Case Study

Disruptive Technologies (Fourth Industrial Revolution 4.0)
Advances in automation, artificial intelligence (AI), big data, cyber-physical system, fintech has brought about what many people called Industry Revolution 4.0.

The following development with regard to Industry Revolution 4.0 has been reported in the media recently:

• More than 22,000 new jobs projected to be created in the manufacturing sector over the next eight years, such as Data Scientist and Robot-Coordinator. There is a shift to higher value manufacturing involving Industry 4.0 technologies, such as autonomous robot and cloud computing. Skills in demand are in areas, such as cloud computing, data analytics and public policy. (The Straits Times, 28 Nov 2016)

• According to the World Economic Forum, in a recent study, predicted that 5 million jobs would be lost before 2020 as AI, robotics, nanotechnology and other socialeconomic factor replaces the need for human workers. (The Straits Times, 7 Nov 2016)

• Robo-Advisor is an online tool that provides customer with insurance needs and offers solutions, for example, the use of Robo-advisor on wealth management, and IBM Watson provides users with advice on legal and health matters. There are other online platforms, such as Dragon Law, which help companies draft legal documents, by using simple language or terms that are easy to understand by laymen. (The Straits Times, 20 Nov 2016)

• Machine or software may eventually replace a third of graduate-level jobs worldwide. The innovation in AI and robotics could force government to order quotas of human workers, upend traditional working practices and pose new dilemmas. (The Straits Times, 06 Apr 2017)

• It was estimated by Vikram Pandit, Ex-Citigroup CEO that 30% of banking jobs would disappear in the next five years. (The Straits Times, 14 Sep 2017)

• Industries, from retail to transportation, are increasingly being disrupted by new technologies and digital applications. (The Straits Times, 5 Feb 2018)

• Roles that requires digital focused skills-such as data mining, digital marketing, data analytics and cloud computing are in high demand, with 57 % of the companies here expected to pay higher salaries for such employees. (The Straits Times, 1 Mar 2018)

One company in the transportation industry affected by the above disruption is ComfortDelGro (CDG). The company was formed in March 2003 through a merger between the two then land transport giants, Comfort Group and DelGro Corporation. Currently, it has a stake in a wide range of industries including the car rental, outdoor advertising, automotive engineering, bus and rail, as well as taxi businesses.

CDG is the current industry leader in Singapore’s taxi industry, boasting the largest combined fleet of taxis. The company “which owns Comfort and CityCab, has a combined fleet of 16,976 representing 60 percent of market share”. (Song, 2017, p. 3) CDG has enjoyed this market leadership since its formation in 2003. However, since 2013, the company’s dominant position as the market-leading incumbent within Singapore’s taxi market has seen several significant challenges, which resulted in the revenue from its taxi business being badly affected. In recent news, CDG Corporation “reported 8.2% fall in 3Q earnings to $80.1 million from $87.3 million a year ago”. (Lee, 2017) By December 2017, the absolute number of CDG’s taxis had decreased by 21% to 13,244 taxis. This is attributable to the increased competition from private-hire companies, such as Uber and Grab that first entered the market in 2013.

The entry of these ride-sharing platforms from Uber and Grab offers commuters an alternative option of booking either a taxi or chauffeured service. These ride-sharing platforms and services are also priced more competitively than the traditional taxi services “with many commuters experiencing cheaper fares during peak hours”. (Song, 2017, p. 5) Uber and Grab base their business strategy on the workings of the sharing economy by utilising untapped resources to meet unmet demands. By being heavily technologically driven, they were able to supply drivers quicker than the then-industry norms, provide convenience through cashless payment (a mode that was yet to be commonly adopted by conventional taxi operators) and even ensure a more enjoyable ride through the feedback system where passengers could rate the drivers based on the services rendered.

Although CDG has since attempted to match Uber and Grab’s value proposition of quality and convenience, CDG has still some way to go to catch up with its competitors. In addition, CDG’s service quality has also been affected. CDG’s taxi drivers have often been criticised for providing relatively poor services and have built up a bad reputation for being aggressive and being picky, choosing passengers based on their own timing and fancies. (Sicheng, 2018)

In an attempt to help its drivers address the decline in passenger pickups, CDG has collaborated with the then Uber, now Grab. This allows its taxi drivers to tap on the “UberFlash” apps to pick up passengers. Incentives are also given by Grab where drivers earn additional income based on the number of trips made. (Abdullah, 2018) This tie-up with Uber allows drivers to make use of the new technology to improve the rate of passenger pick-ups, while also relying on Uber’s driver incentive scheme to motivate drivers’ performance.

