Data analytics help better understand consumer behaviour, trends, demands and also identify issues. It has improved customer acquisition and retention with enhanced customer experience.
Contrarily, the same survey showed that only 21% of potential business users are using data. The vast majority (97%) of real-time decisions are data deprived. This indicates, surprisingly, that organisations and agencies are still relying on their intuition and manual analysis to solve complex problems with multiple variables.
Barriers that limit the uptake of analytics have been well articulated. Kyung-Whu identified the top three concerns – data and privacy concerns, limited access to analytics and lack of talent and training.
On the issue of privacy, 38% of organisations said more than 50% of their data is certified by an organisation authority or adheres to corporate policies. Despite this, customers are concerned about their sensitive and personal data. Organisations need to build trust and communicate properly on the use of data responsibly. This will encourage customers to be more inclined to provide their information.
When it comes to access, data-driven culture often gets stuck at the top. Access to the organisation’s data and analytics is usually concentrated on specific roles. Democratising data is important as it empowers all departments and encourages data-driven decisions at all levels throughout the company.
The last challenge that organisations need to tackle is the lack of talent and training. While simple enough to understand, there needs to be a more intentional drive and strategy to reskill and upskill employees.
In closing, Kyung-Whu encouraged delegates to expanded their thinking and embrace a multi-tool environment. A data-driven culture can only be built on data democratisation, enabling everyone to access every process and every app. Collecting data is only a start, organisations need to enrich the data to gain deeper insights.
Health AI Strategy
Delegates then heard from Sutowo Wong, Director, Analytics and Information Management Division, Ministry of Health, Singapore who elaborated on the AI strategy and use cases in the nation’s health division.
Sutowo acknowledged as the nation shaped its health AI strategy, it needed to be mindful of the external macro trends. One such trend is the democratisation of data and analytics. Self-service analytics and the rising demand for data visualisation requires a better user experience for both data and insights.
The next trend was the rise of analytics apps. Role-based actionable insights needed to be more easily consumed and deployed. Moreover, the ability to support decision making is still the most significant challenge to realising value from investments in analytics.
Singapore’s health AI strategy is aligned with the national AI strategy – a vision that is committed to making Singapore a leader in developing and deploying scalable, impactful AI solutions in key sectors of high value and relevance to citizens and businesses states by 2030.
Specifically, the vision in the health field is to transform and enhance policy decision making, delivery of care and patient outcomes as well as internal operations through the development and deployment of scalable AI solutions in the healthcare sector.
To achieve the vision, the government has developed a strategy and framework for health, identified and driven impactful and feasible AI use cases that could be scaled across the healthcare system, and leveraged ecosystem enablers for AI in the health sector.
Sutowo shared the example of the self-learning retinal screening tech as a successful use case of deploying AI in healthcare. Singapore Eye LEsionN Analyser (SELENA+) is a deep learning system jointly developed by the Singapore National Eye Centre (SNEC) and the National University of Singapore (NUS) that can cut the time needed to screen for Diabetic Retinopathy (DR). SELENA+’s capabilities in analysing retinal images could be extended to a predictive risk assessment model for cardiovascular diseases.
Another use case is AI in the health grand challenge, JARVIS. The initiative aims to help primary care teams stop or slow disease progression and complication development in Diabetes, Hypertension and hyperLipidemia (DHL) patients by 20% in 5 years.
Singapore is upskilling talent based on the whole government analytics competency framework. In the end, Sutowo believes, that beyond AI, the rapid growth in digital health presented opportunities to redefine Singapore care and financing models.
After the informative presentations, delegates participated in interactive discussions facilitated by polling questions. This session is designed to provide live-audience interaction, promote engagement, hear real-life experiences and impart professional learning and development for the participants. It is an opportunity for delegates to gain insight from subject matter experts, share their stories and take back strategies that can be implemented in their organisations.
The opening poll inquired about the main challenge delegates face in their data strategy journey. Almost half (47%) chose a lack of data culture/literacy/skill across employees as their primary challenge. A little less than one-third (32%) thought that missing an overall strategy that crosses departments and teams is their biggest obstacle. Data privacy and security concerns are the biggest challenges for 16% of delegates while 5 % chose a lack of a centralised tool for sharing and collaboration.
The second question inquired about the best option to overcome the people challenge. Again, almost half (44%) believed that their best choice is to increase data literacy by providing education and certification programs. A quarter chose the leadership team to mandate all employees to use the analytic tool as their best option while 19% opted to improve the current process for business users to get instant data. About a tenth (12%) indicated that providing employees with a self-service analytic tool would be their best option.
On being asked about what their business users do when they have new data requirements, almost two-thirds (65%) approached the IT department directly for support. While almost a quarter (23%) went by their gut feeling, 12% opted to raise a Helpdesk ticket.
The next question was about their agency’s biggest data management barrier. Delegates were equally divided (26%) between data collection and data accessibility and sharing. A little more than one-fifth (21%) identified data accuracy – providing a single source of truth – as their main barrier. While 16% chose real-time insights, about 11% went with regulatory compliance.
Delegates were asked what their agency is doing to manage their data management challenges. Almost half (48%) chose a combination between working with current service providers for better efficiencies, and sourcing for service providers to bridge the gap. A third chose to work with current service providers to improve efficiencies and maintain costs. Almost a fifth (19% ) chose to source for service providers to bridge the gap, alongside existing vendors.
On being queried about how many systems their agency store its data, almost three quarters (71%) employed over 10 systems. One-fifth (20%) used 2-4 systems while 10 % had between 5-9 systems.
The next poll asked which applications delegates spend most of their working days. A majority (70%) spent their time with email while a quarter often used productivity applications (like Microsoft Office).
Asked about whether delegates have considered zero-click experience for data, almost two-thirds (68%) have not considered it while a third (32%) have.
The final issue asked delegates’ top data strategy priority in the next 2 years. Well over half (60%) prioritised data sharing to generate insights across agencies boundaries to equip decision-makers with information needed to execute operations better and plan for future contingencies. The remaining delegates were equally split (20%) between prioritising to empower staff with meaningful data insights to drive decisions and to accelerate legacy modernisation to improve resilience and agility.
The Breakfast Insight concluded with remarks from Kyung-Whu Chung who highlighted the role of data analytics and the need for agencies to begin leveraging it. He urged agencies to become data-driven and advised them to accelerate their digital transformation.
In closing, he invited the delegates to reach out to his team to explore ways they could work together to assist them on their journey.