Artificial intelligence (AI) refers to the ability of machines to exhibit humanlike intelligence—for example, the ability to solve a problem without requiring detailed, human-developed software. By reviewing voluminous data sets for patterns, machines can “learn” to perform tasks, such as identifying images, recognising speech, identifying relevant information in texts, synthesising information, drawing conclusions, and forecasting. As AI’s capabilities have dramatically expanded, so has its utility in a growing number of fields.
There is no universally agreed-upon definition of what constitutes AI. The field is advancing rapidly, and developers often mix and match existing technologies to solve specific problems. The term “AI” therefore covers a broad range of technologies and applications, some of which are extensions of earlier techniques (such as machine learning) and others that are wholly new. In fact, there is no generally accepted theory of “intelligence”, and the definition of artificial intelligence changes as people become accustomed to previous advances. While there is disagreement about where to draw the boundaries in this field, there is broad consensus on one thing: AI is the next wave of digital disruption
Artificial intelligence (AI) was first taught in Thailand at government universities more than 30 years ago. Thai-language lecture notes on artificial intelligence (AI) were used in 1975 for teaching an AI course at a university. In 1992 the first AI laboratory was established at the Department of Computer Engineering, Kasetsart University. Research on Thai language processing and expert systems was then concentrated on at the laboratory.
By the 2000s, the AI industry began to develop rapidly. Instruments for storing, processing, and accessing knowledge were needed, giving AI research a great chance to become embedded in Thailand’s national development plan. For instance, this included natural language processing systems for extracting and coding data from unstructured text, algorithms for data mining and knowledge discovery, ontologies and the semantic web, and knowledge service development.
In the early 2010s, the AI industry in Thailand took off and there were many different practical implications of it in the Thai economy including the “Knowledge Engineering and Agricultural Cyber Brain”. Cyber-Brain a community-based platform of services and tools that facilitates IT infrastructure consolidation, information sharing, and collaboration across agencies, partners, and public boundaries. This platform operates to avoid IT duplication between agencies and facilitates integration of IT resources within the federal government and among federal, state, and local governments. With Cyber-Brain, appropriate and personalized knowledge services will be provided to support problem solving, decision making, and early warning.
Since the world population will increase from 7 to 9 billion by 2050, more food will be needed to meet demand. In Thailand, rice is the national food staple and represents the main income sustaining farmers (66 percent of 5.7 million agricultural households are rice farmers). The CyberBrain, as a platform of community knowledge sharing and delivering services in the agricultural domain (especially rice), has been implemented for evaluating nontechnical interoperability and harvesting the best practices for knowledge society development.
Due to the nature and success of the various initiatives being undertaken by the Thai Government to incorporate AI into their National Development Plans, Thailand remains optimistic when it comes to the future of the AI
Today, as a result of collaborations among universities, private organizations, and the government sector, the number of cutting-edge applications for various public services is growing, as evident in Smart Health, Smart Education, Smart Tourism, Smart Energy, Smart Home, and Smart Agriculture. It is a good sign that the Ministry of Information and Communication Technology has seen the importance of integrated service innovation leading to the development of Smart Government and better quality of life for Thai people as a whole.
The Hong Kong Government is carrying out the preparatory work to clearly define the cyber security obligations of critical infrastructure operators through legislation, to strengthen the cyber security of this infrastructure in Hong Kong.
The Secretary for Innovation & Technology made the remarks in the Legislative Council recently, saying that a public consultation exercise is expected to be launched by the end of this year. He emphasised that critical infrastructure is of great significance to the normal operation of society. If information systems, networks or computer systems are disrupted or sabotaged, the operation of major facilities may be affected and this will seriously jeopardise the economy, people’s livelihood, public safety and even national security.
Noting that the increase in cyberattacks in recent years has brought substantial challenges to the cyber security of critical infrastructure around the world, the official noted that Hong Kong does not have specific legal requirements on the cyber security of such infrastructure.
