Leader's Digest #21 (1 December 2018)

LEADERS ISSUE 21

DIGEST

1 DECEMBER 2018

LEADING IN A DATA-DRIVEN ORGANISATION DATA CAPABILITIES

COMPLIANCE

LEADERSHIP

DATA-DRIVEN TRANSFORMATION

Smart Farming 4.0: The Future of Agriculture Making Sense Of Data: What Needs To Change In Organisations Today

Leveraging Data And Analytics To Make Purposeful Decisions Mining The Big Data Of Employee Engagement

Are We Ready For Smart Manufacturing?

This fortnightly publication is dedicated to advancing civil service leadership and putting it into practice contemporary leadership principles.

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PUBLICATION TEAM EDITORIAL

Editor-in-Chief Segaren

Read this issue and past issues online at bit.ly/LEADSCS Scan the QR code below for quicker access:

Assistant Editor Yvonne Lee Diana Marie Capel Graphic Designer Awang Ismail bin Awang Hambali Abdul Rani Haji Adenan

Content Partners:

CONTENTS Page

6 Making Sense of Data: What Needs to Change in Organisation Today

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3 Smart Farming 4.0: The Future of Agriculture

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ISSUE 21 | 1 DECEMBER 2018

8 Leveraging Data and Analytics to Make Purposeful Decisions 10 Mining the Big Data of Employee Engagement 12 Are We Ready for Smart Manufacturing?

THE LEADER’S DIGEST IS A FORTNIGHTLY PUBLICATION BY LEADERSHIP INSTITUTE OF SARAWAK CIVIL SERVICE FEATURING ALL THE LATEST SURROUNDING THE TOPIC OF LEADERSHIP. THE PUBLICATION ALSO FEATURES SPECIALLY SELECTED WRITE-UPS RELATED TO EACH THEME OF THE ISSUE, THROUGH ITS CONTENT PARTNERS.

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SMART FARMING 4.0: The Future of Agriculture 1. Overview The global demand for agricultural production is anticipated to increase drastically due to the need to feed a growing population (estimated to reach 9.7 billion by 2050), which means the demand for food will increase by 70% of what we produce today [1]. The world is on the cusp of huge demand for higher-value food products with consumers showing increasing interest in the freshness, quality and safety of food. These, coupled with factors such as climate change, demographic trends, and

BY PROF. DR JUGDUTT (JACK) SINGH

food waste present an enormous challenge on the agriculture industry.

To address these challenges, there is a need to adopt more efficient and sustainable production methods to produce more food with limited available resources.

Smart Farming 4.0 can address some of these challenges of feeding our growing population effectively and sustainably. It involves integrating the farm management system, precision agriculture, agricultural automation and robotics into farming practices in order to increase productivity, production efficiency and quality of

Demand Crop Farming

Livestock Farming

Grains, fruits, vegetables, other horticultural crops, greenhouse farming, soil-less farming, breeding for genetic gain, smart glasshouses, etc.

Cattle, aquaculture, dairy and poultry, egg production, etc.

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produce. Through the integration of digital technologies with datadriven agricultural practices, Smart Farming 4.0 can equip farmers with more precise information via yield monitoring, field mapping, resource management (e.g., water, fuel, fertilisers, etc), while reducing associated costs; and the benefits are not just limited to large-scale farmers but to all, regardless of their size.

A recent study showed that Smart Farming 4.0 has a potential to raise the crop yields to 70% by 2050 and create a market worth US$240 billion for farming technology industry alone [2].

Supply

SMART FARMING 4.0

Ploughing, irrigation, soil fertility monitoring, planting and harvesting

• Agricultural machinery (e.g., robotic tractors, drones, etc.)

• Farm services • Software • Hardware (e.g., drones, satellites, smart devices, sensors, etc.)

Conventional and Organic Drone and Satellites

Value Chain

Monitoring sensors

Unmanned planes Ear tags, collars, audible and calving sensors, farm monitors, etc.

