The rise in the satisfaction level between its service providers and constituents is the foundation for Singapore’s reputation as an innovative nation. The strategic use of data-centric tools across agencies considerably improves service delivery but, at the same time, also presents difficulties.

There is no denying that data science and analytics have the power to fundamentally change and reinvent how people live, work, and connect with each other. As a result, the quest to advance data collecting, analysis, and automation processes is an ongoing one.

Additionally, there is a growing demand for analytics automation to create flexible, trustworthy datasets that give information to decision-makers and facilitate transformation. Actionable intelligence obtained from such platforms is crucial for providing people, the community and employees with services.

Senior digital executives from the Singapore public sector attended the OpenGov Breakfast Insight on 6 July 2022 to explore scaling analytics across the government.

The Human Impact of Democratising Data

To kickstart the session, Mohit Sagar, CEO and Editor-in-Chief, OpenGov Asia, delivered the opening address. He understands that the reliance on dedicated data professionals and experts can be reduced if every employee is equipped with data skills.

Inter-agency cooperation on technological solutions to social problems creates the possibility for every person to turn data into insights going forward, “Democratising data means upskilling our data workers.”

This “democratisation” means giving people direct access to data and analytics that can help them make decisions. If everyone in an organisation uses the information in the data, both the business and its employees can make better decisions every day. This leads to stronger people and better financial results.

With access to data that can be used, the organisation can make smart business decisions at all the important points in an employee’s life.

The use of tools that allow data workers with a range of expertise and data talents to freely contribute to analytic capabilities is known as “democratising analytics.” Such upskilling is an excellent investment that will pay off generously in the long run.

When balanced solutions are available, developing in-house domain experts need not be difficult or time-consuming.

Data must be seen as more than just a component in the governance system. Effective leadership must consider the limitations placed on data experts working with finite resources like time and efficiency.

By giving public sector workers a platform for various activities, bottlenecks can be eliminated and they are empowered to provide services that are centred on people.

True digital transformation is welcomed when agencies adopt a new mentality and accept the necessity for transformation. In this scenario, the goal of improving the data collection, analysis and automation processes is continuous. Moreover, a secure data capability must be maintained to make room for high-impact performance and solutions.

When data and analytics are used effectively, public organisations and their missions can serve as catalysts for a greater and brighter future. Internal progress is ushered through upskilling when democratised analytics are leveraged consistently and without unnecessary complexity.

Driving Data and Analytics Maturity

Online portals with public access make it possible for public entities to share data. Not only can developers easily cooperate on digital solutions to societal problems, but every individual possesses the capacity to transform data into actionable insights.

“To imagine quicker answers, deeper insights and better judgement, every stakeholder in the public sector needs to participate more creatively,” says Lim Yew Beng, Head, Value Engineering (APJ), Alteryx.

Yew Beng shared the study conducted by Alteryx which shows that the four key dimensions of Asia-Pacific’s readiness for analytics maturity – strategy, data, workforce and process – reflect the organisation’s capacity to derive value from its data and analytics.

The strategy dimension examines the beginning points of transformation. The interdependencies among stakeholders in charge of various initiatives will become a barrier to getting consistent returns from analytics investments without a thoroughly thought-out data and analytics strategy.

Data dimension, on the other hand, examines where changes happen more quickly. How data, the raw material, is consistently regulated throughout the organisation has a significant impact on the rate of acceleration.

Examining the areas where significant support is given to improvements falls under the purview of the workforce dimension. The goal of productivity tools and automation is always to enable and empower individuals so they can complete their tasks more effectively, more quickly and with less effort.

Dealing with the scale of change is taken care of by the process dimension. To enhance analytics process management takes three phases – definition, standardisation and automation.

Meanwhile, existing systems, including software, data retrieval and inter-agency distribution, enable government organisations of any size to collaborate and expedite analytic procedures. The insights required for local growth and community uplift are simplified and mechanised to provide results that may be utilised by everyone.

Yew Beng emphasised that “It is important that we are shifting to the more digital economy. The speed and precision of secure, compliant, and regulated public sector technology in the form of AI, analytics, and machine learning is another solution.”

The government sector must encourage openness while also increasing the visibility of how money is allocated. Through analytics and by using experience, the data gathered from their customers, employees, and vendors can help improve government services and promote innovation.

