IoT is also being used for predictive maintenance and in enhancing employee safety. Smart sensors can monitor parameters such as vibrations, temperature and moisture, and detect abnormal behaviours in equipment – helping field workers to make maintenance decisions in real-time, enhancing their safety.
GIS is being used to get spatial data and map project distribution plans for water, sewage, and electricity. For instance, India’s Restructured Accelerated Power Development & Reforms Program (R-APDRP) government project involves mapping of project areas through GIS for identification of energy distribution assets including transformers and feeders with actual locations of high tension and low tension wires to provide data and maintain energy distribution over a geographical region. R-APDRP is also focused on reducing power loss.
Transparency and Efficiency using Blockchain
Blockchain-based systems are helping the Utilities industry in centralising consumer data, enabling information sharing across key departments and offering more transparent services to consumers.
Energy and Utilities companies are also using the technology to redistribute power from a central location and form smart contracts on Blockchain for decisions and data storage. This is opening opportunities for the industry to trade on energy, and create contracts based on their demand and supply. US-based Brooklyn Microgrid, for example, is a local energy marketplace in New York City based on Blockchain for solar panel owners to trade excess energy generated to commercial and domestic consumers. In an initiative launched by Singapore’s leading Power company, SP Group, companies can purchase Renewable Energy Certificates (RECs) through a Blockchain-powered trading platform, from renewable producers in a transparent, centralised and inexpensive way.
Blockchain is also being used to give consumers the transparency they demand. Spanish renewable energy firm Acciona Energía allows its consumers to track the origin of electricity from its wind and solar farms in real-time providing full transparency to certify renewable energy origin.
Intelligence in Products and Services using AI
Utilities companies are using AI & Automation to both transform customer experience and automate backend processes. Smart Meters, in itself, generate a lot of data which can be used for intelligence based on demographics, usage patterns, demand and supply. This is used for load forecasting and balancing supply and demand for yield optimisation. It is also being leveraged for targeted marketing including personalised messages on Smart Energy usage.
Researchers in Germany have developed a machine learning program called EWeLiNE which is helping grid operators with a program that can calculate renewable energy generation over 48 hours from the data taken from solar panels and wind turbines, through an early warning system.
Niche providers of Smart Energy products have been working with providing energy intelligence to consumers. UK start-up Verv, as an example, uses an AI-based assistant to guide consumers on energy management by tracing the energy usage data from appliances through meters and assisting in reducing costs. Increasingly, Utilities companies will partner with such niche providers to offer similar services to their customers.
Utilities companies have started using chatbots and conversational AI to improve customer experience. For instance, Exelon in the US is using a chatbot to answer common customer queries on power outages and billing.
While the predominant technology focus of Utilities companies is still on cost optimisation, infrastructure management and disaster management, the industry is fast realising the power of having an interconnected system that can transform the entire value chain.
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Cloud adoption, especially in the small and medium enterprise (SME) sector is expected to continue to rise. The Ecosystm Business Pulse Study shows that only 16% of Australian organisations had not increased their cloud investments after the COVID-19 crisis and its impact on the economy.
Ecosystm Principal Advisor, Tim Sheedy says, “The current pandemic has highlighted the digital ‘haves and have nots’ in Australia. The NBN has helped to narrow the gap, but too many in rural and regional Australia continue to suffer the tyranny of distance. Businesses and government departments have been reluctant to relocate outside of the major cities due to the lack of internet and data centre infrastructure. Investing in data centres in rural and regional locations will not only help to close the digital divide but also remove a significant barrier that stops businesses from investing in and relocating to locations out of cities.”
Growing Australia’s Data Centre Footprint
This week, Australia’s Leading Edge Data Centres and Schneider Electric announced a AU$30 million project where Schneider Electric will provide Tier-3-designed prefabricated data centre modules for Leading Edge’s six locations in Australia. Each site will host 75 racks with 5kW power density to support computing operations and minimise data exchange delays. Ecosystm Principal Advisor, Darian Bird says, “The inaccessible nature of some sites makes them suitable for prefabricated data centres, which are plug-and-play containers that can be set up and maintained by a relatively small IT team. Standardisation in edge data centres and automation are key to remote management for anyone deploying distributed infrastructure.”