Another challenge facing CDG is maintaining the size of its workforce. At least 3,000 of its existing drivers have already moved to join Grab in September 2017. (Abdullah, 2017) The exodus of its drivers was the result of a targeted campaign by Grab to attract existing CDG’s taxi drivers to switch over to its partner taxi companies by offering large rental discounts. This was made after the announcement by CDG of a possible tie-up with Grab. (Tan, 2017) Despite that, CDG has yet to offer attractive rental rebates to its drivers although there have been slight reductions in its rental charges. (Cheng, 2017; Tan, 2017)

The challenges to CDG Corporation’s taxi business in Singapore also come from two main areas. Firstly, the improvement of public transport systems, which compete indirectly with taxis, such as public bus services and the mass rapid transit rail network (MRT).

Second, the more recent emergence in Singapore of dock-less bike sharing schemes, which also compete indirectly with taxis for commuter market share as it presents a much cheaper alternative for shorter distance commute.
By law, private rental cars are only authorised to accept planned bookings with the help of the ride-hailing applications. These ride-hailing apps have brought about the convenience of hiring a chauffeured car at commuters’ fingertips at lower costs than traditional taxis; thus, resulting in the increase demand for private rental cars over traditional taxis.

Since the debut of the ride-hailing apps, Grab has been putting pressure on the traditional taxi companies like CDG by poaching their drivers to join them. They offer lower car rental rates and give out promotion codes generously to commuters to promote loyalty.

As technology changes, the nature of jobs also changes. The need for workers to learn new skills regularly and promptly has become even more pressing. Singapore National Employers Federation executive director, Koh Juan Kiat said that employers need to continually invest in the skills of their employees to keep them updated and relevant to their business requirements.

More so, careers are becoming longer due to rising life expectancy, while the half-life of professional skills (the time taken to lose relevance) is becoming compressed to as little as five to six years. This means that a typical worker will need to acquire new skills at least seven to eight times over his/her career, according to Mr Indranil Roy, Future of Work Lead at Deloitte South East Asia. (The Straits Times, 2017)

In the final analysis, jobs will change at the micro level, thus requiring new skills and capabilities to make the most out of technologies. Training, lifelong learning and updating ourselves will become essential for every single job; otherwise, we will become obsolete at a faster rate in an organisational environment that is relatively disruptive.

Question 1
(a) One way to manage the disruptions is for organisation to become a learning organisation. The wide spread use of artificial intelligence (AI) and big data among other things will be the norm in industrial revolution 4.0. Discuss the common themes in the definition of a learning organisation and the challenges that managers operating in the disruptive industries need to be aware of when attempting to transform the organisation into a learning organisation.
(Word limit: 1,000 to 1,200 words)
(15 marks)

(b) Examine the future trends in the field of training and development with the advent of disruptive technologies, and to what extent these trends are applicable/valid in the disruptive industries. Provide relevant examples from the case.
(Word limit: 1,200 to 1,400 words)
(25 marks)

Question 2
(a) In the current disruptive environment, we have to identify the training and development needs of employees on a timely basis to keep pace with the changing technologies, otherwise, skillsets will become obsolete very quickly. Hence, identifying the training and development needs without fully understanding the concepts associated with needs assessment (NA) is an organisational disaster from the training and development perspective.
With this in mind, examine the following with relevant examples from the case:
– The factors that triggers NA
– The purpose of NA
– The three levels of NA.
(Word limit: 1,300 to 1,500 words)
(30 marks)

(b) Based on the results of the needs assessment, evaluate the following concepts/models to help an organisation operating in a disruptive business environment manage the learning of its employees more effectively:
– The basic assumptions of adult learning and their implications;
– The adult learning styles developed by Honey and Mumford (1982).
(Word limit: 1,100- 1,300 words)
(20 marks)

(c) Recommend the strategies that can be used to help employees learn better.

(Word limit: 500 – 800 words)
(10 marks)