Literature Review Assignment
ANDYXU666
Lecture2Slides-2.pptxTechnology and Digitalisation I: Workplace Automation, Big Data, and Cyber Security
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Gartner Top 10 Strategic Technology Trends for 2020
Inju Yang (IY) - 6.06min
Overview
The Digital Economy and Workplace
Workplace Automation
Big Data
Cyber Security
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Platform economy
Platform economy
Platform economy
Platform economy
Platform economy
Platform economy
The “gig” economy
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Platform economy
Platform economy
The “gig” economy
The gig economy: hyper flexibility or sham contracting?
To its proponents, the gig economy is a brave new world allowing people to be masters of their own fate: to choose the work they do and for how much they do it. To its critics, the gig economy is dangerously unregulated and creates fertile ground for exploitation: the promise of choice rings hollow.
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Digital economy to triple to $240 billion by 2025-Southeast Asia’s case
Google’s third “e-Conomy SEA” report
The Digitalisation of the Economy
The trend of the economy is in digital adoption
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The Digitalisation of the Economy
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Some examples of leading companies in a digital world
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Disrupting the corporate recruitment market
Influencer marketing
Telstra
Crowd support transforming service through the crowd
Airbnb
It’s not about what you own but what you do
Managing Big Data
“You can’t manage what you don’t measure.”
Peter Drucker
Big data is so voluminous, but it can be used to address business problems.
- Oracle
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Managing Big Data
What is big data?
Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.
Source: McAfee & Brynjolfsson (2012), Harvard Business Review
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Managing Big Data
Features of big data
Volume: Amount of data
Velocity: Rate at which data is received and acted on
Variety: Types of data that are available
Source: McAfee & Brynjolfsson (2012), Harvard Business Review
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Managing Big Data
Benefits of big data
The more companies are characterised as data-driven, the better they performed.
Companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors.
Big data makes it possible for people to gain more complete answers/solution as it provides more information.
Source: McAfee & Brynjolfsson (2012), Harvard Business Review & Oracle
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| Product Development | Companies like Netflix and Procter & Gamble use big data to anticipate customer demand. They build predictive models for new products and services by classifying key attributes of past and current products or services and modeling the relationship between those attributes and the commercial success of the offerings. In addition, P&G uses data and analytics from focus groups, social media, test markets, and early store rollouts to plan, produce, and launch new products. |
| Predictive Maintenance | Factors that can predict mechanical failures may be deeply buried in structured data, such as the year, make, and model of equipment, as well as in unstructured data that covers millions of log entries, sensor data, error messages, and engine temperature. By analyzing these indications of potential issues before the problems happen, organizations can deploy maintenance more cost effectively and maximize parts and equipment uptime. |
| Customer Experience | The race for customers is on. A clearer view of customer experience is more possible now than ever before. Big data enables you to gather data from social media, web visits, call logs, and other sources to improve the interaction experience and maximize the value delivered. Start delivering personalized offers, reduce customer churn, and handle issues proactively. |
| Fraud and Compliance | When it comes to security, it’s not just a few rogue hackers—you’re up against entire expert teams. Security landscapes and compliance requirements are constantly evolving. Big data helps you identify patterns in data that indicate fraud and aggregate large volumes of information to make regulatory reporting much faster. |
| Machine Learning | Machine learning is a hot topic right now. And data—specifically big data—is one of the reasons why. We are now able to teach machines instead of program them. The availability of big data to train machine learning models makes that possible. |
| Operational Efficiency | Operational efficiency may not always make the news, but it’s an area in which big data is having the most impact. With big data, you can analyze and assess production, customer feedback and returns, and other factors to reduce outages and anticipate future demands. Big data can also be used to improve decision-making in line with current market demand. |
| Drive Innovation | Big data can help you innovate by studying interdependencies among humans, institutions, entities, and process and then determining new ways to use those insights. Use data insights to improve decisions about financial and planning considerations. Examine trends and what customers want to deliver new products and services. Implement dynamic pricing. There are endless possibilities. |
Big Data Applications
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Big Data Analytics
https://www.youtube.com/watch?v=aeHqYLgZP84
Play from the beginning to 01:30 as an introduction to the topic
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Inju Yang (IY) - 2.19min
The Dangers of Big Data
First, big data is…big. Although new technologies have been developed for data storage, data volumes are doubling in size about every two years. Organizations still struggle to keep pace with their data and find ways to effectively store it.
Data must be used to be valuable and that depends on curation. Clean data, or data that’s relevant to the client and organized in a way that enables meaningful analysis, requires a lot of work. Data scientists spend 50 to 80 percent of their time curating and preparing data before it can actually be used.
Big data technology is changing at a rapid pace. Keeping up with big data technology is an ongoing challenge.
Big Data Challenges
Big Data
Take the problem apart into pieces
Put pieces back together to conclude
Big Data
Human Brain
Two pillars of solving complex problems
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Management challenges posed by big data
Leadership
Talent management
Technology
Decision making
Organisational culture
Source: McAfee & Brynjolfsson (2012), Harvard Business Review
Managing Big Data
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Class Activity : How can we use big data wisely?
How does big data help us solve complex problems?
What is the role of big data?
Why is big data alone not enough?
What are the messages to organisations?
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Artificial Intelligence
“…the field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem solving, and pattern recognition.”
- Amazon
Big data and AI
Big data and AI
Types of Artificial Intelligence (AI)
Weak AI or Narrow AI:
Focused on one narrow task
Example: poker game machine in which all rules and moves are fed into the machine
Each and every weak AI will contribute to the building of strong AI.