This announcement follows the news that Leading Edge has secured an investment of AU$20 million from Washington H. Soul Pattinson to construct 20 Tier-3 data centres across Australia. They have also received funding from the SparkLabs Cultiv8 2020 accelerator group. The funding will be used to build more than 20 Tier 3 data centres across regional Australia to provide faster internet speeds and direct cloud connectivity.
This will impact businesses that host mission-critical applications, and stricter uptime requirements, and is expected to benefit IoT, AgriTech and telecom industry applications.
Impact on Industry
Edge connectivity will create a seamless experience for the users to take advantage of faster computing with a local host, lower latency by taking connectivity to where operations reside, and data sovereignty by keeping data within the region, aiding in the development of Australia’s Digital Economy.
Sheedy sees this as an opportunity for primary industries. “One of the real challenges for farms and other agribusinesses investing in IoT and other tech-based solutions has been the lack of local or nearby computing infrastructure that will support applications that require low latency. Leading Edge’s investments in providing data centres in rural and regional Australia will mean these businesses can accelerate their digital transformations.”
With the simultaneous rollout of 5G, Smart City initiatives will also benefit from edge data centres. “Investment in edge infrastructure is likely to take off and follow the 5G coverage map across Australia. We will see operators take advantage of their vast network footprint and combine micro data centres with some 5G antenna locations,” says Bird. “Smart City initiatives will be made possible by 5G connected IoT devices but computing at the edge will be needed to keep, for example, public safety systems, operating in real-time. Many monitoring systems will require local data analysis to be effective.”
Bird also sees potential impacts on the Entertainment industry. “The COVID-19 restrictions and the launch of new services such as Disney+ and Binge in Australia will ensure streaming video continues its impressive growth trajectory. Even facilities such as sports stadiums are beginning to deliver in-person digital experiences to grab back attention from their online competitors. Positive user experience is crucial here and low latency is a must. We’ll see a shift towards edge computing delivered on-site as part of a distributed network. Regional data centres and local caching have always been vital for content delivery to ensure the quality of service and reduce bandwidth costs but the scale is unprecedented.”
Bird talks about potential retail opportunities in the future. “We may see anchor tenants at malls offering their excess capacity to smaller, nearby stores that need the benefits of edge but can’t justify the investment, similar to the way Amazon launched AWS.”
Today’s crisis creates opportunities for platforms such as ProperyGuru to engage customers throughout their journey. It can potentially transform the residential property business, by becoming an Uber-style platform for agents, movers, shippers, storage companies, interior designers, renovation firms and all other stakeholders within the residential property ecosystem. Subject to regulation, it could also act as a mortgage broker and an agency for the exchange of contracts. In other words, it could ‘own’ the customer journey and act as a platform for all services associated with residential property. From the customer perspective, such a platform would be a welcome way of enhancing the experience associated with buying, renting, maintaining, improving, managing, and selling residential property.
IoT and the Commercial Property Sector
From a commercial property perspective, the COVID-19 crisis can also be expected to accelerate the digitalisation of many activities associated with the construction, maintenance, and management of buildings.
According to the findings of the Ecosystm IoT Study, the Construction industry is evaluating several technology solutions that are expected to benefit the industry (Figure 1).
While the industry views these solutions as beneficial, the adoption has so far been low. This will change. Drones have been used to inspect the outside of tall buildings for several years, but this is not yet standard practice. Structural inspections and maintenance of buildings will be automated at a much faster rate post COVID-19. IoT technology will be used for building management. Using IoT technology for the predictive maintenance and management of lighting, climate control, elevators, security, windows and doors will become standard as firms seek to reduce human interactions. Technology that measures footfall, manages safe distancing, takes peoples’ temperatures and identifies those who enter and leave buildings will be introduced, as organisations guard against disease clusters developing within or around their premises.
In essence, the COVID-19 crisis will act as a catalyst for the digital transformation of the property sector. There is a huge opportunity to create new business models not least by offering customers a digital platform on which all of their property-related needs can be addressed. For the commercial property sector, a similar platform can be offered. Additionally, many core activities ranging from construction to building management will be automated, fully leveraging robot, AI and IoT technologies.