Farming

Manufacturing

Wholeselling

Retailing

Consuming

Internet of Things (IoT)

Smart sensing devices

Food safety and food waste traceability

Data analytics / Big data

Soil temperature, moisture, pH, air temperature, humidity, air quality data

Artificial intelligence & Machine learning

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2. Digital Enablers underpinning Smart Farming 4.0 Paradigm

not only provide solutions to the large co-operative farm operations or smart greenhouses, but also to assist organic and family farms (small or medium scale, specific varieties of cattle, conservation of particular breed or variety, or farming specific breed of animals for high quality meat, etc.), enhancing the transparency in farming. IoT is driving the Smart Farming 4.0 paradigm through:

Most useful technology drivers for Smart Farming 4.0 are:

•

• •

• •

Internet-of-Things (IoT) Integration of various smart farm technologies with farmers Real-time diagnostics via Drones, satellite imagery, or smartphone sensors (e.g. soil characteristics, diseases, etc.)

Automation & Robotics for monotonous work processes (e.g. weeding, harvesting, etc.)

Shared Data for information and Decision Support System (big data, cloud, AI, data analytics, visualization, etc.)

•

2.1 Internet of Things (IoT) The Internet of Things (IoT) refers to the smart devices that are connected to the internet and provide a mechanism for collecting and transferring data of a physical aspect of our environment. IoT enables a range of smart farming solutions in the areas of crop, livestock, soil and environmental monitoring, livestock tracking and irrigation management, etc. IoT-based smart farms are integrated with crop monitoring sensors (e.g., temperature, light, humidity, soil moisture, pH, plant health monitoring sensors, etc.), automatic irrigation and fertiliser application machinery [3]. Hence, the adoption of IoT solutions in agriculture is tremendously beneficial as it enables farmers to minimise waste, optimise inputs and enhance the yield. IoT applications

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Farm management: Using highspeed internet, smart devices and sensors, low cost satellites and variable rate technology, usage of resources such as water and electricity can be optimised in order to improve yields that results in high profitability from irrigated crop fields with soil variability.

Climate monitoring: The most popular farm sensors are weather stations that collect the environmental data to provide information on climatic conditions that may affect appropriate crops and require measures to reduce loss and increase productivity.

Livestock monitoring: IoT sensors (ear tags, collars, etc) attached to animals, to monitor their grazing patterns, health, activity, temperature and nutrition factors of an individual animal or collective information on total herd [4].

2.2 Drones Farmers use drones to collect a multitude of data from farms to support decision making. Drones equipped with cameras can assist with producing images of farms at a fraction of the cost, enhancing the monitoring of crop health, assessing soil quality and planning planting locations to optimise resources and land use. Using technologies like GPS, laser measurement and ultrasonic positioning, drones can perform crop

spraying tasks more efficiently, and with greater accuracy and less waste.

2.3 Automation and Robotic Farming Automation and Robotic farming is the new frontier in modern day agriculture where autonomous robots are designed to perform major farm operations. The tasks include analysing the fields, planting, weeding, spraying pesticides or fertilisers, autonomous irrigation, harvesting and capturing images of crops to examine their health. Farm robots can scan the crop health and detect changes using artificial intelligence and are helpful in spotting unhealthy vegetation. The results are promising when using robots and artificial intelligence; drone coordinating with autonomous tractors that shoot laser or spray herbicides can manage weeding more effectively and efficiently compared to conventional methods.

The major advantage is the precision and accuracy; robots can spend time in analysing and treating every plant individually, which means a careful methodology of monitoring crop health and yield. Most of the current research focuses on designing highly efficient autonomous-agricultural vehicles that can manage many field operations without any human support. Driverless tractors, fruit pickers, sprayers, sheep searing robots, automatic milking are in extensive use in large-scale farms.

As an example, driverless tractors that are pre-programmed to follow the field routes are widely used in large farms worldwide. Other farm robots are used in operations such as spraying, weeding, pruning and crop growth monitoring, contributing significantly to the agricultural industry by increasing the production efficiency and decreasing the field labour costs [5]. According to Winter Green Research, the market value

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of agricultural robotics is expected to grow to US$16 billion in 2020 [5].

2.4 Artificial Intelligence AI is introduced in various agricultural operations such as optimising seed planting, irrigation, fertilisation, chemical spraying, harvesting, fruit and vegetable grading to minimise labour costs, recognising weak or sick livestock, etc. There are many areas of the agriculture that can engage with AI technologies [2], for example, just by utilising drone or satellite images of field, soil, crop and weather, AI can predict weather changes, the impact of crop rotations on soil quality, help farmers in making sound decisions on irrigation, fertilisation, planting, crop growth, harvesting, etc. AI is also used in the crop fields to predict outbreak of diseases, identify the diseased plants and treating them to prevent the crop losses more efficiently than human observations. Likewise, diseases and lameness in livestock animals can be recognised using the same technology [2] . AI has emerged together with highperformance computing and big-data technologies to quantify, analyse, unravel and understand the data generated from various agricultural operations [6].

