Industrial OEMs and enterprises are feeling the pressure to deliver smarter products and capabilities faster than ever. More and more, these capabilities are built on a foundation of intricate industrial applications empowering connected equipment as a service
The past decade for industrial OEMs has seen a dramatic rise in the need for business transformation in order to enable revenue preservation and growth in the long term. The SaaS model, at the OEM or distributor level (DSaaS), has become a prominent approach for organisations to sustain existing and acquire new untouched market share, either directly or indirectly. Many OEMs and enterprises of varying tier levels have realized this opportunity and have already started investing in this direction. Following this trend, GE Digitalintroduced GE Predix, Hitachi established Vantara, and Siemens developed Mindsphere, among others.
But why do OEMs need an IoT strategy?
According to McKinsey, industrial OEMs are in a highly productive period using IoT in operational optimisation, integrated smart systems and asset performance management, all with a target market size of US$3 trillion by 2030.
To survive and thrive in this new era of industrial revolution, OEMs must start delivering smarter products or equipment that integrates the Internet of Things (IoT) to become future-ready and protect market share, maximising the value of device data to better assist clients and incorporate new product innovations. With insights into how your equipment performs and how warranty costs occur, you can effectively control the opex. And that isn’t all.
The value of smart equipment goes beyond cost control and asset management. For industrial OEMs, the core competencies are steadily shifting from hardware-centric to software-led services. With soaring global competition and increasing ROI expectations, new benchmarks are fading rapidly.
Industrial IoT and enterprise domain cloud open the door to offering newer revenue streams that bring greater recurring cashflow than a traditional single-time purchase model. These digital services may range from asset performance monitoring, asset remote monitoring and field ops to advanced business models such as equipment-as-a-service.
OEMs’ adoption challenge
In the McKinsey B2B IoT Survey, more than 90% of respondents revealed difficulty in incorporating all six components (connectivity, integration, cybersecurity, interoperability, confidentiality and device (AI/ML) intelligence) of seamless IoT adoption.
CXO-level challenges
Developing a strategy for business model transition through IoT is complex, and executing it is even harder. Building bespoke applications on your own can backfire, leading many CXOs or decision makers at global OEMs to look for a trusted technology partner that can accelerate the development of scalable and reliable IoT services.
Many OEMs and enterprises face significant challenges in making this happen. Even if they already have edge IoT data in hand, their goals of delivering applications such as remote monitoring, predictive maintenance, field service applications and smart products are blocked. Why? Because the underlying technology is complex and requires a lot of specialty skills, time, budget – and risk. The rise in level of complexity with each consecutive phase of application development yields a higher chance of failure at initiation.
If an OEM does not take action today, it’s inevitable that their competitors will— and much faster. Both the risks of not taking action and the benefits of IoT adoption are too big to ignore.
Buy or build an IoT platform, why just one isn’t sufficient?
Despite the benefits of conventional methods to develop an IoT platform (In-house development and IoT platforms), they eventually lead to a buyer’s regret for OEMs. Pick any of the approaches, and you will get a partial resolve for core challenges in the technology adoption.
An IoT platform provides you with faster time to market and proves to be cost-effective. However, it locks you in a single environment with limited flexibility and misfitting customisation (a one-size-fits-all approach). Conversely, the in-house development approach gives you flexibility and customisation according to your business needs, but it eventually leads to a dead-end with gigantic capex, slower time-to-market, skill shortage and bleeding ROI.
Solution: Why is it high time to consider an alternative methodology?
Beyond Gartner’s hype cycle for emerging trends in 2023, OEMs today are ready to implement IoT and AI/ML technologies and are on the verge of decision-making for the right methodology and technology partner.