Milroy was recently part of a conversation with Hari V Krishnan, Group CEO of ProperyGuru Group and Ecosystm CEO, Amit Gupta. Watch the video here 👇
Most government projects involve several stakeholders and are complex in terms of the data, infrastructure and investments required. To take better decisions in terms of project complexity, risks and investments, public sector agencies need to have a structured project management framework, using an optimum mix of physical. technical, financial and human resources. In an environment where citizens expect more accountability and transparency, and where projects are often funded by citizens’ taxes, running these projects become even more complicated. Government agencies struggle to get funding, optimise costs (especially in projects that run over multiple years and political environments), and demonstrate some form of ROI. There is also an overwhelming requirement to detect and prevent frauds.
The global Ecosystm AI study reveals the top priorities for public sector, that are focused on adopting emerging technologies (Figure 1). It is very clear that the key areas of focus are cost optimisation (including fraud detection and project performance management) and having access to better data to provide improved citizen services (such as public safety and predicting citizen behaviour).
Technology as an Enabler of Public Sector transformation
Several emerging technologies are being used by government agencies as they look towards DX in the public sector.
The Push to Adopt Cloud
To prepare for the data surge that governments are facing and will continue to face, there is a push towards replacing legacy systems and obsolete infrastructure. The adoption of cloud services for data processing and storage is helping governments to provide efficient services, improve productivity, and reduce maintenance costs. Moreover, cloud infrastructure and services help governments provide open citizen services. The Government of India has built MeghRaj, India’s national cloud initiative to host government services and applications including local government services to promote eGovernance and better citizen services. The New Zealand Government has sent a clear directive to public sector organisations that public cloud services are preferred over traditional IT systems, in order to enhance customer experiences, streamline operations and create new delivery models. The objective is to use public cloud services for Blockchain, IoT, AI and data analytics.
Transparency through Communication & Collaboration technologies
Since the 1990s, the concept of eGovernment has required agencies to not only digitise citizen services but also work on how they communicate better with their citizens. While earlier modes of communication with citizens were restricted to print, radio or television, digital government initiatives have introduced more active communication using mobile applications, discussion forums, online feedback forms, eLearning, social media, and so on. Australia’s Just Ask Once allows citizens to access information on various government services at one place for better accessibility. More and more government agencies are implementing an omnichannel communication platform, which allows them to disseminate information across channels such as web, mobile apps, social media and so on. In the blog The Use of Technology in Singapore’s COVID-19 Response, Ecosystm analysts spoke about the daily updates shared by the Government through mobile phones. Demonstrating cross-agency collaboration, the information disseminated comes from multiple government agencies – the same channel is also used to drip-feed hygiene guidelines and the evolving government policies on travel, trade and so on.
AI & Automation for Process Efficiency and Actionable Intelligence
Governments are focusing on leveraging centralised resources and making processes smarter through the adoption of AI platforms. Initiatives such as the Singapore Government’s concept of Single Sources of Truth (SSOT), where all decision-making agencies have access to the same data, is the first step in efficient AI adoption. Singapore’s government agencies also have three data aggregators – Trusted Centers (TCs). This enables initiatives such as Vault-Gov.SG which allows government officials to browse a metadata catalogue and download sample data to run exploratory analytics. To push the adoption of AI, several governments are focusing on roadmaps and strategies such as Singapore’s National AI Strategies to transform the country by 2030, and the Government of Australia’s AI Roadmap and framework to help in the field of industry, science, energy, and education.
The first step of AI adoption is often through automation tools, such as virtual assistants and chatbots. The US Citizen and Immigration Service (USCIS) introduced an AI powered chatbot Emma to better support citizens through self-service options and reduce the workload of their customer service agents. The department of Human Services in Australia rolled out various chatbots named Roxy, Sam, Oliver, Charles and the most latest in progress PIPA (Platform Independent Personal Assistant) to provide information on various services and assist on queries.
Real-time data access with IoT
Governments have the responsibility of enforcing law and order, infrastructure management and disaster management. Real-time information data access is key to these initiatives. IoT sensors are being used in various government applications in object detection, and risk assessment in cities as well as remote areas. For example, IoT-enabled traffic monitoring and surveillance systems are embedded to provide real-time updates and continuous monitoring that can be used to solve issues, as well as provide real-time information to citizens. In a futuristic step, the US Department of Transportation (USDOT) is working with auto manufacturers on embedding vehicle to vehicle communication capabilities in all vehicles to avoid collision with emergency braking and vehicle speed monitoring. In an effort to promoting smart city initiatives and for infrastructure maintenance, New Zealand has installed smart cameras with automated processing capabilities, and IoT based street lighting system. IoT has tremendously benefited the supply chain and logistics sector. The US Army’s Logistics Support Activity (LOGSA) is using IoT for one of the Government’s biggest logistics systems. and military hardware with on-board sensors to analyse data directly from the vehicles for better asset maintenance. Again like in AI, there is a need for a clear roadmap for government adoption of emerging technologies, especially considering the safety and ethics angle. The Government of UK has introduced IoTUK, a program to help the public sector and private enterprises to come together and develop IoT technologies considering aspects such as privacy, security, and reliability.
