Efficient and effective logistics is vital to large Oil & Gas projects – equipment must be transported to work sites and raw products need to be processed and then delivered to customers, often using multiple modes of transport in a complex supply chain. In addition to this complexity, another important part of the overall logistics problem is people logistics – How do we move personnel to and from a worksite both safely and efficiently?

Why should I invest in personnel?

Particularly in Australia, where many work sites exist in remote areas, it is not always feasible to relocate employees and their families to a town near the work site. As a result, many workforce personnel are employed on a fly-in fly-out (FIFO) or bus-in bus-out (BIBO) basis, where the employer is responsible for moving personnel to and from the work site.

2013 report from Ernst & Young indicated that human capital deficit is one of the top ten risks facing the global Oil & Gas industry, affirming that

as the sector develops technologically . . . companies that can retain and mobilize people will be able to sustain their competitive advantage.

Effective and efficient personnel mobilization is crucial to any significant oil and gas project. Research published in 2012 by the Australian Centre of Excellence for Local Government (ACELG) into the prevalence of FIFO in Australia predicts that percentage of Australian mining sector jobs filled by FIFO roles will only increase over the coming years.

Improper workforce utilisation increases susceptibility to many internal and external issues, such as: a high employee turnover, high ongoing operational costs to the business, and under- or over-allocation of staff to specific jobs.

Analytics to cut through complexity

People logistics for a large project requires the coordination of travel and accommodation for hundreds, sometimes thousands of people in various remote locations. As with traditional logistics, several crucial decisions have to be made including BIBO vs FIFO, choice of airports or bus routes and staff roster schedules. In addition to this complexity, working with personnel often requires much greater scrutiny – we don’t always require a minimal-cost solution – we need to balance cost, project risk, employee safety and employee satisfaction.

Trying to weigh up all these variables and make decisions in an intelligent way for all of the personnel involved in a project very quickly becomes complex. A 2014 interview by Mining Australia notes that “for many companies [workforce management] is man­ual, or only semi-automated, which increases the risk of error or processing in­efficiencies, increasing costs”. Managing a large workforce is difficult, and only with the right technology can companies provide efficient and effective workforce management.

Through analytics companies can cut through the complexity involved in workforce management. By considering specific variables and how they affect outcomes companies can make better decisions.

Analytics empowers organisations through quantitative justification so that decision makers can be certain that employees will be spending less time in transit, and working on the right jobs at the right times, with the right people.

Biarri and People Logistics

Biarri delivers consulting and SaaS solutions to provide the right technology to enable effective workforce management.

Biarri has a proven track record, delivering people logistics and FIFO solutions for Oil & Gas and Mining companies in Australia including Santos, BMA, and Arrow Energy.

To learn more about how Biarri can help your organisation benefit from analytics and optimisation for people logistics get in touch today!

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The contemporary customer service landscape has evolved considerably, with businesses continually turning to AI-powered contact center solutions to address rising customer expectations. Current smart contact center platforms blend advanced technology with human experience to deliver superior customer experiences while optimizing operational efficiency. Understanding AI-Powered Contact Centers An AI-powered contact center represents a core shift from legacy call center operations. These artificial intelligence contact center platforms employ intelligent learning customer support capabilities to automate everyday tasks, enhance agent productivity, and offer personalized customer interactions across all contact points. The basis of any advanced contact center solution depends on its ability to manage and evaluate enormous amounts of customer data in immediately. Through language processing contact center technology, these systems can grasp customer intent, identify emotions, and provide appropriate responses that feel intuitive and valuable. Core Technologies Enabling Innovation Advanced Analytics and Intelligence Modern AI customer service platforms incorporate advanced predictive analytics engines that analyze past interaction patterns to predict customer needs. Voice analytics capabilities provide live insights into customer sentiment, facilitating preventive intervention when challenges arise. These systems use emotion detection to evaluate customer contentment levels throughout each engagement. Audio recognition technology has become progressively sophisticated, facilitating seamless vocal identification authentication and accurate instant transcription of customer interactions. 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Chatbot platforms have modernized self-service automation, facilitating customers to fix basic issues without human intervention. Intelligent chatbot integration delivers 24/7 support capabilities while preserving uniform brand voice and service quality. When human intervention becomes required, automated redirection systems deliver seamless handoff experience between automated and human agents. Boosting Customer Experience Customization and Context AI-powered contact centers are superior in delivering personalized customer interactions by utilizing comprehensive experience enhancement tools. These systems maintain extensive interaction records and choices, enabling agents to deliver contextually relevant support from the moment a customer engages. Customer intent recognition capabilities permit systems to comprehend the core purpose of customer concerns, even when expressed in different ways. This understanding allows dynamic scripting that modifies conversation flow based on customer needs and emotional state. Preventive Engagement Preventive outreach embodies a important advancement over responsive support models. AI systems track customer behavior patterns and can initiate outreach when potential issues are discovered. This approach often generates increased single-call resolution rates and higher total service quality improvement. Mood identification technology facilitates instant monitoring of customer stress levels, permitting supervisors to deliver prompt support to both customers and agents when complex situations arise. 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