Strong AI:
Machines that can actually think and perform tasks on its own just like a human being
Types of Artificial Intelligence (AI)
Reactive Machines:
Basic forms of AI
Doesn’t have past memory and cannot use past information for future actions
Example: IBM chess program that beat Garry Kasparov in the 1990s
Limited Memory:
Can use past experiences to inform future decisions
Decision-making functions in self-driving cars have been designed this way
Observations used to inform actions happening in the not so distant future, but these observations are not stored permanently
Theory of Mind:
Able to understand people’s emotions, belief, thoughts, expectations
Able to interact socially
Not fully achieved
Self-awareness:
Has its own conscious, super intelligent, self-awareness and sentient
Not fully achieved
What is digital workplace like?
The digital workplace encompasses all the technologies people use to get work done in today’s workplace. It ranges from HR applications and core business applications to e-mail, instant messaging and enterprise social media tools and virtual meeting tools.
The Digitalisation of the Economy
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What are the digital tools available at workplace?
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Workplace Automation
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Workplace Automation
What will be the impact of automation on the economy and organisations?
Can we look forward to vast improvements in productivity, freedom from boring work, and improved quality of life?
Should we fear threat to jobs, disruptions to organisations, and strains on the social fabric?
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Four Fundamentals of Workplace Automation
1) The automation of activities
At least 45% of work activities could be automated using already demonstrated technology
In many cases, automation technology can already match, or even exceed the median level of human performance required
Narrative Science’s Quill
IBM’s Watson
From: Mckinsey & Company
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2) The redefinition of jobs and business processes
Fewer than 5% of occupations can be entirely automated using current technology, but 60% of occupations could have 30% or more of their constituent activities automated
As roles and processes get redefined, the economic benefits of automation will extend far beyond labour savings
Lawyers using text-mining techniques to review legal documents
Sales organisations use automation to improve quality of offers
From: Mckinsey & Company
Four Fundamentals of Workplace Automation
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3) The impact on high-wage occupations
A significant percentage of the activities performed by even those in the highest-paid occupations (for example, financial planners, physicians, and senior executives) can be automated by adapting current technology.
For example, activities consuming more than 20% of a CEO’s working time could be automated using current technologies. These include analysing reports and data to inform operational decisions, preparing staff assignments, and reviewing status reports.
From: Mckinsey & Company
Four Fundamentals of Workplace Automation
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4) The future of creativity and emotions
Capabilities such as creativity and sensing emotions are core to the human experience and also difficult to automate. The amount of time that workers spend on activities requiring these capabilities, though, appears to be surprisingly low. Just 4% of the work activities across the US economy require creativity and only 29% of work activities require sensing emotion.
The potential to generate a greater amount of meaningful work could be achieved as automation replaces more routine or repetitive tasks, allowing employees to focus more on tasks that utilise creativity and emotion.
From: Mckinsey & Company
Four Fundamentals of Workplace Automation
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Workplace Automation
Challenges and risks
Job losses and economic inequality
Privacy concern as automation increases the amount of data collected and dispersed.
The safety risks arising from automated processes, e.g., who is responsible if a driverless school bus knocks down a pedestrian?
From: Mckinsey & Company
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Workplace Automation
Messages for top-management
Keep an eye on the speed and direction of automation, for starters, and then determine where, when, and how much to invest in automation.
Making such determinations will require executives to build their understanding of the economics of automation, the trade-offs between augmenting versus replacing different types of activities with intelligent machines, and the implications for human skill development in their organizations.
The degree to which executives embrace these priorities will influence not only the pace of change within their companies, but also to what extent those organizations sharpen or lose their competitive edge.
From: Mckinsey & Company
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Class Activity : What is your future job like?
Read the New Work Smarts Report to learn how work automation impacts our future jobs.
Discuss in small groups what jobs you would like to have in the future, and what changes you can expect to have in your future jobs.
Inju Yang (IY) - 1.51min, 2017
Cyber Security Disasters of 2018
Digital transformation calls for cyber security
Cyber security myths
We have invested in a high-end security tool
A third-party provider manages our security
We only need to protect our internet-facing applications
We have never been attacked, so our security is good enough
Security is well-managed by the IT department
We have completed our security project
Antivirus is good enough
We don’t need assessments and tests
Managing Cyber Security
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Managing Cyber Security
The four steps of managing for cyber security
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Class Activity : Read these articles and discuss…
The 3 biggest challenges for tech in 2019 - The Business Times: https://www.businesstimes.com.sg/technology/the-3-biggest-challenges-for-tech-in-2019
13 tech experts predict the industry's biggest challenges in 2019 - Forbes: https://www.forbes.com/sites/forbestechcouncil/2018/12/27/13-tech-experts-predict-the-industrys-biggest-challenges-in-2019/#5f45b1851bcd
Silicon Valley parents are raising their kids tech-free — and it should be a red flag - Business Insider: https://www.businessinsider.sg/silicon-valley-parents-raising-their-kids-tech-free-red-flag-2018-2/?r=US&IR=T
Discuss in the context of millennials and Gen Zs growing up with technology:
Is technology controlling us or are we controlling it?
What can we do to thrive in a technology-enabled future?
Class Activity : Read these articles and discuss…
References and Reading List
Chui, M, Manyika, J. & Miremadi, M. “Four fundamentals of workplace automation”, McKinsey & Company, November 2015.
Cyber Security: Empowering the CIO . Report from Deloitte.
McAfee, A & Brynjolfsson, E 2012, ‘Big data: The management revolution’, Harvard Business Review, vol. 90, no. 10, pp. 60-68.
Taking Leadership in A Digital Economy. Report by Telstra Corporation Limited and Deloitte Digital, November 2012.
The Digital Economy in Singapore.
The Digital Workplace: Think, Share, Do. Report from Deloitte.
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