Therefore, in addition to industry best practices as well as guidelines and requirements on cyber security imposed by individual regulatory authorities, the Government is making preparations to clearly define the cyber security obligations of critical infrastructure operators through legislation to enhance the cyber security of critical infrastructure in the city.
It will also refer to the cyber security standards adopted worldwide and by other jurisdictions in formulating relevant standards. The government emphasised that it has been closely monitoring the trends of cyber attacks and the associated security threats around the globe.
The Office of the Government Chief Information Officer has formulated a comprehensive set of Government IT Security Policy & Guidelines which are reviewed and updated regularly. All bureaus and departments must strictly abide by the policy and guidelines to ensure the security of government data and information systems. Moreover, government websites and systems have adopted multiple layers of security measures to detect, block and tackle different types of security threats.
The Secretary for Innovation & Technology made further comments in the Legislative Council meeting and stated that in the past five years, the current-term Government has unprecedentedly invested over $150 billion to support I&T development. Various initiatives are gradually taking effect, and the overall I&T ecosystem is becoming more vibrant. For example, the gross domestic expenditure on research and development (R&D) has increased by more than 45 per cent in the past five years; the number of start-ups rose from around 1 500 in 2015 to around 4 000 in 2021; the venture capital investment substantially increased from $3.4 billion to over $40 billion during the period. The region also saw the establishment of over 10 unicorns in the same period.
In the 2021 Policy Address and 2022-23 Budget, the Government has put forward several future-focused and groundbreaking initiatives. In terms of land supply, having regard to the continuous increase in Hong Kong’s demand for land dedicated to scientific research and advanced industries, the Government is continuing to increase infrastructure, including consolidating the Hong Kong-Shenzhen Innovation and Technology Park (HSITP) in the Lok Ma Chau Loop and the areas around Lok Ma Chau/San Tin to form the San Tin Technopole, building landmark I&T facilities with a scale comparable to Cyberport in Lau Fau Shan, reviving the Ma Liu Shui reclamation project, planning for the construction of the second Advanced Manufacturing Centre, etc.
In this way, the HKSAR Government is working to boost various I&T infrastructures across the region in a bid to future-proof Hong Kong.
Researchers from the Brookhaven National Laboratory of the US Department of Energy have developed a novel machine learning (ML) framework that can pinpoint which phases of a multistep chemical reaction can be adjusted to boost productivity.
The method could aid in the development of catalysts, which are chemical “dealmakers” that speed up reactions. It was created to investigate the conversion of carbon monoxide (CO) to methanol using a copper-based catalyst.
The reaction is made up of seven relatively simple elementary steps and was used as an example by the researchers in their ML framework method. The goal was to determine which elementary step or subset of steps in the reaction network controls the catalytic activity.
Traditionally, researchers attempting to improve such a reaction would calculate how changing each activation barrier one at a time might affect the overall production rate. This type of analysis could determine which steps were “rate-limiting” and which steps determined reaction selectivity—that is, whether the reactants proceeded to the desired product or via an alternate pathway to an undesirable by-product.
The new machine learning framework is intended to improve these estimates so that scientists can more accurately predict how catalysts will affect reaction mechanisms and chemical output. The scientists began by collecting data to train their machine learning model. The data set was created using “density functional theory” (DFT) calculations of the activation energy required to transform one atom arrangement to the next over the course of the reaction’s seven steps.
The scientists then used computer simulations to see what would happen if they changed all seven activation barriers at the same time – some going up, some going down, some individually, and come in pairs.
They generated a comprehensive dataset of 500 data points by simulating variations in 28 “descriptors,” which included the activation energies for the seven steps as well as pairs of steps changing two at a time. This dataset forecasted how individual and pairwise tweaks would affect methanol production. The model then ranked the 28 descriptors in terms of their significance in driving methanol output.
The scientists retrained the ML model using only the six “active” descriptors after identifying the important descriptors. Based solely on DFT calculations for those six parameters, this improved ML model was able to predict catalytic activity.
The model, according to the team, can also be used to screen catalysts. The model predicts a maximum methanol production rate if it can design a catalyst that improves the value of the six active descriptors.
