In the midst of the current global crisis, the Utilities industry has had to continue to provide essential public services – through supply chain disruption, reduction of demand in the commercial sector, demand spikes in the consumer sector, change in peak profiles, remote staff management, cyber-attacks and so on. Robust business continuity planning and technology adoption are key to the continued success of Utilities companies. The Ecosystm Business Pulse Study which aims to find how organisations are adapting to the New Normal finds that 6 out of 10 Utilities companies are accelerating or refocusing the Digital Transformation initiatives after the COVID-19 outbreak, underpinning the industry’s need for technology adoption to remain competitive.
Drivers of Transformation in the Utilities Industry
The Evolving Energy Industry. As consumers become more energy-conscious, many are making changes in their usage pattern to stay off the grid as much as possible, potentially reducing the customer base of Utilities companies. This increases their reliance on renewable energy sources (such as solar panels and wind turbines) and batteries, forcing Power companies to diversify and leverage other energy sources such as biomass, hydropower, solar, wind, and geothermal. The challenge is further heightened by the fast depletion of fossil fuels – it is estimated that the world will have run out of fossil fuels in 60 years. The industry is also mandated by government regulations and cleaner energy pacts that focus on climate change and carbon emission – there are strict mandates around how Utilities companies produce, deliver and consume energy.
Business Continuity & Disaster Management. Perhaps no other industry is as vulnerable to natural disasters as Utilities. One of the reasons why the industry has been better prepared to handle the current crisis is because their usual business requires them to have a strong focus on business continuity through natural disasters. This includes having real-time resource management systems and processes to evaluate the requirement of resources, as well as a plan for resource-sharing. There is also the danger of cyber-attacks which has been compounded recently by employees who have access to critical systems such as production and grid networks, working from home. The industry needs to focus on a multi-layered security approach, securing connections, proactively detecting threats and anomalies, and having a clearly-defined incident response process.
The Need to Upgrade Infrastructure. This has been an ongoing challenge for the industry – deciding when to upgrade ageing infrastructure to make production more efficient and to reduce the burden of ongoing maintenance costs. The industry has been one of the early adopters of IoT in its Smart Grid and Smart Meter adoption. With the availability of technology and advanced engineering products, the industry also views upgrading the infrastructure as a means to mitigate some of its other challenges such as the need to provide better customer service and business continuity planning. For example, distributed energy generation systems using ‘micro grids’ have the potential to reduce the impact of storms and other natural disasters – they can also improve efficiency and quality of service because the distance electricity travels is reduced, reducing the loss of resources.
The Evolving Consumer Profile. As the market evolves and the number of Energy retailers increases, the industry has had to focus more on their consumers. Consumers have become more demanding in the service that they expect from their Utilities provider. They are increasingly focused on energy efficiency and reduction of energy consumption. They also expect more transparency in the service they get – be it in the bills they receive or the information they need on outages and disruptions. The industry has traditionally been focused on maintaining supply, but now there is a need to evaluate their consumer base, to evolve their offerings and even personalise them to suit consumer needs.
The global Ecosystm AI study reveals the top priorities for Utilities companies, that are focused on adopting emerging technologies (Figure 1). It is noticeably clear that the key areas of focus are cost optimisation (including automating production processes), infrastructure management and disaster management (including prevention). 
Technology as an Enabler of Utilities Sector transformation
Utilities companies have been leveraging technology and adopting new business models for cost optimisation, employee management and improved customer experience. Here are some instances of how technology is transforming the industry:
Interconnected Systems and Operations using IoT
Utilities providers have realised that an intelligent, interconnected system can deliver both efficiency and customer-centricity. As mentioned earlier, the industry has been one of the early adopters of IoT both for better distribution management (Smart Grids) and for consumer services (Smart Meters). This has also given the organisations access to enormous data on consumer and usage patterns that can be used to make resource allocation more efficient.
For instance, the US Government’s Smart Grid Investment Grant (SGIG) program aims to modernise legacy systems through the installation of advanced meters supporting two-way communication, identification of demand through smart appliances and equipment in homes and factories, and exchange of energy usage information through smart communication systems.
