Examples of Data Use (from US)
1. Industrial Manufacturing
Measuring and certifying of the safety of autonomous vehicle by RSS 1[Summary]⚫

Some companies are already contributing to the safety standards ofautonomous vehicles.

⚫

Company A has developed a Responsibility-Sensitive Safety (RSS) model, thatcan measure and prove the safety of autonomous vehicles, using a tested
mathematical formula to mimic human driver behavior. RSS provides
autonomous vehicle manufacturers with a transparent safety model to test andprove the safety of their vehicles, and defines a ‘safe state’ for human
responsibility and caution needed to prevent accidents.

Providing connected car hardware2[Summary]⚫

Some companies, in partnership with telecom companies, already provide
connected car hardware.

⚫

Through connected car Wi-Fi hotspots which are embedded in vehicles,
enabling travelers to stream entertainment or work on-the-go.

⚫

Activating one hotspot can get multiple connections and eliminating the needfor individual data plans or routing devices⚫

The car Wi-Fi can also be connected to from outside vehicles, making it aviable connectivity solution when working from home.

⚫

Beyond in-vehicle infotainment, automotive players started to offer otherconnected services such as, predictive maintenance, real-time emergency
response, concierge services, and even in-vehicle e-commerce services.

Implementation of autonomous driving

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⚫

Company B has nearly 50 deep learning models, trained from millions of images,
running at once on the car's onboard computer to predict what the auto-pilot
should do in reaction to traffic signals, pedestrians, or other objects.

⚫

In addition to such deep learning models are high-performance, low-power
consumption system on a chip that offer high reliability and scalability to allow
for over-the-air updates. Such Application-specific integrated circuit (ASIC) orGraphical Processing Unit (GPU) chips are embedded into autonomous vehicles
to allow for on-board edge processing, reducing the volume of data that needs
to be transmitted outside the vehicle.

Machine learning enabled drug discovery optimization⚫

By leveraging machine learning on multiple data sources, Company C was able
to quickly and accurately predict biomarkers of therapeutic response and informtarget selection for drug discovery.

⚫

Artificial intelligence raised a hypothesis that the comapany’s existing medicine,medicine A, to treat rheumatoid arthritis could be used to treat COVID-19,

The

Food and Drug Administrative issued an Emergency Use Authorization to allow
use of medicine A as a part of combination therapy to treat hospitalized COVID19 patients, marking an example of where artificial intelligence supported
identification of an alternative indication for an existing drug.
[Future Barriers (1.Industrial Manufacturing)]⚫

Software talent and AI expertise – engineers need to reskill and learn thehow/what of data labeling, model development/training and deployment.
Providing training on software development and machine learning to existing
engineers are necessary.

⚫

Limited availability of labelled datasets hinders development of ML models –revamping internal policies on collecting and labelling images that are usable for
AI in the future including making sure data is in an integrated and interoperable
format. It is hoped that practices to gather and label unstructured data formachine learning purposes will be established.

2⚫

Legacy IT policies and fragmented infrastructure impede data-driven use cases– integrated databases or ‘single sources of truth’ are needed. Launching agile
digital divisions to operate unencumbered in a ‘test and learn’ environment withlatitude from legacy organization is also needed.

⚫

Top management reluctant to invest in bold digital transformations. Perceptionthat automation threatens workforce stability – C-level need to drive resource
reallocation into software, analytics, AI.

⚫

It is desirable to create initiatives to incentivize industrial manufacturing
companies to adopt digital through public-private collaboration.

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2. Retail
Deep learning driven demand prediction 3[Summary]⚫

Traditionally, demand prediction involved old-school statistics to analyze
datasets such as historical sales reports and competitor product catalogues.
There is, however, a wealth of information available that traditional techniques
cannot easily capture, such as, for apparel: comments on fashion blogs;
popular styles and colors as seen on social media posts; customer style andcolor searches on online stores.

⚫

Machine learning, and deep learning – including image and text recognition –can unlock new realms of customer data that can provide insight into what is
popular and selling now, and in the future. Such insights can be valuable forretailers during the process of designing and predicting demand for products.

⚫

An example of a company playing in this space is that, Company D launched apartnership with a search engine company as a part of their Project in 2018, touse machine learning, and deep learning for image recognition, to evaluate
product trends and predict demand. By analyzing images and other data, thepartnership will enable the company to predict colors, shapes and styles likely
to be in vogue and design products accordingly.

[Expected impacts]⚫

Improved sales prediction accuracy, shortened times between design andproduction.