When the researchers compared their model predictions to the experimental performance of their catalyst—as well as the performance of alloys of various metals with copper—the predictions matched the experimental findings. Comparisons of the ML approach to the previous method for predicting alloy performance revealed that the ML method was far superior.
The data also revealed a lot about how changes in energy barriers might affect the reaction mechanism. The interaction of the various steps of the reaction was of particular interest—and importance. For example, the data showed that lowering the energy barrier in the rate-limiting step alone would not improve methanol production in some cases. However, increasing methanol output by adjusting the energy barrier of a step earlier in the reaction network while keeping the activation energy of the rate-limiting step within an ideal range.
The NSW Government announced that it is investing AU$ 2.4 million in a partnership with two Sydney Universities aimed at supporting regional councils to reap the benefits of smart cities technology. In partnership with local councils, the Smart Places Acceleration Program continues to deliver smart technological capabilities to fix problems that people are facing every day.
The Minister for Local Government stated that said 91 regional councils in NSW could benefit from the Smart Regional Spaces: Ready, Set, Go! partnership with the University of Sydney and UNSW Sydney under the Smart Places Strategy launch. She noted that this innovative partnership with regional councils, the University of Sydney and UNSW will see them connect with industry experts, and empower investment in new technology and data-driven solutions to help address the substantial divide in digital inclusion between Australians living in rural and urban areas.
The Minister stated that examples of smart place initiatives include smart street lighting, real-time bus schedules available on digital screens or through apps, using smart sensors to gather waste management data or smart sensors installed on parking spaces.
Minister for Customer Service and Digital Government noted that digital uplift and inclusion is a key pillar of the Smart Places Strategy, especially making sure regional communities can take advantage of emerging smart technology.
The Dean of the Sydney School of Architecture, Design and Planning at the University of Sydney said smart technology was ready to be expanded into the state’s regional communities. Smart technology solutions in transport, communications and energy efficiency are already a reality in metropolitan cities and there is an incredible opportunity to bring more of these initiatives into our rural and regional areas.
The Dean of the Faculty of Arts, Design and Architecture at UNSW said the project is an example of the University’s commitment to transforming the lives of people in regional communities, with the Smart Places movement offering social, economic and environmentally sustainable advantages. She added that many of the ideas generated by this movement to date relate to the challenges of dense urban living that do not necessarily translate to regional spatial scales, assets and geographically dispersed communities, and why a tailored regional focus is so important.
The Smart Regional Spaces: Ready, Set, Go!, is funded through the Digital Restart Fund under the Smart Places Acceleration Program and expertise and contributions from UNSW and the University of Sydney.
About the Smart Places Strategy
Building on Government’s long term planning frameworks, the Smart Places Strategy will enhance existing economic and technological strategies by streamlining policy and plans across all levels of Government in NSW. The NSW Government will play an important role in ensuring its customers realise the full benefits Smart Places have to offer.
- setting legislation, policies and guidelines for place owners, industry and government agencies to consistently roll out smart initiatives;
- creating partnership structures and governance models across local, state and commonwealth governments and the private sector to maximise investment in smart initiatives; and,
- direct investment to support market acceleration and to address market failure so that no one is left behind.
The Smart Places Strategy aligns with and brings together the outcomes sought within the NSW Government’s metropolitan and regional infrastructure, economic, land use and digital strategies. This helps achieve their overall liveability objectives in regional and metropolitan places.
The Ministry of Communication and Information Technology of Indonesia’s most recent initiative is the Digital Technology 4.0 Adoption Programme for MSMEs, which is a long-term assistance programme for MSME producers in the processing sector in 13 priority areas -a part of their digital transformation promotion for Micro, Small, and Medium Enterprises (MSMEs).
North Sumatra, Bangka Belitung, Banten, Greater Jakarta and the Thousand Islands, Central Java and the Special Region of Yogyakarta, East Java, West Kalimantan, West Nusa Tenggara, East Nusa Tenggara, Southeast Sulawesi, North Maluku, West Papua, and Papua are among the thirteen provinces.