On the other hand, staff may now concentrate on higher-value, more strategic tasks that call for human intervention and intelligence due to automation.

However, the persistent reliance on manual processes can be a result of the lack of fresh options. Organisations might not be able to scale their procurement operations or address issues with transparency and sustainability without a reliable procurement platform.

While concentrating on the readiness criteria pertinent to business analytics is crucial, it is vital to examine other readiness aspects for business analytics and ensure that financial and technological resources are sufficient.

In the context of analytics, organisations should take four critical preparation considerations into account: operational, cultural, domain and strategic readiness. For organisations implementing analytics, ensuring readiness across all elements is crucial because several of them may eventually evolve into crucial success factors for analytics. Spending on analytics and other IT-driven projects are not significantly different from one another. For success, it is crucial to link organisational strategy and analytics.

Yew Beng shared four tips to easily adapt the analytics in an organisation:

• Make analytics Easy: Execute every task in minutes or hours, not days and weeks
• Cover Everything: From insight to action across every data type and source​
• Be​ Everywhere: Insights across hundreds of use cases, on-prem and in the cloud​
• Enable Everyone: Democratised analytics for every person, every skill level​

The willingness to invest in analytics is a sign of strategic readiness, but only if this investment is supported by a solid business rationale. The process of strategically preparing comprises establishing goals for analytics, problems the organisation expects to solve through analytics, and the kind of urgent questions that can or cannot be answered.

In closing, Yew Beng mentioned that Alteryx answers the question of how data science and analytics will change business. It all started with the idea of making a software platform that helps businesses feel the excitement of getting answers faster.

Bridging the Analytics Divide: ​Reflections as a Healthcare & Analytics Practitioner

The deployment of tools that enable data workers of varying skill levels and data talents to independently contribute to analytic capabilities constitutes democratising analytics. Such skill development is the ideal investment, yielding great returns over time. Creating in-house domain specialists does not have to be difficult or time-consuming when balanced solutions are available.

“Every employee must make a concerted effort to improve their data processing and analytical skills. If every employee has data skills, the organisation will undoubtedly profit,” says Dr Joshua Lam, Data Architect (Data Operations & Architecture, Chief Data Officer’s Office), Health Promotion Board, Singapore.

Dr Lam shared that as the key agency overseeing national health promotion and disease prevention programmes, the Health Promotion Board (HPB) aims to empower Singaporeans to attain optimal health, increase the quality and years of healthy life and prevent illness, disability and premature death.

HPB adopts a combination of strategic approaches to encourage healthy behaviours among the population and build a sustainable ecosystem for healthy living.

• Combining broad-based and targeted interventions in key settings
• Fostering meaningful partnerships across whole-of-society
• Leveraging policies and regulatory measures to shift lifestyle choices
• Public education to increase awareness, sustain mindshare and nudge health behaviours
• Harnessing technology and data for greater precision in understanding behaviours and delivering interventions

Dr Lam emphasised the importance of digital knowledge and systems gaps in analytics for digital transformation given the impact of technology on society and the rapid pace of innovations with no precedence in the past.

A person’s capacity to locate, assess, and create understandable information using digital technology is referred to as having “digital literacy,” a broad notion. One of the few core skills that are not taught in schools is digital literacy, which is essential for success in areas like communication and the job market.

Both in developed and developing nations, there is a painfully significant problem with the lack of computer literacy. The COVID-19 problem provided the clearest example yet of how technology is affecting the country in ways that have never been seen before in human history.

Rapid improvements in AI, robotics and other new technologies are happening in shorter cycles. This is changing the nature of the jobs that need to be done and the skills that are needed to do them faster than ever before.

According to Dr Lam, Healthcare is a unique niche market since there is so much data. For example, healthcare data analysts assist organisations in raising patient satisfaction, reducing healthcare costs and improving the quality of care.

As businesses seek to benefit from big data and its many applications, including how it may be used to improve healthcare quality, their role has grown more crucial. Hence, the healthcare sector needs executives who have a thorough awareness of the difficulties being encountered as well as the capacity to comprehend data and apply it.

