While the rest of the nation ground to a standstill in 2020, New Zealand’s essential industries went into overdrive. The transport sector worked tirelessly to ensure everyone across the country had access to essential goods. From delivering bulk goods to supermarkets to dropping off grocery deliveries and online orders, it played a vital role in keeping the country moving.
In response to the economic shock, the government began announcing national infrastructure plans and funding for local governments to spend on upgrading water infrastructure, leading to jobs in the construction industry and stimulation for the economy.
However, this year has resulted in changes driven by COVID-19. Businesses accelerated their digital capabilities to adapt to remote work and achieve financial sustainability.
In 2021, organisations across transport, construction and local government will be contending with the ongoing impacts of the pandemic and new ways of working that are here to stay.
Here’s how they can harness the power of artificial intelligence (AI) and smart technology to stay ahead of the curve and deal with disruption.
Before the pandemic struck, construction consultants were projecting a shortage of about 57,600 workers. Work is urgently underway to train workers and reconfigure industry staffing needs. The Infrastructure Commission notes that there is $47 billion of work underway, with 1616 projects by 82 organisations.
Despite the anticipated growth of the industry and many recently announced projects, the building and construction industry still faces a productivity problem. The global industry is amongst the least digitised of all industries and that is mirrored in New Zealand too. A recent report by BRANZ states that improved accuracy of standardised and digitised information is a key source of productivity gain. This is because of reduced paperwork, information search time and costs.
Without effective asset and resource management, construction businesses risk stretching staff thin across various worksites in an attempt to manage demand. Smart fleet management systems driven by AI and machine learning offer a clear and comprehensive picture of where your plant and vehicles are at any given time. If an urgent job comes in, you can check onsite utilisation and assign the nearest operator to the task. This boosts customer service by ensuring the job is completed as quickly as possible.
Fleet management systems paired with GPS location tracking also allow construction managers to effectively manage their assets. You’ll know when a certain piece of machinery is being used extensively, or if it’s sitting idle, you can send it to a job site where it’s needed most.
You can also see how your assets are being used, so if there’s a piece of equipment that gets regular use, you might choose to own it outright instead of renting it.
Local governments are faced with a busy programme of ‘shovel-ready’ infrastructure projects and resource management reviews in the next five years. However, with COVID-19, the sector has been impacted by barriers like major income-loss from airports and services, plus constrained abilities to increase rates.
Thankfully, AI-driven fleet management systems are making it easier for local governments to lower costs and boost productivity with big data. The operations team can optimise their productivity by tracking the real-time whereabouts of each and every asset – from lawn mowers to road works machinery. The team can get insight into machine usage to better understand the utilisation of each asset – and relocate or substitute with hired equipment if needed.
Historical data like waste management routes can be pulled up and viewed at any time, and AI-powered telematics systems let you see where you can optimise your routes to improve services for the community. A GPS-based solution can give a better, more granular understanding of fuel and vehicle costs, which can assist on improving budget management.
As well as productivity, service level and budgets, councils are becoming increasingly aware of the impact of climate change, and our largest councils are making major commitments to cutting their greenhouse gas emissions. AI comes into play here too, with data provided by AI-powered fleet management systems highlighting environmentally unfriendly behaviours, such as excessive idling or the total CO2 output of a diesel-based fleet, to ensure councils keep their green strategies on track.
Real-time AI-based analytics show fuel consumption per vehicle, and managers can see when vehicles are idling or speeding – both of which contribute to unnecessary fuel use.
Digital-based solutions, such as checklists, sign off sheets, maintenance schedules, and even electronic RUC licencing can reduce the amount of paperwork flowing through the organisation. By reducing paper waste, a council can further reduce its environmental footprint.
Road freight services have always been important, but in the crunch weeks around the nationwide lockdown, spending in supermarkets and dairy’s rose as much as 60% over a seven day period. While most COVID-19 cases are caught at the border, many of the restrictions set in place during the pandemic will be sticking around for a while, from rigorous on-site requirements to ongoing border restrictions and regular testing of businesses that engage with New Zealand’s ports and airports.
Operators working with exporters are now faced with big fluctuations in work due to major disruptions to global supply chains. In December 2020, 800 trucks and drivers transported almost 1200 containers from Northport in Whangarei to Auckland, due to a container ship diverting from the Ports of Auckland because of ship traffic in Auckland. With roadworks, Christmas traffic and some windy passages, this was a big task for many operators.
With freight demand continuing in 2021, AI-based systems help to streamline fatigue management to make sure drivers are staying safe and rested while meeting demand. Instead of having to manually enter data into written logbooks, when you use an electronic driver logbook all work and rest information is quick to enter in, and the timing information is viewable at a glance. A proactive fatigue management strategy allows operators to manage multiple driver schedules while also letting drivers take fatigue management into their own hands.
As 2021 ramps up, organisations across construction, local government and transport are looking to the future. Advancements in technology like AI and machine learning are helping these companies overcome potential threats and obstacles by offering data transparency, reducing data entry, and allowing workers to self-manage fatigue.