This programme will be carried out for 6 months offline and online, involving 165 facilitators or local heroes, and implemented in 15 Training Centre locations spread across 13 priority areas.
– Johnny G. Plate, Minister of Communication, and Information
To support the MSME assistance facility, a starter kit in the form of a data package will be provided for 30,000 MSMEs for 6 months, equipped with a learning management system and a Point of Sales (PoS) system aggregator application. It is hoped that the MSME digital technology adoption programme 4.0 will result in an increase in the level or scaling-up of MSMEs in terms of digital technology adoption, which is divided into four levels: beginner, observer, adopter, and leader.
The beginner level is designed for MSMEs with limited business, financial, and technological dimensions. The first level is for those who are just starting out with social media. Second, observe or use a marketplace for businesses that have been managed in a relatively modern but low-tech manner. The third category is adopters, which are businesses that have a good level of technology adoption and knowledge but still use traditional business management, such as fintech platforms and aggregators and a Point of Sales system.
Meanwhile, level leaders are companies that have been managed in a relatively modern manner and have a relatively high level of technology adoption and knowledge, such as using Big Data 3D modelling, QR Code, Augmented Reality, or Virtual Reality.
The Minister of Communication and Information explained that this programme is a more intensive version of the MSME go digital or digital onboarding programme. Through this sustainable assistance facility, it is hoped that MSMEs in the manufacturing sector will be able to increase their access to marketing, income, the competitiveness of innovation, as well as the efficiency and effectiveness of their business operations, allowing them to advance to class and contribute more to the economy, particularly during the post-pandemic economic recovery.
As a result, the Minister of Communication and Information Technology believes that commitment to strategic policy support from various parties is required. This includes regional heads, ministries, and institutions, as well as industry support, including both domestic and global technology companies, as well as the national digital ecosystem.
The Role of Small and Medium-Sized Businesses in the Post-Covid-19 Recovery
According to Minister Johnny, the public is currently taking sides and prioritising job creation, and MSMEs are an important node for job creation. The number and qualifications of available jobs, as well as the quality of the jobs themselves.
“To be carried out in a sustainable manner, because our national MSMEs are very large and the foundation of our national GDP rests on MSMEs, which contribute more than 97% of jobs,” he said. This was demonstrated by the consistent increase in the contribution of the digital economy to Indonesia’s GDP.
In 2019, the contributions of the new digital economy were around 2.9%, rising to around 4% in 2020, and they are collaborating to make the digital economy’s contribution to GDP in 2030 around 18.8%. Joint efforts to gradually increase the digital economy’s contribution to the gross domestic product from year to year continue to increase and will significantly contribute to Indonesia’s GDP.
To increase the protection of geographical indications (GI) products in the Philippines, the Intellectual Property Office of the Philippines (IPOPHL) has issued implementing rules and regulations (IRR) on geographical indications (GI)
“Supporting these goods to have the global spotlight they deserve, will make a tangible difference in the lives of our farmers, our weavers and all who make up our GI landscape,” said Rowel S. Barba, Director General, IPOPHL.
The IRR, drafted by the Bureau of Trademarks, attempts to implement the 1997 IP Code’s recognition of GIs as protectable intellectual property. It will also satisfy the Philippines’ commitment as a member of the World Trade Organisation to give reciprocal rights and protection for GIs to other members. Hopefully, it will be finalised and implemented soon, making unique and high-quality Philippine items more appealing.
The proposed IRR defines GIs as any indication that identifies a good as originating in a territory, area, or location, and where a given quality, reputation, or other characteristics of the good are primarily related to its geographical origin and human factors.
According to the draft, GI registrants have the right to restrict their products from being used in the following ways:
- Misleading the public as to the geographical origin of the goods;
- Falsely representing to the public that the goods originate in another territory;
- For wines or spirits, using in translation or accompanied by expressions such as “kind,” “type,” “style,” “imitation,” “method,” “as produced in” or other similar qualifying terms;
- For agricultural products, foodstuff and any product of handicraft or industry, using in translation or accompanied by expressions such as “Kind,” “type,” “style,” “imitation,” “method,” “as produced in” or other similar qualifying terms, if such use would be misleading to the public;
- Constituting an act of unfair competition as defined by the Paris Convention; and
- Any other use similar or analogous to the above.