Deep learning driven demand prediction 4⚫

By eliminating time spent waiting in line and paying, Company E has streamlined
the customer journey and enhanced the customer experience, while reducing
human error at checkout. Another hidden benefit of the company is the ability tocollect valuable data on customer behavior and preferences. Physical grocery

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stores have no way of tracking anything beyond final purchases. The company,by contrast, uses customer scrolls, views and clicks to obtain additional insights,e.g. the number of times a product was picked up but replaced on shelves without
a final purchase. This trove of data can inform assortment decisions and store
layout.
[Future Barriers (2. Retail)] 5⚫

Prevalence of legacy systems increases modernization costs.

⚫

Capability gaps and limited data availability hinder rollout of turnkey e-commerce
solutions for small stores.

⚫

Size of workforce poses challenges for staff retraining and change management.

⚫

Store-based incentive structure discourages shifting to e-commerce andomnichannel.

⚫

Non-standardized product and customer IDs hinder supply / demand, andcustomer analytics⚫

Following countermeasures need to be taken:•

Leverage secure cloud data platforms to process high frequency andvolume of retail customer data to enhance operations and customer
centricity.

•As retail is an industry that frequently connects with large population groups,
the availability of rich, granular and high frequency customer datasets, withoften fewer sensitivities around data collection and usage (compared topatient health records) allows players to perform fully functional advancedanalytics. In order to fully leverage this data enterprises need to move awayfrom legacy systems to cloud-based digital platforms that support data
integration and building of scalable digital applications.

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3. Education
Enrichment of online education (EdTech players) 6[Summary]⚫

Several EdTech players aim to simplify the provision of online teaching whenin-person education is not possible, and also reduce the amount of time spentby teachers and students assigning, completing, and grading homework.

⚫

Some OS vendors, for example, have each built on their workplace productivity
suites to offer education-focused products: teachers can use them to deliver
lessons remotely, share materials, and distribute and collect assignments.

⚫

Additional cloud solutions can also be integrated by schools to foster creativity
and teamwork. Such a solution allows teachers to design interactive projects
where students can collaborate to practice multimedia storytelling, using
accessible, browser-based tools.

Enrichment of online education (High Education) 7[Summary]⚫

In Japan, institutions such as the University of Tokyo have made lecturerecordings and courseware available online, and many have temporarily adopted
online learning. For universities, hybrid or fully remote instruction presents
several opportunities.

⚫

It lowers operating costs from lecture halls and accommodation facilities, makes
it possible for more students to attend courses, and allows for more flexible
academic calendars. Moreover, the use of cloud and other technologies allows
educators to leverage resources from multiple new sources, such as otheruniversities or education programs. In order for these models to be successful,
however, universities need to carefully design programs that allow for academic
mentorship and feedback, social interactions, and equitable access.

[Future Barriers (3. Education) 8]⚫

GIGA program promotes cloud adoption to a certain extent, but has no clear

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mandate for actually adopting the cloud. And due to security concerns, there arecases where faculty’s devices for school affairs are not permitted to connect tothe Internet, which becomes a barrier to collect and utilize the study data ofstudents.
⚫

In addition, personal information protection ordinances of local governments
have been a barrier: While driven by the desire to protect individuals’ privacy, thecomplexity and multiplicity of such provisions may present a major impediment,
particularly in implementing remote-based education at scale.

⚫

A harmonized privacy regulatory framework would facilitate the deployment ofcloud-based learning solutions countrywide. Government should support theacademic institutions based on the updates of the revised Education Information
Security Policy Guideline and should continue to revise future guidelines
balancing security and cloud/internet access. In addition, expanding IT literacy
training opportunities for faculty members will be the key to enhance optimized
learning opportunities for each and every student.

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4. Government Services
Data sharing across public and private sector (Estonia, United Kingdom, UnitedStates)9[Summary]⚫

In a digital world, making data accessible is critical to development. The digitalworld is less about data integration – which requires moving data from one
location to another - and more about sharing data sets or making data
accessible through Application Program Interfaces (APIs). Businesses havesolved this problem by creating data-lakes with data sets that can be accessed
across an organization, or by developing layers with APIs to enable builder
teams to access select data.

Building a data exchange layer can achievesignificant benefits for customers without requiring major IT overhauls.
⚫

Estonia is a marquee example of deploying a data sharing layer that has
improved customer experience with significant efficiency gains, saving thegovernment 1,407 working years in 2018.

⚫

The UK’s Government Digital Service (GDS) shares ~20,000 datasets enablingdata scientists and software specialists to develop new applications.

⚫

Many US cities also excel at data sharing. For example the city of Chicago
makes thousands of datasets available, which citizen data scientists anddevelopers have used to build apps, a notable example being identifying safe
areas to run or ride a bike in. The city of Boston similarly shares thousands ofdata sets; an innovative example involved an app that used a phone’saccelerometer while driving to detect where there could be potholes in the roadthat needed to be repaired. A final example is the city of San Francisco whichalso makes many datasets available, for example to track energy usage acrossbuildings.