Blockchain enabled Traceability & Transparency
Moving paper-based systems to digitised systems makes processes efficient to a degree. However, more is required for full traceability and transparency. Managing the data flow and safeguarding the information is vital for government organisations, especially as there is an increase in cross-agency collaboration. Government agencies and departments across the globe are increasingly collaborating using Blockchain technology, while at the same time maintaining the security of the data. For instance, in Georgia, the government department of Land, Property and Housing Management is using Blockchain to maintain land and property records. The blockchain-based land registry allows speedier approvals with no involvement of paperwork or multi-party signatures on physical documents. This is enhancing service quality while offering better security measures as the data is digitally stored in the National Agency of Public Registry’s land title database. Estonia is using Blockchain to protect their digital services such as electronic health records, legal records, police records, banking information, covering data and devices from attacks, misuse, and corruption.
Technology-led digital transformation has become the norm for public sector organisations across both emerging and mature economies. However, agencies need to create clear roadmaps and frameworks, including RoI considerations (which may not only be financial but should include citizen experience) and avoid ad-hoc implementations. The key consideration that government agencies should keep in mind is citizen security and ethics when adopting emerging technologies.
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Going back to my previous statement about rubbish and social media, the validation and quality of data exchange is part of the value proposition of using mobile technology.
What aspects of our current IT infrastructure create that ‘data value add’?
IoT and Edge Computing. Most of us are not going to be comfortable in crowds going forward. If I can reserve a space, or I can use a sensor to see how full an environment currently is, it will impact my decision to go somewhere. The faster that real-time information is processed and available, the better the outcome.
Blockchain technology is functioning enough to address the challenge of how to secure the data and prevent malicious cyber-attacks. This includes medical data hacking, supply chain theft, and other data-oriented safety issues on hygiene and product providence that we are experiencing now.
At Ecosystm, we highlight how and where enterprises plan to invest and adopt technology while adding insights and expertise on to the use cases and trends. We are also able to reflect upon the agility of the same enterprises to make that technology investment count towards the next phase of their business model. In a post-COVID situation we see inventive ways enterprises are using technology. This is not only for societal benefit, but to make a difference in the marketplace. And mobile plays a key role in this next phase of engagements.
Yes and no. If we look at the history of the ERP solution, as an example, we find that it was initially meant for and deeply entrenched in Manufacturing organisations. In fact, the precursor to modern-day ERP is the Manufacturing Resource Planning (MRP II) software of the 1980s. Now, we primarily look at ERP as a cross-industry solution. Every business has taken lessons on inventory and supply chain management from the Manufacturing industry and has an enterprise-wide system. However, there are industries such as Hospitality and Healthcare that have their niche vendors who bundle in ERP features with their industry-specific solutions. This will be the general pattern that all tech solutions will follow: a) an industry use case will become popular; b) other industries will try to incorporate that solution, and in the process; c) create their own industry-specific customisations. It is important, therefore, for those who are evaluating emerging technologies to cast their net wide to identify use cases from other industries.
AI and automation is one such tech area where organisations should look to leverage cross-industry expertise. They should ask their vendors about their implementations in other allied industries and, in some cases, in industries that are not allied.
For cybersecurity, their approach should be entirely different. As companies move on from network security to more specific areas such as data security and emerging areas such as GRC communication, it will be important to evaluate industry experience. Data protection and compliance laws are often specific to industries – for example, while customer-focused industries are mandated on how to handle customer data, the Banking, Insurance, Healthcare and Public Sector industries have the need to store more sensitive data than other industries. They should look at solutions that have in-built checks and balances in place, incorporating their GRC requirements.
So, the answer to whether organisations should look for industry expertise in their vendors is that they should for more mature tech areas. An eCommerce company should look for industry experience when choosing a web hosting partner, but should look for experience in other industries such as Banking, when they are looking to invest in virtual assistants.