On the other hand, the Bureau of Trademarks has the authority to withdraw a trademark registration for the following reasons:
- The protection requirements have not been met;
- The requirements for protection have not been met;
- The geographical origin of things has shifted, taking into account both natural and human factors;
- a court or tribunal determines that the designated producer has no effective control over the use of the GI, the items’ manufacturing standards, or other product requirements;
- GI registration was obtained using misleading claims and documents during the application process; and
- It has been established that a recognised or protected geographical indicator exists.
IPOPHL Assists Highland Provinces in Achieving GI Registration
IPOPHL recently aided several producers in Benguet (one of the provinces and tourist destinations in the Philippines) in taking the first steps toward registering their unique local products as geographical indications (GIs) in order to increase marketability and worldwide reach.
A workshop titled “Origin-Based Branding of Benguet Products and Services” was held with the goal of assisting Benguet brands and various products and services in gaining more market impact and recall, particularly in the international market, where products with quality and a good story thrive – with GI protection. Strawberry, cacao, coffee, and handicrafts, all of which are well-known in Benguet, are being studied by IPOPHL.
In the Philippines, GIs are protected by the Trademarks section of the Intellectual Property Code of 1997. The well-known Guimaras Mangoes and the Tau Sebu T’nalak, both registered as collective marks, are potential GIs.
Camiguin Lanzones, Davao Cacao, Kalinga Coffee, Antique’s Bagtason Loom, Aurora’s Sabutan Weave, Samar’s Basey Banig, Basilan and Zamboanga’s Yakan cloth, and, most recently, Masbate meat and Baguio Strawberry are among the others.
The Inter-Ministry Committee on Scams (IMCS) of Singapore has initiated two new programmes with the goal of protecting e-commerce marketplaces from fraudulent activity. These are E-commerce Marketplace Transaction Safety Ratings (“TSR”) and the Revised Technical Reference 76 on Guidelines for Electronic Commerce Transactions (“TR 76”).
The E-commerce Marketplace Transaction Safety Ratings build on these guidelines, by raising consumer awareness of the anti-scam measures on major e-commerce marketplaces in Singapore. MHA would like to thank our partners from the e-commerce industry for working with us on these initiatives to combat e-commerce scams.
– Desmond Tan, Chairman, the Inter-Ministry Committee of Scams & Minister of State, Ministry of Home Affairs & Ministry of Sustainability and the Environment
Desmond said that the adoption of anti-scam procedures in the amended TR 76 recommendations by e-commerce businesses and marketplaces would increase the security of e-commerce transactions and protect customers from e-commerce fraud.
TSR aims to provide consumers with information on anti-scam measures that major e-commerce marketplaces have in place while the TR 76 seeks to provide e-retailers and online intermediaries such as additional requirements for e-commerce marketplaces to protect e-commerce transactions from fraud.
The TSR provides consumers with information regarding the transactional security of various e-commerce marketplaces based on the range of anti-scam methods in place. It encompasses big e-commerce marketplaces that support online transactions between numerous sellers and multiple buyers and has a considerable local reach or a significant number of reported e-commerce frauds.
Major e-commerce marketplaces have been rated for their overall security. The ranking indicates the level to which anti-scam measures have been adopted to assure user authenticity; transaction safety; the availability of loss reparation channels for consumers; and the effectiveness of their anti-scam procedures. One to four ticks are available, with four ticks being the highest and best rating and will be awarded to e-commerce marketplaces that implement all essential anti-scam procedures. Annually, these ratings will be evaluated.
Consumers can also refer to the TSR microsite for safety feature warnings and specialised marketplace features. The goal of the TSR microsite is to improve consumer awareness of security measures that safeguard e-commerce transactions and to encourage the use of such features and best practises when conducting business online.