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Digital citizen and business journey portal/apps (United Kingdom, Singapore,Estonia, Japan, Norway) 10[Summary]⚫

The UK’s Government Digital Service (GDS) developed ‘Gov.UK’ in 2012, a onestop-shop to access e-services, which replaced ~1,700 different government
websites and provides access to ~300 agencies. This has been estimated tosave taxpayers £70m per year in service delivery costs.

⚫

The UK, as a part of its consolidated government e-services website, allows
citizens to create online childcare accounts which can then be used to obtainchildcare support programs, such as yearly free childcare with approved
childcare providers.

⚫

In terms of purpose-specific apps, the Singapore government created an app
called ‘Moments of Life (Families)’, to proactively support families of children
aged 6 and below: it provides necessary information to parents and caregivers(including birth registration, preschools, immunization records) and is designed
to improve with feedback.

⚫

Estonia, often touted as the top eGovernment executed a plan to consistently rollout new digital products. In 2000 it rolled out e-Taxes, in 2002 ID-card to access
e-services, in 2005 i-voting, in 2007 Mobile-ID; a mobile version of the original
ID card. Later in 2011 it launched Reporting 3.0 to help entrepreneurs accelerate
the submission of data, and in 2014 it launched e-Residency. Estonia has further
identified 10 focus areas to keep pace with digital revolutions and emerging
technologies by moving basic services to a full digital model, with the goal ofhaving at least 7 new services functioning in 2020.

⚫

In Japan, obtaining residence certification (known as juminhyou) is an essential
prerequisite for various other activities such as opening a bank account or

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starting a new job; It is now possible to use one’s My Number card to issue andprint a juminhyou at any of approximately 55,000 convenience stores spread
across the country – and serving 740 municipalities that represent over 80% of
the national population – in a process that takes just a few minutes at a selfoperated kiosk. Moreover, certain municipalities such as Shibuya in Tokyo haverolled out chatbots, that can be used to apply for and electronically pay forjuminhyou copies and other documents such as tax certificates through one’s
smartphone, via the popular LINE messaging app. After requesting and paying
via LINE, citizens have to wait to receive physical copies of the documents which
are mailed to their registered residential addresses. Although the kiosks andchatbots mark considerable improvements from a process based on physicalvisits, they still involve receiving paper copies of the juminhyou.
⚫

An example is Norway, where pension applications can be made entirely online
using the Norwegian Labor and Welfare Administration’s portal, and citizens canapply electronically and receive a response within minutes. Citizens may also
use the portal to get an overview of their pension earnings, calculate future
pension amounts, and compare options to see how withdrawal dates and rates
can affect the size of one’s pension – all without having to deal with multiple slipsof paper.

10Online portal to enable one-day company setup (New Zealand)⚫

Starting a company requires deciding on a business structure, obtaining approval
for a company name, securing the necessary capital, appointing key staff, andestablishing a legal address.

11⚫

Streamlined this process, New Zealand reached the top of the World Bank’s
global DB (Doing Business) ranking for ease of starting a business. On theCompanies Office website, registering a business is a one-step procedurecompleted in under a day.

[Expected impacts]⚫

Quicker setup of company, reduction in processing time for government workers.

Online paperless platform for import and export of goods and services(Singapore)11[Summary]⚫

A truly interesting innovation is Singapore’s online platform for trade, the NTP(Networked Trade Platform), which has won several international awards. Morethan an online marketplace, it allows any Singaporean business to log in with asingle business ID, connect with domestic and international players across thevalue chain, set up paperless contracts and customs declarations, organize
freight shipments, monitor trade activity and integrate with third-party systems.

[Expected Impacts]⚫

Increased volume and expedited process of trade, reduced disruptions toproduction schedules due to a streamlined and diversified supply chain.

Central management of public procurement (South Korea, Sweden)⚫

Korea ON-line Eo-Procurement System (KONEPS) was created as a central
portal for public procurement, The launch of KONEPS reduced bid processing
time from 30 hours to <2 hours, and is one of the largest e-commercemarketplaces in the world with a total transaction volume of around U$60B.

⚫

Sweden is another example, with a common eProcurement platform that waslaunched as long ago as 2007.

[Future Barriers (4. Government Services)] 12
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Data standards vary across agencies - data is not always machine-readable orallows for joint analysis. Different legal frameworks between agencies, nationaland local governments create complexities regarding what data can be digitizedor shared. Need to establish standards for data format and data quality acrosssources, deploy “data dictionaries”, implement APIs and use cloud-based single
sources for each data type.

⚫

Interoperability of systems across government agencies - adopting common
protocols or data types, reducing interoperability overhead.

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