Are some industries more focused on industry experience than others?
Ecosystm research also sought to find out which industries look for industry expertise more than others (Figure 2). Surprisingly, there are no clear differences across industries. The Services, Healthcare and Public Sector industries emphasise marginally more on industry expertise – but the differences are almost negligible.
There are some differences when we look at specific tech areas, however. For example, industries that may be considered early adopters of IoT – Transportation, Manufacturing and Healthcare – tend to give more credit to industry experience because there are previous use cases that they can leverage. There are industries that are still formulating standards when it comes to IoT and they will be more open to evaluating vendors that have a successful solution for their requirement – irrespective of the industry.
The Healthcare Industry Example
Ecosystm Principal Analyst, Sash Mukherjee says, “In today’s fast-evolving technology market, it is important to go beyond use cases in only your industries and look for vendors that have a demonstrated history of innovation and experience in delivering measurable results, irrespective of the industry.” Mukherjee takes the example of the Healthcare industry. “No one vendor can provide the entire gamut of functionalities required for patient lifecycle management. In spite of recent trends of multi-capability vendors, hospitals need multiple vendors for the hospital information systems (HIS), ERP, HR systems, document management systems, auxiliary department systems and so on. For some areas such as electronic health records (EHR) systems, obviously industry expertise is paramount. However, if healthcare organisations continue to look for industry expertise and partner with the same vendors, they miss out on important learnings from other industries.”
Talking about industries that have influenced and will influence the Healthcare industry in the very near future, Mukherjee says, “Healthcare providers have learnt a lot from the Manufacturing industry – and several organisations have evaluated and implemented Lean Healthcare and Six Sigma to improve clinical outcomes. The industry has also learnt from the Retail and Hospitality industries on how to be customer focused. In the Top 5 Healthtech trends for 2020, I had pointed out the similarities between the Financial and Healthcare industries (stringent regulations, process-based legacy systems and so on). As the Healthcare industry focuses on value-based outcomes, governments introduce more regulations around accountability and transparency, and people expect the experience that they get out of their retail interactions, Healthtech start-ups will become as mainstream as Fintech start-ups.”
It is time for tech buyers to re-evaluate whether they are restricting themselves by looking at industry use cases, especially for emerging technologies. While less industry customisations mean easier deployments, it may also hamper innovation.
In our blog, Artificial Intelligence – Hype vs Reality, published last month we explored why the buzz around AI and machine learning have got senior management excited about future possibilities of what technology can do for their business. AI – starting with automation – is being evaluated by organisations across industries. Several functions within an organisation can leverage AI and the technology is set to become part of enterprise solutions in the next few years. AI is fast becoming the tool which empowers business leaders to transform their organisations. However, it also requires a rethink on data integration and analysis, and the use of the intelligence generated. For a successful AI implementation, an organisation will have to leverage other enabling technologies.
Technologies Enabling AI
Organisations have been evaluating IoT – especially for Industry 4.0 – for the better part of the last decade. Many organisations, however, have found IoT implementations daunting for various reasons – concerns around security, technology integration challenges, customisation to meet organisational and system requirements and so on. As the hype around what AI can do for the organisation increases, they are being forced to re-look at their IoT investments. AI algorithms derive intelligence from real-time data collected from sensors, remote inputs, connected things, and other sources. No surprise then that IoT Sensor Analytics is the AI solution that is seeing most uptake (Figure 1).
This is especially true for asset and logistics-driven industries such as Resource & Primary, Energy & Utilities, Manufacturing and Retail. Of the AI solutions, the biggest growth in 2020 will also come from IoT Analytics – with Healthcare and Transportation ramping up their IoT spend. And industries will also look at different ways they can leverage the IoT data for operational efficiency and improved customer experience (CX). For instance, in Transportation, AI can use IoT sensor data from a fleet to help improve time, cost and fuel efficiency – suggesting less congested routes with minimal stops through GPS systems, maintaining speeds with automated speed limiters – and also in predictive fleet maintenance.
IoT sensors are already creating – and will continue to create large amounts of data. As organisations look to AI-enabled IoT devices, there will be a shift from one-way transactions (i.e. collecting and analysing data) to bi-directional transactions (i.e. sensing and responding). Eventually, IoT as a separate technology will cease to exist and will become subsumed by AI.