On the other hand, TR 76 as the national standard for e-commerce transactions, has been updated to incorporate additional anti-scam rules for e-retailers and e-commerce platforms in order to provide enhanced safety for online customers. Enterprise Singapore oversaw its development through a multi-stakeholder Working Group constituted by the Singapore Standards Council.
The additional anti-scam regulations will outline recommended practices for e-commerce companies and marketplaces. These best practices encompass the pre-, during-, and post-purchase phases of transactions, as well as customer assistance and merchant verification.
One of the key recommendations for TR 76 is that e-marketplaces should determine the information to acquire from merchants and the verification processes to follow. Wherever possible, e-marketplaces should check their merchant’s information against Government records or compare it to the identification document(s) provided; while the merchant verification is outsourced to a third-party service provider, the e-marketplace shall implement measures to facilitate, whenever possible, the prompt retrieval of records.
The goal is to improve merchant authentication, transaction security, and enforcement against e-commerce fraud. The new rules in TR76 are graded as part of the TSR’s safety features. In general, e-commerce platforms that adhere to TR76 standards would receive a higher TSR score.
These rules encompass the end-to-end process of e-commerce transactions and believe they will assist e-retailers and e-marketplaces in improving the traceability and security of customer transactions.
The development of enterprise-class applications has become increasingly important for enterprises seeking to access high-quality data. As they attempt to manage a data-driven organisation to achieve their corporate purpose, enterprise leaders must create frameworks to connect dependencies across processes for reliable information. When data is effectively interpreted, it becomes the key to unlocking critical business insights.
Today’s enterprises are attempting to optimise and exploit data – which they rightly regard as a valuable asset – for actionable insights. It is necessary to be secure and accurate to better support decision-making and satisfy demanding customer requirements. Not only that, but this data must be easily accessible, with exploration functions that provide analytics for obtaining actionable insights.
Recent advances in data analytics, business intelligence, machine learning and artificial intelligence have enabled enterprise organisations to better detect and accurately forecast operational difficulties. This exponential improvement in the ability to analyse enormous historical data sets and millions of pages of unstructured text to track patterns and identify potential problems is revolutionary.
By creating business intelligence dashboards, organisations can instantly understand where to increase efficiencies, when to manage costs and how to impress customers with the right financial solutions in the long run. Businesses should also focus on new methods using data to predict and mitigate risk effectively to ensure business success. Further, data analytics tool develops a single source of truth for compliance and method to build trust among customers.
Digital transformation leads to improved analysis and use of data. Through this transformation, enterprises can implement more effective business and finance practices. Although many enterprises recognise the importance of having an adequate data infrastructure, it is not yet reliable enough in many countries.
The rate at which data is generated is increasing all the time. People are preparing themselves to function and engage with data in the larger environment. In addition, the necessity to improve usable data analysis while becoming increasingly data-driven in decision-making is unanimously acknowledged.
This cannot be done without reliable analytics tools capable of desegregating and connecting previously siloed data, making it manageable from a single place.
Enterprises must be more perceptive in times of business uncertainty to detect and respond to new technology opportunities that drive digital transformation. Hyperintelligence – a term that has only lately been coined – makes data accessible to employees at their convenience.
For forecasting and strategising, data must be gathered from reliable and personalised sources. The simple card, which is considered the future of Data Analytics, aims to give important data insights for specified keywords across most web apps.
OpenGov Breakfast Insight on 25 May 2022 at Sheraton Towers Singapore aimed to provide the latest information on how enterprise is using data analytics to drive mission outcomes.
Data as the new oil
To kickstart the session, Mohit Sagar, Group Managing Director, and Editor-in-Chief, 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 a huge amount of money on technological innovations.
“Data can enable governments to make informed decisions,” Mohit asserts,” but people use data for different reasons.”
Data is no longer confined to technical departments. Successful projects must be partnerships between lots of different groups with different goals, mindsets, levels of understanding and ways of working. Breaking down silos is vital to collaboration and innovation.
Mohit believes that access is not enough – people need to possess the tools and skills. He believes that people have been looking at data abundantly but are looking for new insights. “You must look at the same thing from a different perspective. To do so, you need a new lens and develop a new culture.”
