An Atlantic Crossing (twice) at the end of 2022. I will be sailing with 2-mast Clipperbrik “De Morgenster” from Rotterdam in The Netherlands to South America and the Caribbean. At the start of 2023 I will be sailing back.
Analyst firm Gartner published their list of Industrial IoT Platform leaders in October 2020. Notably Siemens MindSphere is missing from the list. The Gartner Magic Quadrant ™ however lists Hitachi, PTC and Microsoft as leaders and Software AG as a ‘visionary’.
If we look further in both reports, there are also other differences in the ranking such as IBM being a ‘contender’ in Gartner’s view and a ‘strong performer’ in the view of Forrester.
Obviously both analyst firm use their own set of criteria and methods to rank the providers of IoT platforms. It is also not uncommon for providers to work with a limited set of analyst firms, so it could be the case that Siemens decided not to participate in Gartner’s research in 2020.
Participating in analyst firms research is a well-established way to create independent evidence how a solution or product holds up compared to its competitors. In general, the ranking is based on a combination of product related questions, customer references and a product demonstration to the analyst reviewing team. The amount of work for the providers should not be underestimated; there is a significant investment in time needed to address the many questions and solid customer references. I have done it multiple times in the past and can testify that it is an intense process.
However, if we look at the topic of this Magic Quadrant ™ and Forrester Wave ™ I want to raise an important question: what is the relevance of researching a platform?
Comparing IoT platforms with each other is a bit like comparing Linux to Windows or macOS. These operating systems exist next to each other and a choice for one or the other is not necessarily based on their underlying functionalities. The real value is created by choosing the available applications, scalability and developer ecosystem. In my opinion the same applies to (industrial) IoT Platforms.
A choice of IoT platform should be based on these 3 elements, combined with the amount of access to trained staff and product specialists for implementation and maintenance.
Finally I would maintain the opinion that standardization within the company is an important aspect. Choosing one platform and sticking with it allows for scalability and efficiency, two cornerstones of any IoT implementation.
Based on this there probably is not a ‘best’ platform, there are however the best use cases for a particular organization. And those use cases are the applications that run on the platform. Just like Microsoft Office runs on Windows, applications for preventive maintenance or digital twins are the right software to focus on in industrial IoT.
I am looking forward to the analyst firms to compare the IoT applications and create a list of leaders in use cases. Comparing Operating Systems feels like the wrong investment in time and effort for both the analyst and provider teams.
As an IoT specialist I get asked many times about the newest and greatest in the field of IoT. Sometimes investors want to know about the newest start-ups or technologies – ‘where should I invest?‘.
This type of question is difficult to answer as people seem to want to find the next new tool or not-yet-invented method to solve a large array of problems.
It is my opinion that at this time the focus of the questions should not be on technologies or methods; the focus should be on specific use-cases and particular application objectives.
The wave of increased digitalization has brought with it the challenge to find the best place to use these digital technologies, and the search sometimes brings places that are a good fit, but also places that are a bad fit.
We see this in the application of IoT in the consumer space (a microwave with an internet connection?) and in the business space as well.
As a result of this search and the fear-of-missing-out on this new revolution, many proof of concepts are executed and the digital enablement of devices is introduced ‘because we can and it may bring value’.
I have been a witness to many of these proof of concepts where a solid understanding of their impact on the business was not taken into account. This is innovation because ‘we need to innovate’.
The real value is not to be found in the utilization of new technologies or methods, instead it is to be found in the impact on your business process and certainly on the product or service that you provide.
The purpose should not be to monitor temperature of your factory, office, or house; the purpose should be to create a healthier and safer working and living environment.
The revolution is not to measure and use IoT to do so, it is to be found in the improvements you can implement consequently.
My advice to all that are looking for the best new IoT invention, technology or method is to first look at what you want to achieve and I would expect that you would very probably be able to use existing technologies to achieve your objectives.
Mr.Paul Albada Jelgersmaworks at Atos, a global leader in digital transformation with over 110,000 employees in 73 countries and annual revenue of over € 11 billion. At Atos, he is, among other things, responsible for development of services and applications for “Siemens Mindsphere”, which is Siemens’ digital IoT platform for industrial companies.
According to Mr. Albada Jelgersma, many companies now understand that access to data enables new value creation and thus opens up for new opportunities. However, this requires digital platforms to enable the combination of data from different sources. Today there are typically two types of platforms, thegeneric platformwith suppliers like Microsoft, Amazon and Alibaba, andspecific platformswith suppliers like Siemens, Bosch, GE, SAP and PTC. Both types have their pros and cons. Generic platforms are adjustable, but as a result require more configuration work, to enable applications. However, as a user you must be on top of the domain competence concerning the application. Specific platforms often have more built in domain functions and knowledge, but generally they are less easy to adjust and customize for use in domains that are outside of their scope.
