Parsable: key drivers for industrial decisions in 2020
Increase in the priorit...
Manufacturing Global takes a look at Parsable’s key drivers for business decisions within the manufacturing industry for 2020.
Increase in the priority of capturing human activity data
To improve the productivity, quality and safety within industrial companies, the sector is expected to raise the priority of capturing human activity data, and to open up new opportunities for the application of machine learning.
For many years, machine learning was centered around using algorithms and models to identify patterns and make decisions with minimal human intervention.
Key steps made so far:
The digitalisation of paper-based standard operating procedures to collect data.
Data analysis: look at what, why and how something happened in order to identify trends and predict future behaviours.
New ways machine learning is being applied - which will be seen more throughout 2020 - is the interaction and exchange of human activity data with ‘intelligent’ machines and platforms, with human behaviour informing prescriptive next best actions.
“According to PwC, manufacturers’ adoption of machine learning and analytics to improve predictive maintenance will increase by 38% by 2022.”
Sustainability across the value chain
Parsable predicts that across the entire value chain, sustainability will be a key driver in technology decision making to improve operational efficiency and reducing waste, which will become mandatory.
Organisations no matter how big or small will be held accountable to maintain sustainability from customers, investors, partners and the general public. Something which is increasingly being used to define a trustworthy company.
Batch of one
‘Batch of one’, is the new norm for manufacturing as the increase in consumers demanding choice, resulting in manufacturers being required to rapidly deploy agile and mobile-first worker platforms.
As companies gain greater visibility on their customer needs and wants, the manufacturing industry will be under pressure to address the niche markets and preferences faster than ever. However, many manufacturers are lacking the equipment designed to handle the variability. During 2020, companies will need to address ways to handle quicker transitions between production runs and how to make line changeovers a continuous exercise. However, in order to achieve this increased efficiency and agility, manufacturers could face an increase in potential equipment malfunction, safety incidents and deviations from standard operating procedures, something which they need to be prepared for.
As the correlation between safety to quality and overall operational efficiency becomes increasingly clear: Parsable highlights that Safety is becoming a true C-suite issue.
Whilst workplace safety should always be a top priority, in recent years workplace safety has increasingly come to the forefront of industry focus, and in 2020 this will reach new heights. Parsable predicts that the industry should see increased attention on safety culture, worker protection and regulations as the impact of safety on quality and efficiency becomes increasingly important.
From the top-down leaders will demand an increase in transparency and proactivity to enforce and improve worker safety, which will include the investment in technology.
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Gartner: Leaders Lack Skilled Smart Manufacturing Workers
With organisations rapidly adopting industry 4.0 capabilities to increase productivity, efficiency, transparency, and quality as well as reduce cost, manufacturers “are under pressure to bring their workforce into the 21st century,” says Gartner.
While more connected factory workers are leveraging digital tools and data management techniques to improve decision accuracy, increase knowledge and lessen variability, 57% of manufacturing leaders feel that their organisations lack the skilled workers needed to support their smart manufacturing digitalisation plans.
“Our survey revealed that manufacturers are currently going through a difficult phase in their digitisation journey toward smart manufacturing,” said Simon Jacobson, Vice President analyst, Gartner Supply Chain practice.
“They accept that changing from a break-fix mentality and culture to a data-driven workforce is a must. However, intuition, efficiency and engagement cannot be sacrificed. New workers might be tech-savvy but lack access to best practices and know-how — and tenured workers might have the knowledge, but not the digital skills. A truly connected factory worker in a smart manufacturing environment needs both.”
Surveying 439 respondents from North America, Western Europe and APAC, Gartner found that “organisational complexity, integration and process reengineering are the most prevalent challenges for executing smart manufacturing initiatives.” Combined they represent “the largest change management obstacle [for manufacturers],” adds Gartner.
“It’s interesting to see that leadership commitment is frequently cited as not being a challenge. Across all respondents, 83% agree that their leadership understands and accepts the need to invest in smart manufacturing. However, it does not reflect whether or not the majority of leaders understand the magnitude of change in front of them – regarding technology, as well as talent,” added Jacobson.
Technology and People
While the value and opportunities smart manufacturing can provide an organisation is being recognised, introducing technology alone isn’t enough. Gartner emphasises the importance of evolving factory workers alongside the technology, ensuring that they are on board in order for the change to be successful.
“The most immediate action is for organisations to realize that this is more than digitisation. It requires synchronising activities for capability building, capability enablement and empowering people. Taking a ‘how to improve a day in the life’ approach will increase engagement, continuous learning and ultimately foster a pull-based approach that will attract tenured workers. They are the best points of contact to identify the best starting points for automation and the required data and digital tools for better decision-making,” said Jacobson.
Long term, “it is important to establish a data-driven culture in manufacturing operations that is rooted in governance and training - without stifling employee creativity and ingenuity,” concluded Gartner.