The crux of the matter is, he says, “Are organisations asking the right questions and maximising the use of data?”
In closing, Mohit emphasises the importance of partnerships that could help leverage data analytics for an organisation. “Use technology and minimise customisation. Do not try to customise technology – use readily available tools.”
By working with the right people, a company can accelerate its digital journey towards effective digital transformation. In light of this, he encouraged delegates to look for experts to partner with who could ease their transformation journey.
Value creation through data analytics
Ram Kumar, Chief Data and Analytics Officer, Cigna spoke next on how to create value through data analytics.
Ram begins with a definition of a data-driven organisation: it performs analytics/advanced analytics and builds data-driven intelligent (AI) solutions to drive business outcomes. Using data does not necessarily mean an organisation is “data-driven” or has a “data-driven culture”.
Expanding on what a data-driven culture means, Ram adds that it is related to how the “lifecycle of data” is managed and governed effectively and efficiently which would enable an organisation to organise, enable/democratise its data for consumption to drive activities acceptably. Ultimately, it is to use data to make informed decisions, create value, resolve conflicts and manage risks.
Ram shared his organisation’s data and analytics vision: a data-driven culture that is built on democratised data and intelligent data-driven insights that drive affordable, simple and predictable healthcare for our partners, customers and communities.
People often take data for granted, Ram feels. Organisations need to recognise that data is an enabler and should democratise it – make it accessible and available. Once data is democratised, anything is possible.
A true data culture for Ram is when data is on the balance sheet and information is more valuable than hardware and software.
He also shared what a data-driven value creation prioritisation framework looks like:
- IM (Information Management) Strategic Priorities/Themes
- Country and Regional Business Priorities
- Enterprise Strategic Priorities/Themes
Data and Analytics Capability Maturity Assessment
- Data Lifecycle Management & Governance
- Data Analytics
- Data processes
- Data Privacy, Ethics & Security
- Data Monetisation
- Data Value Creation & Measurement
- Data Architecture
- Technology supporting Data enablement
- Data culture
IM Data and Analytics Strategy and Roadmap
- Data and Analytics Platform – Op & Analytical
- Tools and Technologies
- Operating Model
- Ways of Working – Partners, Central/Local
- Frameworks, Standards, Processes
- Data Governance Model
- Data and Technology Architectures
- Skills and Capabilities
- Data-driven culture
- Quarterly Review and Validation
Data strategy should be agile and reviewed every three months to ensure that it aligns with value creation.
Business Use Cases Prioritisation
There are criteria that the business has to meet before looking at the use case that the organisation wants to implement. This is to ensure that it can be operationalised:
- Business Use Cases for Regions/Countries
- Technology Use Cases for Regions/Countries
- Link to strategic themes e.g., affordability
- Business Use Cases Prioritisation and Value Creation Framework – Implementation feasibility/effort vs. business value
- Business Use Cases Accountability Register
- Waiting List Use Case Register
- Quarterly Business Use Case Validation
Business Use Cases Execution and Operationalisation
- BI, Descriptive, Predictive, Prescriptive & Disruptive Analytics (inc. ML/AI)
- Data Stage Gate Review Process
- Smart Data Governance
- Operational Analytics
- Value Measurement and Reporting
- One Page Case Study
- End to End Execution and Delivery Process Continuous Improvement
In conclusion, Ram is a true believer that organisations need to own their data strategy. True transformation can only happen when organisations focus on business value creation through use cases or data foundational work.
Deepening organisational use of data analytics
Kyung-Whu Chung, Director, Sales Engineering, APAC at MicroStrategy spoke next on the different stages of data analytics and maturity.
“Why do we do analytics?” Kyung-Whu begins. “There are different reasons, ranging from growth, efficiency, user experience, quality, risk.“
There are huge benefits for organisations to using data analytics, including improved efficiency and productivity. Better data analytics leads to faster and more effective decision-making and 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, demand and identify issues. It improves customer acquisition and retention with enhanced customer experience.