3. Challenges Some of the challenges in changing current farming practices to Smart Farming 4.0 include: •

•

•

Managing Infield Variability fertiliser, water, chemicals and labour on pastures, livestock and crops, etc.

Optimised Farm Operations including on-farm connectivity, labour and energy efficiency, waste management, machinery and system interoperability, animal welfare, etc.

Legal and Institutional Barriers - technology for governance

• •

•

integrity, legal frameworks for agriculture data, legal and institutional barriers and complexities that affect agricultural innovation.

Building Human Capital - research, education and training capabilities for multi-generational farmers Data Management - who owns the data and the use of the data and who is responsible and accountable for mismanagement leading to economic/environmental mishaps – technology driven Moving from family farming towards cooperative/commercial farming

4. Conclusion For many decades, farmers have followed seasonal patterns for planting, farm management and harvesting using their knowledge and experience to tackle the challenges imposed by climatic change such as drought, cold, flood and preserved their livelihoods.

With increased demands on agriculture to produce more food, Smart Farming 4.0 is the key for enabling efficient and sustainable production methods and is perceived as the future of Agriculture.

The digital transformation brought about via IoT, automation & robotics, drones, artificial intelligence and data sharing are seen as the fundamental technologies underpinning the Smart Farming 4.0 paradigm. It equips farmers with valuable real-time information and the intelligence that enable them to operate their farms efficiently and remotely, monitor their crops and livestock, reduce farm operation costs (e.g. suggestions for irrigation based on soil moisture data captured in real time), improve crop yield while minimising the impacts of climate change.

References 1. Sachs, G. (2016a). Precision farming.

Global Investment Research. Available at: https:// docdrop.org /static/drop-pdf/ GSR_agriculture-N1sH6.pdf 2. Sachs, G. (2016b). Artificial Intelligence. Global Investment Research.

Available at: http://www.smallake.kr/wp content/uploads/2017/05/ P020161223538320477062.pdf 3. https://www.iotforall.com/iotapplications-in-agriculture/ 4. https://easternpeak.com/blog/ iot-in-agriculture-5-technologyuse-cases-for-smart-farming-and4-challenges-to-consider/ 5. Padraig, B. (2016-11-25). "In the future, will farming be fully automated?". BBC News. Available at: https://www.bbc.com/news/ business-38089984 6. Liakos, K., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018).

Machine learning in agriculture: A review. Sensors, 18(8), 2674.

Prof Jack Singh is the Chief Scientist & Chief Advisor for Digital Economy, State Government of Sarawak, Malaysia. He is acknowledged as one of Australia’s leading ICT researcher, administrator and thought leader.

He has considerable experience in initiating and leading large-scale research, development and commercialisation initiatives collaboratively with industry, government, universities and community to drive high impact outcomes of global significance.

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Making Sense Of Data: What Needs To Change In Organisations Today

BY PRETHIBA ESVARY

30% of the company is not ready for the change plans that we intend to roll out.

HR

What does that mean?

What do we have to do to change that?

CEO CFO

If a human resources (HR) practitioner is unable to answer the questions above, then they are not doing their job well enough.

IBM Watson Talent Specialist James Hewitt revealed: “Organisations have long been capturing data about their employees, but typically these data sets are stored in siloed systems.�

A McKinsey article reported something similar. It said that organisations are just sitting in pools of data and are finding it a challenge to retrieve meaningful and actionable insights from those data.

Why? Is it because HR is unsure of where to start?

Or it is simply because they are fearful of delving into the unknown?

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Refusal to budge from a fixed mindset isn’t going to help an organisation get to its destination.

So, what is it that must change?

1) Composition of the HR department

and accurate and is able to provide valuable insights to the organisation.

"According to Sharma, the parameters that one sets at the beginning is therefore critical as those will determine the kind of data produced, and consequently, influence the insights which are generated."

This is where statisticians, mathematicians and psychologists come into the picture to run experiments, he says.

Accendo’s Chief Executive Officer (CEO) Sharma KSK Lachu believes that HR departments today should be made up of three vital groups. “One-third should consist of HR practitioners who are specialists in particular areas such as performance management and recruitment.