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.
Australia’s data centre market has grown exponentially, to a large part due to the Government’s strong policies around cloud adoption. This is in line with the vision of creating a Digital Economy by 2025. Australia’s Tech Future talks about technological changes in 4 key areas including building infrastructure and providing secure access to high-quality data. Availability of local data centres is key to building better infrastructure to support the Digital Economy.
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.”
COVID-19 is accelerating digital transformation activities across industries. Remote working is now standard practice and digital engagement is replacing face-to-face interaction. Cloud technology has become essential rather than an option, and rollouts of new technologies such as augmented reality (AR) and intelligent automation are being expedited.
One of the industries that offer great potential for technology-driven transformation is the property sector.
Many activities within the property ecosystem have remained unchanged for decades. There are several opportunities for digital engagement and automation in this sector, ranging from the use of robots in construction to the ‘uberisation’ of the residential property customer journey.
The processes associated with buying or renting property remain cumbersome and complex for customers. Indeed, customers engage with many different organisations throughout their residential property lifecycles. When compared to some other industries, the customer experience can be poor. Components of the journey – such as property search – offer some great experiences but other parts such as exchanging contracts can rarely be described as positive customer experiences.
Although AR and virtual reality (VR) technologies can facilitate property inspection, most inspections are still undertaken on-premise, together with a real estate agent. Contract exchanges often involve interactions with legal professionals in-person. Securing a mortgage or a rental agreement also typically requires face-to-face interaction. Deposits commonly necessitate the physical presentation of a cheque.
The Uberisation of the Property Sector
So, in the residential sector, there are clear opportunities for start-ups and property search platforms to offer greatly enhanced customer experiences. The COVID-19 crisis will speed up the rate at which digital technologies are used to automate activities throughout the residential property customer journey and to engage customers digitally.
Property search platforms such as Singapore-based PropertyGuru, have been creating innovative ways of engaging customers and extending their range of services, for many years. For PropertyGuru, its news features, mortgage calculator, and ability to search for investment properties overseas, have enabled it to offer customers more value from its platform. Its PropertyGuru Lens feature uses AR and artificial intelligence (AI) to give customers a more immersive and improved experience. In common with other real estate platforms, it offers AR and VR tools for inspections.
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.
The opportunities that can be created by 5G continue to excite businesses and consumers alike. As 5G rollouts gather pace, new consumer experiences and business models emerge. For consumers, enhanced mobile broadband offers superior experience, driving the consumption of much more data-rich content and the more widespread application of emerging technologies such as augmented reality (AR). For businesses, the low latency, higher bandwidth, and the ability to handle massive machine type communications promised by 5G create opportunities for a dizzying array of uses cases, usually linked to IoT technology.
As enterprise use cases like autonomous driving, remote surgery and software-defined factories are enabled by 5G, the impact of cybersecurity breaches becomes much greater. Breaches can potentially have a catastrophic impact – they could lead to serious damage to or the destruction of sensitive critical infrastructures, such as power stations and transportation systems.
Security vulnerabilities associated with 5G are underpinned by a change in network architecture. The latency benefits of 5G require a more distributed architecture to enable use cases which require real-time data processing. This leads to the virtualisation of higher-level network functions formerly performed by physical appliances. So 5G networks will necessarily create a greatly expanded attack surface. If an attacker gains control of the software managing the networks, they can also control the network and potentially cause chaos.
One of the major benefits of 5G is massively increased bandwidth. This is also a huge benefit for attackers. An increase in available bandwidth makes it much easier to generate attack traffic from compromised connected devices and vulnerable networks. As volumetric DDoS attacks grow in terms of frequency, magnitude, and sophistication, traditional defences such as out-of-band scrubbing centres and manual interventions become inadequate and expensive.