AI is changing the way organisations need to store, process and analyse the data to derive useful insights and decision-making practices. This is pushing the adoption of cloud, even in the most conservative organisations. Cloud is no longer only required for infrastructure and back-up – but actually improving business processes, by enabling real-time data and systems access.
Over the next decades, IoT devices will grow exponentially. Today, data is already going into the cloud and data centres on a real-time basis from sensors and automated devices. However, as these devices become bi-directional, decisions will need to be made in real-time as well. This has required cloud environments to evolve as the current cloud environments are unable to support this. Edge Computing will be essential in this intelligent and automated world. Tech vendors are building on their edge solutions and tech buyers are increasingly getting interested in the Edge allowing better decision-making through machine learning and AI. Not only will AI drive cloud adoption, but it will also drive cloud providers to evolve their offerings.
The global Ecosystm AI study finds that four of the top five vendors that organisations are using for their AI solutions (across data mining, computer vision, speech recognition and synthesis, and automation solutions) today, are also leading cloud platform providers (Figure 2).
The fact that intelligent solutions are often composed of multiple AI algorithms gives the major cloud platforms an edge – if they reside on the same cloud environment, they are more likely to work seamlessly and without much integration or security issues. Cloud platform providers are also working hard on their AI capabilities.
Cybersecurity & AI
The technology area that is getting impacted by AI most is arguably Cybersecurity. Security Teams are both struggling with cybersecurity initiatives as a result of AI projects – and at the same time are being empowered by AI to provide more secure solutions for their organisations.
The global Ecosystm Cybersecurity study finds that one of the key drivers that is forcing Security Teams to keep an eye on their cybersecurity measures is the organisations’ needs to handle security requirements for their Digital Transformation (DX) projects involving AI and IoT deployments (Figure 3).
While AI deployments keep challenging Security Teams, AI is also helping cybersecurity professionals. Many businesses and industries are increasingly leveraging AI in their Security Operations (SecOps) solutions. AI analyses the inflow and outflow of data in a system and analyses threats based on the learnings. The trained AI systems and algorithms help businesses to curate and fight thousands of daily breaches, unsafe codes and enable proactive security and quick incident response. As organisations focus their attention on Data Security, SecOps & Incident Response and Threat Analysis & Intelligence, they will evaluate solutions with embedded AI.
AI and the Experience Economy
AI has an immense role to play in improving CX and employee experience (EX) by giving access to real-time data and bringing better decision-making capabilities.
Enterprise mobility was a key area of focus when smartphones were introduced to the modern workplace. Since then enterprise mobility has evolved as business-as-usual for IT Teams. However, with the introduction of AI, organisations are being forced to re-evaluate and revamp their enterprise mobility solutions. As an example, it has made mobile app testing easier for tech teams. Mobile automation will help automate testing of a mobile app – across operating systems (Figure 4). While more organisations tend to outsource their app development functions today, mobile automation reduces the testing time cycle, allowing faster app deployments – both for internal apps (increasing employee productivity and agility) and for consumer apps (improving CX).
CX Teams within organisations are especially evaluating AI technologies. Visual and voice engagement technologies such as NLP, virtual assistants and chatbots enable efficient services, real-time delivery and better customer engagement. AI also allows organisations to offer personalised services to customers providing spot offers, self-service solutions and custom recommendations. Customer centres are re-evaluating their solutions to incorporate more AI-based solutions (Figure 5).
The buzz around AI is forcing tech teams to evaluate how AI can be leveraged in their enterprise solutions and at enabling technologies that will make AI adoption seamless. Has your organisation started re-evaluating other tech areas because of your AI requirements? Let us know in the comments below.
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The industry also faces the challenge of skills shortage. A survey conducted by the Global Energy Talent Index (GETI) found that nearly 70% of Oil and Gas professionals think the industry is already facing skills shortage or will be hit by it within the next 5 years. This is due to a number of reasons, including a reluctance of younger professionals to commit to a profession that has harsher conditions than many. Moreover, as energy transition becomes a topic of global discussion, many have a perception that the industry is not sustainable in the future. The industry also goes through cycles where they cut back on exploration and production, which results in the loss of skills and inadequate knowledge transfer. It has a long-term challenge around knowledge management.
