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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Innovation has continued to revolutionise the workplace. It has been 40 years since digital technology transformed the back offices of large organisations; 30 years since the PC revolution revolutionised the front office with productivity tools such as word processors and spreadsheets for all information workers; just 20 years since the Internet became a common business tool and; the smartphone, particularly the iPhone made its way into the workplace.
Each of these waves of technology contributed towards workplace transformation and has made way for the new wave of transformation – through emerging technologies such as Artificial Intelligence (AI) and newer business models (as-a-service and cloud-based delivery of personal productivity tools).
Organisations are being driven towards a “Mobile First” strategy to empower their “Smart employees” – no longer thinking of migrating their web apps to mobile apps, as and when required. They are looking to implement and develop mobile apps first. In the global Ecosystm Mobility study, only about 2% of organisations indicate the absence of a Mobile-First strategy and this is a good indication of the transformation that lies ahead.
To be able to implement a Mobile-First vision, become a Smart Workplace and for a seamlessly integrated environment, organisations will need to invest in multiple technologies simultaneously. These include:
Collaboration tools: Software and tools that help individuals in the workplace to collaborate and work together on a project in a smart and efficient way with shared data and resources – irrespective of their locations. Although the concept of collaboration is not new, technologies such as AI and Cloud allow for greater collaboration. This has driven leading players in the market to also offer Cloud solutions. Microsoft is a good example, where Cloud brought added features and services to their MS Office suite to match the requirements of an evolving workplace.
Social media: A technology that was popularized in the consumer space evolved into a major collaboration and productivity technology for enterprises. This opens up the possibility of incorporating sophisticated analysis tools, many of them driven by AI technology, leveraging social networks. Using social media in the workplace has also improved employee experience, as it enables the employees to interact in similarly efficient ways in the workplace, as they do in their personal lives.
Workflow and content management: Digitalisation is opening newer avenues, simplifying the way work gets done and exploring ways to improve existing processes and workflows. Workflow and content management systems have improved the way employees produce and manage business information thus making processes more efficient, cost-effective, and secure.
Mobility: The advent of smartphones, wireless networking, and mobile applications have enabled employees to work from any place and any time. This has expanded the workplace boundaries and employees can stay connected with the work while on the move.
Workplace innovation is already pervasive in customer focussed industries. However, workplace innovation is also combining with other emerging technologies such as AI and IoT to transform workplaces in supply-chain intensive industries as diverse as Manufacturing, Transport & Logistics, Energy & Utilities, and Mining & Resources. As this trend continues, we will start to see even more innovations to our places of work.