“The next one-third should consist of psychologists, mathematicians and statisticians. The last group should consist of people from different parts of the organisation who possess business acumen,” he said.

Aside from creating a knowledgesharing culture, Sharma said: “Changing the composition of the HR department allows for experimentation and this builds credibility through more robust science.”

He gave an example of measuring the performance of a low-performing group versus a high-performing one over a period of one year. The former is given positive reinforcement and the latter isn’t. Data from the two groups are then placed against each other to retrieve insights about the correlation between rewards and recognition, and performance.

He said: “Organisations must understand that in order to create and generate clean data, you need to have a big sandbox to play in."

“You must build an internal capability process that can help you run experiments."

“It’s important to remember that technology is an enabler for what you are trying to achieve. If your process is rubbish, technology is just going to enhance that.”

According to Hewitt, it is important to note that “analytics in itself won’t solve an organisation’s issues. However, it does shine a light on issues based on data, rather than opinions.”

Take performance management as an example. The traditional assessment centre (AC) falls short in terms of generating forward-looking data and in meeting an organisation’s need for speed, scale and analytics, Sharma said.

Thus, the idea of supplementing traditional ACs with virtual assessment centres (VAC) came about. In Accendo for instance, their VAC comes equipped with artificial intelligence elements of IBM Watson Talent Insights.

This enables an organisation to understand the current performance of its existing employees and steps the employees ought to take to reach a particular level of competency.

Sharma added that this is the kind of information HR folks need to have today.

In a nutshell Knowing how to gather clean data and how to make sense of it can yield great value for a business. That being said, having the right make-up in your HR department is equally important – without the right talent, it would prove challenging to achieve an organisation’s goals.

3) Invest in the right technology

2) Method of generating data and insights Based on his 15-year experience in the HR technology field, Sharma admits that one of the biggest challenges organisations face is in collecting clean data – data that is accessible

* Read our online version to access the hyperlinks to other reference articles made by the author.

IBM Watson Talent Specialist James Hewitt

Prethiba is passionate about impacting people through the written word. She believes that our lives are solely written by us, and thus the power to change for the better lies with us.

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Leveraging Data and Analytics to Make Purposeful Decisions

BY DR FAROUK ABDULLAH

The onset of the digital era has had a major impact on consumer behaviour, purchasing patterns, payment methods, consumption habits and increasingly high expectations of service.

These changes in behaviours are happening in both the businessto-business (B2B) and business-toconsumer (B2C) environment, across industries and geographical borders.

In essence, every organisation irrelevant of size and location will have to transform to remain relevant and competitive.

Data and analytics are major enablers in the digital era. It is a well-proven fact that organisations that ignore or fail to employ data and analytics will inevitably cease to exist.

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‘Culture eats strategy for breakfast’ Two of the major components of leveraging data and analytics in your organisation are culture and strategy.

Getting your business strategy or vision right will set your organisation’s flight path which, in turn, drives the operating and performance frameworks for your employees.

It is not an easy task and in most cases for small organisations, it is never completed mainly due to the inability of owners or managers to step back from the operational aspect of running the business.

However, without documenting the strategy or vision, it is near impossible to map the data and analytics strategy beyond operational needs.

Take for example, a specialist screw manufacturer.

The strategy could be, ‘The only screw manufacturer in Malaysia’, ‘The best screw manufacturer in Malaysia’, ‘The most value for money screw manufacturer in Malaysia’, ‘The biggest screw manufacturer in Malaysia’ or ‘The most reliable screw manufacturer in Malaysia’.

Each of the statements will point to a different data and analytics strategy and approach – from what data you should collect to how to visualise the data to data science application.

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However, without changing the culture of the organisation, we know that no matter what strategy we put in place, it cannot be executed.

Small business owners need to acknowledge that they are the major and, in some cases, the only driving force of the organisational culture.

The availability and affordability of data and analytics technology makes it a level playing field between large and small organisations when it comes to leveraging data. It means that small organisations can adopt the same technology as the bigger players.

engineer will be responsible for the capture, transfer and storage of your data.

Resistance to change, hesitation in adopting new technology, suspicions of the benefits of data and analytics and a reluctance to investment are all hallmarks of an unhealthy culture.

Also, be prepared to change your existing business model.

‘It’s the people that make the business’

In most cases, Microsoft Excel will do for small businesses. But the important thing to remember here is what to visualise, and for whom.