Safety and environmental regulations
The industry has to contend with green energy movements and environmental regulations. There are several country-level regulations around air and water quality. Most Oil and Gas companies have cross-border operations and have to comply with a number of regulations on harmful emissions, greenhouse gases and offshore activities, in several countries. Increasingly, all leading Oil and Gas companies have to work in alignment with the Paris Agreement when developing solutions across functions – exploration, extraction and supply chain. There are also worker safety regulations and standards that they have to comply with.
The global Ecosystm AI study reveals the top priorities for Oil and Gas companies that are focused on adopting emerging technologies (Figure 1). It is very clear that the key areas of focus are process automation, asset and supply chain management and compliance.
Technology as an Enabler of Oil and Gas Transformation
Several emerging technologies are being used by the Oil and Gas industry as they continue their struggle to remain competitive across the different stages of operations – upstream, midstream and downstream.
As the costs of sensors go down, connectivity widens and computing power increases, the industry is seeing greater uptake of Industrial IoT (IIoT) solutions. From wearables (to monitor employee safety) to drones with smart cameras (for remote inspections, environmental monitoring), IoT solutions have an immense role to play in the Oil and Gas industry. The industry has had to be cautious about the choice of devices, however, due to pervasive inflammable hydrocarbons and the related regulations.
Not only are they implementing sensors, Ecosystm research finds that 30% of Oil and Gas companies are also leveraging the IoT sensor data for analytics and intelligence. A common application is in predictive maintenance. Two years ago, Chevron launched predictive maintenance solutions in its oil fields and refineries. While the pilot ran on heat exchangers, the company aims to connect all assets by 2024 and expects to save millions on asset management.
AI and machine learning have applications across Oil and Gas operations, leveraging IoT sensor data. “Smart fields” where production is monitored centrally, has a high level of automated controls. AI/Analytics is allowing companies to run simulations, use predictive data models and identify patterns to gauge risks associated with new projects. This has an impact on production, exploration and making efficient use of existing infrastructure. Oilfield services company Baker Hughes has worked on an AI-based application that allows well operators to view real-time production data and predict future production with more accuracy.
While the applications of AI in the industry are often focused on upstream activities, AI has applications across all operations. In the midstream, transporting crude oil to refineries has always had its unique challenges. Since transport lead times are long and prices fluctuate based on the availability of products, organisations benefit from demand forecasting and price risk modelling. While the common perception of the industry does not include customer interactions, the truth is that the industry is increasingly focusing on the retail space. The need is enough for Shell to begin experimenting with virtual assistants as far back as in 2015, to interact with their retail customers. In fact, the company anticipates a higher adoption of AI in the industry and is collaborating with Udacity to bridge the skills gap.
Technologies empowering employees
As discussed earlier, one of the key challenges of the industry is the inability to manage a reliable knowledge management system that can help consistent knowledge and skills transfer. A single source of truth that can be accessed by all employees on processes, including safety requirements has an immense role to play to help with the skills shortage in the industry.
Enterprise mobility is another tech area that holds immense potential for the industry, with its huge proportion of mobile workers, many in remote locations. Mobility solutions can help in productivity, process optimisation and monitoring of health and safety of the employees and are increasingly incorporating wearables and location-based services. GIS and GPS systems are helping employees with accurate directions, easier access to drilling locations and more. Given the number of devices, platforms and OSs, the industry is seeing an increased interest in unified enterprise mobility (UEM) solutions. Ecosystm finds that more than a third of Oil and Gas companies have implemented or are evaluating UEM, while another 20% are expressing early interests.
The sheer quantity of documents, transaction records and contracts that a typical Oil and Gas company has to manage – including cross-border transactions – poses some difficulty for the industry. The companies have to reconcile and handle issues involving multiple contractors, sub-contractors, and suppliers. Supply chain and inventory management is also a challenge. With the adoption of Blockchain, the industry can automate the management of purchase orders, change orders, receipts, and other trade-related documentation, as well as inventory data with more efficiency and transparency. Blockchain is enabling a seamless supply chain, improved project management and simplifying contractual obligations at each point along the way. Gazprom Neft’s aviation refuelling business is an early adopter of Blockchain-based smart contracts. All refuelling operations are undertaken exclusively on the basis of digital contracts approved by both parties near real-time and eliminates the possibility of any breach of contract and makes the accounting process more transparent.
As the market continues to be volatile for Oil and Gas companies and uncertainties loom in the future, the industry will increasingly depend on technology to remain competitive.
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