In a 5G World, Security Postures must be Agile and not Act as a Bottleneck to Performance
5G use cases require a radical shift in cybersecurity posture and a new set of security considerations. Networks managed by enterprises and service providers need to scale up to handle larger capacity requirements and scale out to accommodate the increased demands of edge computing and the growing volumes of IoT endpoints. Security infrastructure must change accordingly with upgrades to both physical and virtual components. Importantly, security postures must also be sufficiently agile to change with new requirements while ensuring that security does not act as a bottleneck to network performance.
A common response to the increasing complexity of distributed cloud and IoT environments – where existing tools cannot always detect new and emerging threats – is to deploy brand new security tools. This seems like a great solution but can lead to significant problems and compromise security. Over time, the deployment of multiple security tools creates an estate of siloed security products, sometimes reporting to their own dashboards. Although this management challenge is typically being addressed by service providers and large enterprises, most commonly with SIEM, they must continually ensure that there is provision for the centralisation of security alerts, so that cybersecurity staff do not face the challenge of monitoring multiple consoles and cross-referencing between disparate screens and information formats. Applying security policy changes is a laborious and time-consuming task in a multi-dashboard environment – representing a security threat in its own right.
In the case of large volumetric attacks, redirecting suspicious traffic to scrubbing centres adds latency and imposes a significant financial burden, since mitigation costs are directly tied to the volume of the data traffic. Large enterprises and service providers should consider adopting new DDoS protection approaches that incorporate AI, real-time analysis, and telemetry to automate a more intelligent and cost-effective detection and mitigation process.
Different Policies Required to Reflect Specific Needs of Each Use Case
5G allows mobile service providers to partition their network resources, to address a diverse set of use cases with differing performance and functional requirements. These varying service performance profiles have a direct impact on security protocol choices and policy implementation. For instance, the service in one use case, such as a Smart City application, may require extremely long device battery life, which constrains the security protocol in some other way (e.g., how often re-authentication is performed). In another example, the use case may be very privacy-sensitive, requiring unusually intensive security procedures (e.g., very frequent reallocation of temporary identities).
The complexity associated with securing highly distributed and virtualised networks powered by 5G, will grow enormously and be hampered by an ever-increasing skills shortage. The only way to address these challenges is to create an intelligent security infrastructure that is sufficiently agile to scale with the network and use AI to detect, contain and eliminate threats. Security managers will need a unified view of all assets – physical and virtual – so that multiple security policies can be enforced and managed.
Governments face multiple challenges which are further getting highlighted by the ongoing global crisis. They have to manage the countries’ financial performances, reducing fiscal deficits. Every economy – whether emerging or mature – face challenges in bridging economic and social divides and ensuring equal access to infrastructure across the population. Most governments have challenges associated with the changes in demographics – whether because of rapid urbanisation, a fast ageing population or those associated with immigration policies.
Government agencies have the task of ensuring reliable public service, keeping their citizens safe, and striving for cost optimisation. In this constantly evolving world, agencies need to rely on technology to manage ever-growing citizen expectations and rising costs. Several government agencies have started their digital transformation (DX) journey replacing their legacy systems to transform the way they deliver services to their citizens.
Drivers of Transformation in Public Sector
Creating cross-agency synergies
Government agencies have access to enormous quantities of citizen data. But much of that data resides with individual agencies, often with no real synergies between them. For improved cost management and better utilisation of the data, it is imperative for governments to think of cross-agency collaboration systems and tools which give the larger entity a better visibility of their resources, contracts and citizen information. This involves, developing procedures, frameworks and working beyond their limited boundaries, leveraging technology to share information, applications, platform and processes. While this has been in discussion for nearly a decade now, most government agencies still work in departmental siloes and find it hard to work as a networked entity. The Ecosystm AI study finds that nearly three-quarters of public sector organisations find data access a challenge for their AI projects.