Kyung-Whu acknowledges that in the past, most might have used data analytics for efficiency, but mature organisations today are using data to increase customer services and drive topline growth. The way that data is being used today is in driving more significant business outcomes.
As Kyung-Whu shares the different stages of data maturity, he explains that stages one to three are based on business requirements and the building of a trusted environment. However, stages four and five are looking at data as an asset and zooming in on data adoption, working the data as a life cycle.
In closing, Kyung-Whu agrees with Ram that data strategy has to be owned by the organisation. Everyone will be at a different stage, he believes. What is important is knowing where organisations are at and how they would like to move forward. He encouraged delegates to expand 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.
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 to 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 polling inquired on the stage in which organisations are at based on the Business Intelligence Maturity Assessment. Most (61%) are at level 3 (strategic) while the remaining delegates are either at level 2 (tactical) (11%), level 5 (transformative) (11%), or level 4 (mission-critical) (17%).
Kyung-Whu remarks that it is often not a neat distinction in stages. There are a few dimensions: people, process, technology and the data itself.
The next poll inquired about the main challenge delegates face in their data strategy journey. Half (50%) chose a lack of data culture/literacy/skill across employees as their primary concern. Under a third (31%) thought that missing an overall strategy that crosses departments and teams is their biggest obstacle. Just over a tenth (13%) indicated data governance, data privacy and security concerns, while the lack of a centralised tool for sharing and collaboration was troubling for 6% of the delegates.
One delegate felt that it is easy to get the tool in place, but the challenge lies in getting people to use data to generate insights and share insights. Mohit echoed that it is a cultural issue on top of the possibility of needing to navigate legacy technology.
Kyung-Whu agrees that data culture and literacy are important. He is glad that organisations are looking into people because it shows a shift in the maturity of organisations.
Another delegate said that the level of maturity and adoption varies across the different agencies in his group of organisations. To analyse data, organisations need to have common data dictionaries as well as a governance structure that is agile enough to adapt.
On the top analytic adoption challenge in their agency, most (41%) found unstated factors to be the issue. Over one-third (35%) found data quality and accuracy concern the biggest obstacle. The remaining thought that the lack of talent and training (18%) or found the limited access to analytics challenging (6%).
Kyung-Whu commented that it is important to ensure that people are speaking the same language. There needs to be more bridging between business and IT.
When asked about their agency’s biggest data management barrier, 38% found data accessibility and sharing the biggest stumbling block. A quarter (25%) found the ability to analyse data in real-time the biggest challenge. The remaining delegates found providing trusted data to be a hindrance (19%), regulatory compliance (12%) or data collection/cleansing (6%) their biggest barriers.
Mohit believes that if businesses learn to use data, they will become ten times stronger. Kyung-Whu adds that the key is to get people to use data through trigger points. At the right moment, if the data shows up and is pushed to people, it can prompt people to ask the next or the right questions. The more people are enabled, the more data regulation becomes important.
Inquiring as to what business users do when they have new data requirements, an overwhelming majority (80%) would approach data analysts in their business unit for support. Of the remaining, 13% would raise a Helpdesk ticket for IT (Information Technology) support, while 7% would go with their gut feeling.
On being queried about the application that delegates spend most of their working days on, just over half (53%) spent their time on productivity applications (like Microsoft Office), followed by email (29%) and then business intelligence applications (18%).
Looking to know whether delegates have considered zero-click experience for data, over two thirds (67%) need more information, 22% have not considered it while 11% have.
The Breakfast Insight concluded with remarks from Kyung-Whu who reiterated 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.
Kyung-Whu suggests a paradigm shift that would help with the use of data analytics – bringing intelligence to the general audience (70%) who would not ask questions about data. The key is to offer them “answers to their first questions.”
Instead of getting people to reach out to analytics platforms, the strategy should be about injecting intelligence to where people are – through zero-click analytics to solve the problem that we just discussed.
In closing, he invited the delegates to reach out to his team to explore ways they could deepen the data analytics maturity in their organisation. He emphasised that it is a long-term journey that MicroStrategy has walked and would be willing to undertake.