helps connect siloed processes, systems, and technologies together to provide real-time data analytics and best practices. By integrating every facet of the product lifecycle on a single-platform solution, can be streamlined and embedded with data to highlight opportunities to improve, automate, and expand.

As backend processes communicate with people and equipment in the field, managers can gain greater organisational visibility, gaining oversight of important enterprise data and real-world information that could impact the business, such as traffic, weather, customer demands, and feedback. Furthermore, equipment equipped with intelligent IoT sensors can measure vital usage metrics to improve equipment’s longevity.

The (IoT) is an idea easily thrown around but often misunderstood in terms of capabilities. IoT sensors provide the capacity to monitor, collect, analyse, and manage data in real time from critical business equipment. This ability to respond and adapt means equipment can and automatically trigger service and maintenance actions to minimise business impact. Business leaders can thereby make decisions when they matter most, planning and forecasting with greater accuracy and broader horizons.

With business transparency that feeds data into a centralised system, businesses have access to tighter resource management and control. This helps minimise waste while optimising processes and resource usage, which is critical at a time when the energy and resources sector must consider more sustainable options to continue thriving – both commercially and within the experience economy.

As the world becomes more socially and environmentally conscious, our industry needs to be ever mindful of the impact we’re having in the regions we operate and on the people we service. This shift alongside the digitalisation of communication platforms means businesses are under more scrutinous eyes than ever, which has led to more customer-centric practices across different industries. The amount of competition, communication channels, and information sources ensures customers have more buying power to influence an organisation’s success.

The digital transformation of supply and communication networks has driven many providers and brands to more personalised offerings, unlocking the value of critical business data to forecast better, service consumers more proactively, and discover best practices by connecting disparate systems to a single source of truth.

integrate all data sources and processes onto a unified system for better organisational oversight and management. This opens the path for next-generation efficiencies across the business, linking different industries, organisations, and data sources to create a more holistic understanding supported by data-rich environments that evolve with changing business needs.

Within that , Â鶹ԭ´´ highlighted four areas for introducing more intelligent technologies and practices into the energy and resources sector that I would like to outline and explore further.

1. ‘Extending beyond the barrel’ means putting intelligence, data analytics, and best practices into every stage of the resource lifecycle. In centralising these various functions and processes, businesses can simplify order commitment and fulfilment using live-investment management, real-time availability, and faster material replenishment. Data analytics and IoT sensors help extend our understanding beyond standard resource and operational touchpoints.

2. ‘Digitalising production and delivery’ provides a 360-degree view of businesses and supply networks, making it easier to track and analyse all inputs and outputs. Digital transformation also empowers staff with the technology to work remotely through mobile-enabled applications. With a digitally supported workforce, businesses can operate more seamlessly and safely, especially during restrictive circumstances that require constant connection, communication, and verification.

3. ‘Competing as an ecosystem’ is vital in facilitating collaboration and elevating the quality of our industry’s practices, technologies, and environmental impact. The energy and resources sector must explore opportunities and partnerships outside of our industry boundaries to development more sustainable solutions. As we connect systems and networks to build a digitally powered ecosystem, our industry can build upon base capabilities and develop best practices. With a collaborative platform for sharing data insights, we can optimise processes regardless of industry sector to elevate the collective efforts towards productivity, profitability, and sustainability.

4. ‘Unlocking value with technology’ is a culmination of the other points I’ve discussed here. With intelligent technologies like predictive analytics, machine learning, and blockchain, our industry can reduce wasted time and resources spent on legacy processes and manual tasks. Intelligent technology is the most comprehensive way to create value through efficiencies and data-backed decision making. Using real time collaborative visibility and continuous innovation, these intelligent solutions evolve with our needs and changes.

COVID-19 has had widespread impact across national borders and industries, continuing to restrict the movement of goods and people. Intelligent supply chains present a strong blueprint for digitalising our everyday processes.

Data-embedded functionality sets the foundation for digitalisation and automation – not only allowing businesses to operate seamlessly and intelligently but helping managers plan for an uncertain future. This is paramount as we adopt the vital lessons and accelerations brought on by COVID-19, using the momentum of this pandemic to make more bold and informed decisions to thrive in time of uncertainty.

The post The Digitalisation of Supply Chains: Natural Resources’ Role in Thriving Post COVID-19 appeared first on Â鶹ԭ´´ Australia & New Zealand News Center.

In this modern era of continuous technological improvement and instant gratification, keeping up with customer demands is proving increasingly challenging for everyday businesses. Customers now expect easy ordering, faster delivery times and a personalised level of service. Evidently, in the last few months, we have seen the closure of large retailers in Australia who have failed to meet customer needs and expectations.

is becoming more important as customers are not just looking to buy the products alone but rather the experience around them. The perfectly illustrates this point, while the mode of transportation is the same, what airlines primarily compete on is customer experience. Emirates, one of the highest ranked airlines clearly understands the value of customer experience.

As well as being the first to install TV screens on every seat on every aircraft, they offer a number of small customer perks that really add up. They offer great flexilibilty, with online flight check-ins opening 2 days in advance and convenience, as customers travelling across all classes can check in their luggage from anywhere in Dubai.

So, how can we bring an exceptional customer experience to our brand and products?
To answer this, we need to first better understand what our customers want and why they want them. There are two main approaches to better understand your consumer needs. One is to look at the myriad of Operational data (O-data) the businesses have collected.

This operational data may include past transactions, customer demographics, purchasing behaviour, and many more. Many organisations are now analysing and leveraging customer data to make informed business decisions. Many have also gone a step further by setting up a data division headed by a whose role is evolving.