Improving citizen engagement
Increasingly, citizens are becoming tech-savvy and are expecting digital services from their government agencies. Not only that, but they are also ready to have conversations with agencies and provide feedback on matters of convenience and public safety. With the popularity of social media, citizens now have the capability to take their feedback to a wider open forum, if the agency fails to engage with them. Public sector organisations have to streamline and automate the services they provide, including payments, and provide real-time services that require collaborative feedback and increased participation from citizens. Smart governments are successfully able to leverage their citizen engagement to use open data platforms – Data.gov and data.gov.uk, are allowing communities to target and solve problems for which governments do not have the bandwidth. With citizen centricity and open government policies, there is also an ever-increasing need for greater accountability and transparency.
Managing project performance and costs
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.
The next phase of a post-COVID world will be one of reduced physical contact, tighter regulations, and new habits and hygiene practices. This will translate into significant process changes which will be deeply enabled by mobile technology. All mobile form factors will be more integrated into how we interact. Interactional changes will be found in our homes, offices, public spaces and services.
In this blog post I address two fundamental questions as a technologist on the underpinnings of this shift:
- How can enterprises find ways of rebuilding and cementing trusted relationships using mobile technology?
- How does our infrastructural foundations support mobile technology for contactless transactions? (privacy, two-factor authentication, data quality and so on)
Situational shift to mobile
Given the rapid shifts in the last six months in how we can interact with each other, enterprises will have to be agile and flexible in process design going forward to optimize opportunities for customer engagements.
We will continue to have further disruptions on how we live and work in the next 12 to 18 months and potentially beyond. Some of the shifts towards mobile have been expected for a while, yet this crisis has pushed the timeline ahead as to how we engage.
Use cases in the “new normal”
Here are some use case examples in this next phase of business where mobile enables the transaction between consumer and environment:
Education. The reskilling and training certification that will be necessary to address unemployment, will be on Mobile First. Because of bandwidth, learner attention span, and form factor, there will be retooling of educational programs to be bite-sized and more media oriented.
Retail. Retail and delivery businesses shifting to remote first, with drop-off points that use mobile for contactless signatory and payment.
Healthcare. Telemedicine primarily by mobile devices (phone, laptop, phablet). Personal medical data sharing over mobile will require enhanced data encryption and two-factor authentication, which needs addressing via encryption and authentication.
Entrepreneurship. More side hustles that are mobile-based and mobile administered. Any authorization and transaction-oriented activities will be driven by mobile.
Government. Requests for document renewal or identity authentication for approval or submission of materials, with one-touch request.
Supply chain. Visibility and tracking of inbound and outbound materials. One-click reordering, and contactless payment verification.
Workplace. Contactless engagement with mobile as authentication of actions (coffee machine payment, copier usage, keyless office, meeting room allocation).
Facilities management. Hygiene controls with personnel health detail tracking (who cleans what room when). Deep cleaning management tools for audit trails, liability.
Role of mobile in creating engagement
Building trust
As we filter through the level of rubbish coming at us via social media, websites and our email, most of us are looking for a trusted information source. Our mobile is our window to the world, and many are applying appropriate filtration to make that world a bit more manageable.
The reason that people did previously download an app was partly based on what information had to be handed over in terms of permissions. The app builder needs to build a trusted relationship on benefit, not on what can be leveraged from the consumer.
To build that trust and create a closer engagement – albeit driven by situational need vs. consumer want – app developers need to consider these consumer needs:
- Level of trust in quality of information provided (e.g. weather info vs something more critical)
- Trust in app data usage and functionality (does it work?)
- Privacy of data being used and being held (statements and auditability)
- Location of data (on whose device: client or server)
- Speed and reaction time (Is there edge computing or the use of IoT to help push mobile information quickly?)
- Loss of data or loss of device and the impact on app access (More than lost passwords, lost processes and lost data)
Technological foundations for mobile usage
Network and bandwidth
We have all experienced bandwidth issues in the last few months, either sharing bandwidth with loved ones in lockdown to peak periods of video conferencing activity across geographic regions. Entertainment content providers such as Netflix and Disney+ were asked to lower the quality of the data streaming.