‘It is not 'big will eat small', it is, 'fast will eat slow'’ Wise words from Rupert Murdoch the media mogul – never has this been truer than in the speed of change that we are living in now.

Having the right data and analytics talent in the organisation is an important consideration when you are looking to leverage the data that you have.

Next, is to visualise your data in a format that can be easily digestible and used in your business – what is happening now.

Once you’ve got your data right and visualised, it is then the turn of the data scientist to start building models to predict what will happen next.

It is crucial that you understand the roles within the data eco-system, namely; the data engineer, the data analyst/visualiser and the data scientist.

All these talents could be outsourced as managed services – these should not cost the small business an arm and a leg.

In a large percentage of small businesses, you will not have a need

The time is now…

As data size and velocity continues to increase, stop worrying about big data and what you can use big data for.

Start by understanding and documenting your business strategy and lay the foundations for the business direction.

Create the right culture for data and analytics adoption within your workforce – drive business conversations and decision-making based on data.

Seek advice on the types of free “open-source” technology that you could adopt. There is nothing wrong with Excel if that is all you need.

The wait-and-see attitude of yesteryears is one of the cultures that we need to change. Ironically, being small in today’s world will work in your favour.

for a data scientist at the adoption stage.

The key role you should focus on is the data engineer. Getting your data right is your main priority. The data

Get the right talent help from external vendors or hire the right talent. But most important of all for the small business owners or managers, the time to act is now.

Dr Farouk Abdullah is the Chief Data Scientist of Natural Intelligence Solutions.

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Mining the Big Data of Employee Engagement

BY JOSEPH TAN

What do we know to be important but are unable to measure?

- Marcus Buckingham

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As organisations grow, so do the need for ‘mining for data’ in the right places – to make sense of the immense amount of information and transactions (both internally and externally) so that we can improve profitability and productivity.

The real value in any measurement is not in reports about what had happened (lagging indicators), but rather the value is to be found in what it can confidently forecast about the future (leading indicators).

Nowhere is this more prominent than in the measurement of employee engagement – every growing company measures it, puts it on display and derives fancy-looking charts and trends but after the complexity of the big data

of employee engagement, it only comes down to two simple factors.

Every effort to data-mine for employee engagement must eventually distil down to these two basic ingredients – everything else is superfluous.

• Do I have a great boss?

• Do I have a great job?

Hence, if you are facing a ton of employee engagement data and you need to make some simple sense out of it, the data ought to provide leading indicators as to how the managers are doing and also how much of a job fit does every employee have?

Let’s expand these two engagement tracks a little bit more.

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The boss factor According to Gallup, about 50 per cent of employees come to work not knowing what is expected of them. Sure, employees turn up for work and they can act busy or find something to do but do they know how their work connects to what really matters?

The great boss is someone who communicates clearly what is expected and then ensures that the employee has the right materials and equipment to do a good job.

In fact, according to Marcus Buckingham:

“It is better to work for a great manager in an old-fashioned company than for a terrible manager in a company offering an enlightened employee-focused culture.”

Another element of employee engagement that should be tracked is whether the employee senses that he or she is first treated as an individual.

Ironically, it is only when I am first treated as an individual that I have the motivation to perform well as an employee.

Here is a quick test – Who have I recognised for doing a good job in the last seven days?

For your employee engagement data to mean anything, it ought to provide diagnostic linkages back to the day-today behaviour of the managers – else, there is no leading effect to the findings.

The four vital roles of a manager which should be tracked are: • Identify talent • Set expectations • Motivate • Develop

The job factor According to Gallup, employees who have the opportunity to do what he or she does best every day is six times more engaged and three times as likely to have a higher quality of life.

Here is the key – the way to create engagement for the employee is not to talk about the job. In fact, when employees talk about what they do best, they rarely frame the discussion in terms of a job description.

In other words, when an engaged employee talks about his role, he is using terms which describes not a series of tasks to be accomplished, rather it is described in a series of satisfying moments.

A great job is defined as a situation of maximised overlap between one’s role and one’s soul.

The greater the overlap, the greater the job becomes.

Although there are many components that make up a great job like experience, knowledge and skills but the one part that makes that crucial difference is a personal one – it is your unique talents – the way you are naturally wired to think, feel and behave. When my job offers me the opportunity to exercise my unique set of talents, then I am no longer making a living, rather my life is in the making!