The other approach is to directly ask customers for feedback whether it be through customer surveys, interviews, focus groups, etc. The collected data, also known as the Experience data (X-data), helps businesses to understand customer sentiment and values. By combining the O and X data, it provides powerful knowledge to the businesses to understand what their customers really want and why they want it.

Many businesses are becoming aware of the and so they have started their eXperience Management (XM) journey. For example, through Qantas’s Voice of Customer (VoC) program, it has introduced new innovative products such as wifi on board, project sunrise, world’s first waste free flight, etc.

Qantas has just brought all disparate platforms and processes across its business units in a single Qualtrics platform. Moreover, Qantas brought together their experience and operational data to help them better understand how its customers interact with the check-in systems and to personalise the experience offered. There are more examples on how XM enables businesses to innovate.

Now that we have both O+X data, how can we realise its benefits?
The key here is to understand what’s possible with this data and how to effectively process and turn raw data into actionable insights that support business processes. Machine Learning and Artificial Intelligence (AI) are that allow you to mass crunch large datasets in a short period of time.

Below are common use cases across various industries, where companies have been able to leverage their O+X data to gain a competitive advantage.

Text Analytics
It is quite common nowadays for organisations to employ machine learning techniques to analyse qualitative data such as customer surveys, product feedback, and social media. This Experience data enables organisations to discover core customer values and needs. The feedback is even more effective when we analyse them against demographics data.

For example, if a shoe company knows that a demographic group places a high emphasis on comfort. Then they would focus more on the quality of the materials rather than creating stylish outward appearance for such group. A better understanding on your target market can directly translate into tangible financial rewards like increase in sales and revenue. Additionally, it can improve intangible aspects of an organisation such as reputation and customer satisfaction.

Predicting and Understanding Customer Behaviour
Operational data from customer transactions enable organisations to understand buying patterns of their customers. By applying intelligence technologies on top of O+X data, organisations can predict the future buying behaviour of their customers like which new products will appeal to particular demographics. Early and accurate prediction allows organisations to be at the forefront of trends and take advantage of them.

Personalisation
Personalising customer experience includes offering products and services tailored to customer preferences. Many online platforms such as Amazon, Netflix and Marriott International employ machine learning to offer personalised recommendations based on customer past buying patterns. Furthermore, we also see personalisation embedded in every aspect of the customer journey.

For example, a chatbot that does not only answer customer queries but has an intelligence to combine Operational and Experience data to provide a unique customer experience. It combines and stores your past information, such as past product complaints and purchases, brand preferences, product enquires and which staff served you. Equipped with this information, it can tailor its responses to resolve your current issue quicker and more hassle-free.

Augmenting Shopping Experience
Artificial Intelligence is now becoming ubiquitous in a retail environment to improve customer satisfaction. A number of retailers have started looking into implementing Smart Mirrors in their stores. A smart Mirror uses computer vision, touch and recommendation technologies to augment customer buying experience, for example, the option of trying on clothes digitally.

The mirror can automatically detect customer sentiment on the digital clothes they try and collect this Experience data. If combined with Operational data such as customer past transactions, the smart mirror can recommend products that customers are likely to purchase, thus, creating a seamless, easy shopping experience.

Get more insights on how

The post Embedding Intelligence to Win in the Experience Economy appeared first on Â鶹ԭ´´ Australia & New Zealand News Center.

In recent times we have seen the power that exciting bring to increasing this impact – concepts such as machine learning, Blockchain and IoT are enabling businesses to embed capabilities such as prediction, security, sensing and automation within their processes.

The current focus of many digital transformation programs is on increasing the efficiency of company operations by embedding these technologies into “business as usual� processes, including:

– The use of machine learning to increase the accuracy and speed of many finance functions.

– IoT lowering the labour required to inspect and manage assets.

– Analytics unveiling insights that lead to better informed company growth plans, enabling the development of new strategies and in turn driving revenue.

In other words, current digital transformation programs are enabling companies to move from performing business processes to predicting how best to operate their business. With the cost of hardware such as cameras rapidly dropping, further use cases involving machine vision are also emerging, providing ever-increasing amounts of data from which businesses can fuel the efficiency and effectiveness of their operations.

For businesses to become truly however, a comprehensive external view of company operations and place in the market needs to be considered.

In some cases, companies are taking a much more refined view of their regional and industry position and that of their customers, using analytics to discover opportunities to optimise their respective offerings.

The more powerful approach being taken by companies operating at the leading edge of digital is taking a real time to customers and encountered by employees. Whether these companies are operating in the B2B or B2C space, new approaches need to be taken to provide points of market differentiation and improved employee value propositions – the operational technology discussed earlier is now largely commoditised, being critical to the success of a company but not offering any major competitive advantage.

Solutions such as are being used by these digital pioneers to “close the loop� in terms of merging the successful operation of their business processes with the stellar delivery of meaningful experiences.

By being able to fuse the eXperience and Operational data being captured and deriving insights through predictive technology, these companies can become true by proactively managing the experiences enjoyed by customers and employees alike.

Coupled with the ability to gather in-depth feedback on products, services and brands, this fusion of operations, intelligence and experience fuels the much more effective digital transformation of businesses into Intelligent Enterprises with a focus on commercial and customer outcomes, rather than capabilities and processes.

You can learn more on how businesses are becoming Intelligent Enterprises by .

The post Becoming an Intelligent Enterprise – From Operations to Outcomes appeared first on Â鶹ԭ´´ Australia & New Zealand News Center.