But then what online activity will take priority? Will we start to see pricing differentials for guarantees of availability? What about subscription models with platinum, gold and silver memberships (as in frequent flyer programmes) as to the network bandwidth you or your activity is allocated? Will things be done over VPN not only for privacy but for priority? I also see VPN as a possible solution towards issues like Zoom bombing and other intrusions to daily business operations.
We come to the role of a pandemic in 5G investment, which is similar to the role of investment in R&D during an economic downturn. Clearly, the world needs better bandwidth with more agility and future-proofed for functionality. You cannot drive a fast car on a bumpy road with potholes.
But for countries losing thousands of citizens to a virus with critical infrastructure at risk, where is the priority of a better telecom infrastructure? My colleague Shamir Amanullah wrote a report prior to the pandemic about the Race for 5G in Southeast Asia which is a good barometer for other regions. There is a good CNBC article from Todd Wassermann on the US situation, and a rather excellent survey on consumer sentiment on 5G from February 2020 by Politico.
Role of data quality and its security
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.
Final thoughts
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.
Identifying and selecting a vendor for your tech project can be a daunting task – especially when it comes to emerging technologies or when implementing a tech solution for the first time. Organisations look for a certain degree of alignment with their tech vendors – in terms of products and pricing, sure, but also in terms of demonstrable areas of expertise and culture. Several factors are involved in the selection process – vendors’ ability to deliver, to match expected quality standards, to offer the best pricing, to follow the terms of the contract and so on. They are also evaluated based on favourable reviews from the tech buyer community.
Often businesses in a particular industry tend to have their unique challenges; for example, the Financial Services industries have their specific set of compliance laws which might need to be built into their CRM systems. Over the years, vendors have built on their industry expertise and have industry teams that can advise organisations on how their business requirements can be met through technology adoption. These experts speak in the language of the industry and understand their business and technology pain points. They are able to customise their product and service offerings to the needs of the industry for a single client – which can then be repeated for other businesses in that industry. Vendors arm themselves with a portfolio of industry use cases, especially when they are entering a new market – and this often gives them an upper hand at the evaluation stage. In the end, organisations want less customisations to keep the complexity and costs down.
Do organisations evaluate vendors on industry experience?
Ecosystm research finds that industry experience can be a significant vendor selection criterion for some tech areas (Figure 1), especially in emerging technologies such as AI. AI and automation applications and algorithms are considered to be distinctive to each industry. While a vendor may have the right certifications and a team of skilled professionals, there is no substitute for experience. With that in mind, a vendor with experience in building machine learning models for the Telecommunications industry might not be perceived as the right fit for a Utilities industry implementation.
Whereas, we find that cybersecurity is at the other end of the spectrum, and organisations perceive that industry expertise is not required as network, applications and data protection requirements are not considered unique to any industry.
Is that necessarily the right approach?
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
IoT
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.
Cloud
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.
The Oil and Gas industry has seen volatile times and is affected by its own set of unique challenges ranging from commodity price fluctuations, a potential supply crunch, geo-political events, and energy policies including energy transition. Moreover, the challenges and requirements are distinct at different stages of operations – upstream, midstream and downstream. The industry has been an early adopter of a few emerging technologies and is looking to leverage them to remain competitive and better employee management.
Drivers of Transformation in the Oil and Gas Industry
Remaining competitive in an evolving market
Oil and Gas companies are having to clean up old processes, as the market gets increasingly competitive. Ecosystm research finds that the top business priorities for Oil and Gas companies do not stop at cost reduction and revenue growth. The industry also has to focus on employee experience and safety, compliance, and increasingly even customer experience. And they must remain competitive through potential disruption in supply, demand and production; the rising costs of processes; and ongoing exploration costs. Oil and Gas companies are also focusing more on their downstream operations including retail in order to remain competitive.
Shortage of skilled workforce
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.
IIoT
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
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.
AI is also helping organisations monitor environmental risk and has the potential to help Oil and Gas companies with their compliance requirements. Gazprom Neft, one of the largest suppliers of natural gas to Europe and Seismotech are exploring using AI for seismic data processing, for solutions that are specific to the needs of the industry.
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.
Blockchain
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.