Data silos obstruct corporate operations and the initiatives that support them in data analytics. Executives’ capacity to use data to manage corporate operations and make wise business decisions is constrained by silos.

As new jobs are created and skill requirements change, the current pool of skilled workers won’t be able to keep up with demand. “To democratise data across silos for utilisation to unearth new business insights, leadership support and data literacy are essential.”

Companies will need to provide a path for their staff to achieve data literacy, which includes understanding why data literacy is important, what data literacy looks like for each employee, and how to set a baseline for employee competencies and a common data language. 

Interactive Discussion

After the informative talks, delegates took part in discussions based on polls. This event is meant to give live audience interaction, encourage participation, give people real-world experiences, and help them learn and grow professionally.

On how delegates rank the usage of data and data analytics tools for decision-making in their organisation, a majority answered that they use data in the decision-making process, but the analysis is primarily a manual process. Others felt that they have some tools in place or need improvement by having better tools to analyse. Data-driven decision-making is an excellent method for gaining a competitive advantage, increasing profits, and lowering costs.

Regarding the biggest data challenge in their organisation, the delegates answered that adding new data sources is difficult and time-consuming. Companies can collect and analyse massive amounts of data and unlock unprecedented potential. Big data challenges include finding the best way to deal with a lot of data, which means storing and analysing a huge amount of information in different data stores. When working with Big Data, many big problems need to be solved quickly. Some delegates felt that efforts to manage data are expensive or data is manually aggregated to produce BI/reports for executive leadership.

On what was the greatest barrier to integrating more data and analytics into their day-to-day decision-making, most indicated that it was limited access to data. Data that cannot be directly shared with the general research community due to potential risks to study participants and the confidentiality agreements made with them are referred to as restricted data. The datasets may require expensive and time-consuming access. Others went to compliance with data security and privacy requirements, or available data is not accurate.

When asked what their organisation’s main driver for using data and analytics was, a majority agreed to improve the speed and accuracy of business decisions. Organisations are under more and more pressure from the competition to not just attract customers, but also comprehend their needs to improve the customer experience and forge enduring partnerships. Some participants said their main driver was achieving better customer experience and improved capability to upsell/cross-sell the product portfolio.

On the biggest barrier to progress in their organisation’s data journey, a majority opted for the disconnection between IT & business as customers expect businesses to know them, establish meaningful connections, and deliver a seamless experience across all contact points in exchange for providing their data and granting relaxed privacy in its use. Other delegates answered the non-data-literate workforce.

In the last poll, the delegates were asked about how well their organisation used data and analytics. In general, delegates felt that they distribute static reports regularly. Analytics is a system that helps people make decisions every day and, in some cases, makes decisions for them.

Some organisations don’t need to “convince” key stakeholders to use analytics when making decisions. On the other hand, some organisations face strong opposition, which is often a sign of the culture or the readiness of the organisation. Of the remainder, some said that they utilise performance dashboards to slice, dice and drill down, as well as combine predictive modelling, AI, and machine learning techniques. They have incorporated visualisation into their process and transactional systems.

Conclusion

According to Mohit, government agencies can collaborate and streamline analytical processes thanks to existing systems including software, data retrieval, and inter-agency dissemination. To provide results that everyone can use, the insights necessary for local growth and community uplift are streamlined and automated.

Secure data capabilities must be maintained to make room for high-impact performance and solutions in Singapore. True digital transformation is welcomed when agencies adopt a new mentality and accept the necessity for transformation.

Alteryx helps data analysts, business leaders, IT professionals and data scientists get deeper insights faster and more efficiently than they ever thought possible. Likewise, Alteryx Advocacy has a network of innovative stars who are motivated by a visionary data mission which is categorised into two – Alteryx Innovator and Alteryx Visionary.

An Innovator is an Alteryx customer who loves to learn new things, hears about business problems, and builds workflows in their head to solve them. Innovators love to talk about what they’ve learned and help others get better at analytics.

A Visionary, on the other hand, is an Alteryx customer who oversees their line of business or enterprise’s data and analytics strategy. Visionaries think about the future with foresight and the knowledge that the power of self-service analytics is the key to business growth and sustainability in the future.

In conclusion, Yew Beng highlighted that through data science and analytics, organisations especially the government, have changed the way their business is done and “working together for the economy is very important.”