Unlike generations ago, when workers come to work for the purpose of finding a meal, today’s workforce is looking to find a sense of meaning.

This appears to be the trend as affluence becomes the norm and the workplace is becoming more than just a place for ‘doing work’, rather it is for doing meaningful work. The mantra appears to be – “I want my work to matter because I want my life to matter”.

The engagement imperative In Gallup’s state of worldwide engagement study (2013), only 13 per cent of employees worldwide are engaged, 63 per cent are disengaged while 24 per cent are actively disengaged. This is a glaring leverage for productivity that most organisational leaders are missing out on.

Instead of purchasing the next greatest tool or system, have you considered a similar investment in improving the level of employee engagement?

Furthermore, without the right levels of employee engagement, even the best possible tools will be under-utilised because technology is only as good as the whole-hearted commitment of the user.

The next time you are planning to ‘data-mine’ the big data of employee engagement, consider the following preparatory steps to ensure that the data becomes meaningful diagnostics for developing great bosses and creating great jobs for employees: • Select a proven engagement survey which links results to managerial behaviour and employee strengths.

For my clients, I recommend Gallup’s Q12 survey.

• Put in place a follow-up managerial development programme which focuses on addressing the gaps identified in the engagement survey.

• Put in place a talent management programme to increase the engagement level of employees with potential for growth.

• Enhance job descriptions to make it more outcome-based so that there is room for the demonstration of unique talents and strengths.

• Enhance the performance appraisal process to focus on strengths while managing weaknesses.

As in most data-driven efforts, it is garbage in, garbage out. With human capital being the most underutilised asset in today’s competitive environment, we dare not treat this subject of employee engagement lightly and approach this from purely an analytical perspective.

After all, isn’t it the right of every human being to be treated as a unique individual? This is the starting point of engagement that works.

Joseph is a Leaderonomics faculty trainer who is passionate about engaging with leaders to transform culture in organisations.

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Are We Ready For Smart Manufacturing?

BY LAY HSUAN, LIM

It’s business as unusual Digitalisation, robotics, automation, Big Data and cloud computing in our personal and professional lives have resulted in us being connected often with our smart devices like our phones, cars, television, and other appliances.

Digitalisation isn’t just affecting end users like us; it’s also shaking up the world of business and manufacturing, turning it upside down and inside out.

‘Upside down’ because no one can really foresee what other disruptive technologies are coming our way or how we are prepared for these changes.

‘Inside out’ because it involves leadership from within the organisation to turn these challenges into opportunities for growth and innovation.

For the longest time, manufacturing has provided many job opportunities for non-skilled workers. It has been a critical force that has helped advance developing nations to become highincome ones.

Some of us still see loads of blue factory buses – the “Bas Pekerja” – on Malaysian roads every working day, as workers are picked up from designated spots to industrial sites.

We wonder if this sight will be a thing of a past in the near future as automation begins to take over some of the work we do.

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A glimpse into smart manufacturing This is nothing less than a paradigm shift in industry: the real manufacturing world is converging with the digital manufacturing world to enable organisations to digitally plan and project the entire lifecycle of products and production facilities.

– Helmuth Ludwig, CEO, Siemens Industry Sector, North America

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I had the rare opportunity last month to visit some of Germany’s leading manufacturing sites with a group of 25 media personnel from Malaysia under the K-Pintar-ESMT programme called “Industry 4.0 and Digitalisation Programme for Media”, thanks to the Human Resources Development Fund and the National Press Club.

Some of the smart manufacturing trends that I observed include:

1. Mass customisation With data integration, players in the automotive industry are able to bridge the relationships between themselves, their suppliers and their customers to offer a more modular experience of producing unique car variants.

The Mercedes-Benz manufacturing plant in Stuttgart helped us catch a glimpse of the future automotive industry, as automation and robotics came alive and worked with ultimate precision on fairly flexible production lines.

The machines worked seamlessly with humans to transform metal and various components into a complete body of artwork as a Mercedes car, custommade for customers from around the world.

2. ‘Servicification’ of manufacturing EOS, an e-manufacturing solutions company in Munich, further wowed us as we witnessed first-hand how Additive Manufacturing technology is used to build complex components for heavy industries using 3D printers, providing ideal business-to-business solutions.

In this digitalised facility, the machines worked autonomously, until you observe what is truly happening inside each working unit.