Mr.Albada Jelgersmaforesees that digital platform solutions will possibly be provided to companies free of charge in the future. This, on the condition that ownership of data will be transferred to the digital platform provider, enabling new opportunities and new business models for the digital platform provider. Whether this is good or bad in general, is impossible to judge. Each case is specific and needs to be negotiated separately.
Moreover, one can notice a political influence on the digital platforms of today, says Mr.Albada Jelgersma. This is seen through state laws and regulations which indicate increased local barriers in countries like China. Smaller countries in Europe take on a dual approach. On the one hand an increased focus on the local industry and on cooperation in-between countries can be seen. On the other hand, there is a tendency of some countries to isolate themselves more, e.g. Brexit. One of Mr.Albada Jelgersma´s concerns is that international cooperation in the development of digital platforms does not get as much attention and focus as the national orientation.
Another important trend that Mr.Albada Jelgersmahighlights is ethics, which is becoming increasingly important among digital platform providers. When data is feeding autonomous self-learning systems that makes decisions, man is not any longer in direct control of the decisions. How can human values then be maintained?
In the 1stblog in the series, an overview was shared of the journey to managed enterprise IoT, which we divide into three levels of maturity. In my second post you will learn more about the first level: Enabling the use case.
Once you have determined the IoT use case you need to ensure that the solution is secure, accurate and predictable – i.e. it delivers sustainable value – in the face of increasing quality of devices, edges, continuous data flows, and technologies. This is enabled through ‘non-functional requirements’ (NFRs) and spans both execution qualities and evolution qualities. This is going ‘beyond the use case’.
By focusing on ‘how’ the use case is delivered, instead of ‘what’, you can realize the following benefits:
Quality: If your products and services cannot extract value, the data, and opportunities, it is lost.
Risk: Complex IoT use cases can put business continuity at risk; reduce it through strong NFRs.
Productivity: A use case has little value if it stops working after 6 months or in peak load periods.
Future-proofing: Your system should be built for low cost and simple improvements / evolution.
Realizing this require you to define, discuss, document, and design your NFRs as you enable the use case and beyond it. Extending the timeline from the previous post, the following activities take around 12-24 months:
Project: Design solution, install and implement IoT solution from core to edge, integrate into your existing business systems as well as ensure system security – including building ecosystem of partners.
Business Platform: Scale-up and industrialize the use case to a full platform, do further roll-outs, integrate into your existing business and enhance parts of the system to delivery sustainable value.
Below is a non-exhaustive list of topics and example questions to be considered for NFRs:
Does your E2E use case need an operational uptime of 99.99% or 95%?
What are you E2E RTO/RPO? What are the business impact / cost of your use cases being down for 1 or 60 minutes? How does this impact backup or disaster recovery? How do you enable HA, backup or disaster recovery in a distributed architecture?
How will you update millions of devices? When and how to push new functionality? How to handle a million+ devices all calling home sick? Will you have 24×7 operations?
How will data be handled across different silos? Do your platforms work together?
How quickly do you need to access the data? Does it need to be processed at edge?
How will the system do backups and ensure service continuity? How will you ensure high uptime of distributed architecture? How will errors be handled ‘gracefully’?
How will data from connected objects be trusted? How will you ensure security in new and high risk environments? How will you reduce attack surface? How will you ensure internal and external compliance, auditability as well as alignment to standards?
How will you reduce the head count of managing such E2E complexity? How will you optimize latency issues to improve real-time outcomes and / or use experience?
How will defects be corrected? Will the system and components have self-healing? How will uptime be ensured without sending people / parts onsite?
Will your system be built on principles of separate independent functionality?
Will it scale up/down to meet peak demands?
By focusing on ‘how’ you enable value from and not just ‘what’ the use case is you will derive much greater long term value for your business. To do this, you need to define, discuss, document and design them into the use case from the start. If you are not already doing this I suggest you look at facilitating it as soon as possible.
I have spoken to many clients who have rolled out IoT solutions which are ‘the future of the businesses’. It is therefore unfortunate when they stop working effectively or if the operations team only know of problems when they are informed by the customer. It is normally at this point that they ask for expertise on going ‘beyond the use case’. A few common outcomes are re-building the app, creating a new platform, facilitating rapid scalability or enabling an operations team with E2E monitoring; either way, it costs time and money that were not predicted in the business case.