One of the 3D printers, which uses Direct Metal Laser Sintering, showed us how a laser beam dissolves the metal powder and how it is solidified into a crosssection of the component.

According to our site coordinator, these machines ‘communicate’ with each other through cloud technology and industrial Internet of Things (IoT).

As a solutions provider, EOS technology is simplifying the design and production of complex parts for use in aerospace, medical and other fields.

It also enables its customers to benefit from its integrated services comprising consulting, training, research and development.

How ready are we?

Across the globe, Industry 4.0 seems to promise increased efficiency, reduced costs and greater customer satisfaction.

In Asean, Singapore is ranked at the top of the World Economic Forum’s 2016 Networked Readiness Index, a key indicator of how countries are keeping up with the digital world.

Meanwhile, a 2016 survey conducted by the Federation of Malaysian Manufacturers and Malaysian Institute of Economic Research shows that only 12% of the respondents were fully aware of the Industry 4.0 wave. About 41% were somewhat aware, 28% need more information and 19% were not aware at all.

Other industry experts have opined that our slow uptake could be due to industry players grappling with funding challenges, mindset shift and low expertise.

We are, essentially, still at the 2.0 level (mass production, assembly line) although the global manufacturing in the electrical and electronic sector, for example, is fast evolving with Big Data, IoT and cloud computing.

What can we do to drive a digital mindset in the industy?

1. It starts with leadership Interestingly, in Singapore, it’s the government that is driving digital innovation with initiatives such as Future Ready Singapore blueprint, Smart Nation programme and its e-Government Action Plan.

In many other countries, it’s mostly driven by the private sector.

Are we in danger of being left behind?

Their integrated approach from the government, private and public sectors in a central committee aligns them towards various digitalisation efforts, and that includes participation from digital early adopters like Siemens and General Electric.

Malaysia’s low awareness and adoption of Industry 4.0 aren’t necessarily due to ignorance, but a real business decision on whether the market size or production is big enough for them to embark on these changes, according to Second Minister of International Trade and Industry (MITI) Datuk Seri Ong Ka Chuan.

In a seminar on smart manufacturing and automation organised by the Malaysian Investment Development Authority (MIDA), Minister Datuk Seri Mustapa Mohamed said that MITI is consciously taking several strategic moves to spearhead the adoption of smart manufacturing and Industry 4.0 in Malaysia.

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For example, the government is currently working with industry players on our very own National Industry 4.0 Blueprint, expected to be ready by the end of this year.

2. Infrastructural support system As both the manufacturing and services sector contribute to almost 80% of Malaysia’s gross domestic product, we need to build partnerships with international industry experts from Germany, Japan, Korea, China and Singapore to equip us with the technical know-how, and to collaborate on research and development.

MIDA, for one, is working with Rockwell Automation, a US-based industrial automation and smart technology provider to increase our competitive advantage.

Besides that, the Automation Capital Allowance, which was introduced in the 2015 budget through MIDA has helped various industry players optimise its automation initiatives. A case in point is a local clothing manufacturer which

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successfully increased its production volume by over 300%, while reducing defect rate by 80–90%.

Our pace of Industry 4.0 adoption today doesn’t justify how or what we can achieve in the near future.

MITI had also pushed for the inclusion of an incentive in the national budget to spur growth of the automation ecosystem among local manufacturers and accelerate the Industry 4.0 transformation in the country.

Steadily, with concerted efforts from all players to prepare Malaysia to enter the future of smart manufacturing, I believe we can all get there – and only if our belief corresponds with our willingness to embrace technology.

Bringing it together Smart manufacturing is a different ball game which requires deeper analytical thinking, partnerships, knowledgesharing, communication and creative problem-solving.

Not jumping on the bandwagon of Industry 4.0 means the end of our manufacturing’s growth opportunity and innovation.

For now, let’s get our act together, and get moving!

* Read our online version to access the hyperlinks to other reference articles made by the author.

Lay Hsuan was part of the content curation team for Leaderonomics.com, playing the role of a content gatekeeper as well as ensuring the integrity of stories that came in. She was an occasional writer for the team and was previously the caretaker for Leaderonomics social media channels. She is still happiest when you leave comments on the website, or subscribe to Leader’s Digest.

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Read more about the National Policy on Industry 4.0 at:

https://iotworld.co/2018/10/31/industry-4wrd-malaysia-national-policy-on-industry-4-0/

or scan the QR code below for quicker access:

Issue 21 | December 2018

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