If you haven’t read “Precision: Principles, Practices and Solutions for the Internet of Things” by Timothy Chou (PhD) yet, I strongly urge you to do so. He teaches invaluable lessons on a structured and solution centric approach to the Internet of Things. He does so in an unpretentious and neutral way, avoiding the traps of being tangled in the sheer size the Internet of Things encompasses.
I recently visited the IoT World conference in Santa Clara, CA. Having been at this conference a couple of times in the past, it is always a delight to see the movement in the industry and how things that have been concepts just two years ago, are now reality. One of the speakers there brought up Dr. Chou’s book and talked about the IoT framework. If you have been working in this area for a while, I am sure you are familiar with the five layers of the framework; Things, Connect, Collect, Learn, Do. This has been a standard for some time now and propagated by most consultant and analyst agencies. This framework helps you to understand where in the value chain your company is and if you are spanning access multiple sectors of the value chain or if you are a critical component of the process. What it doesn’t do though is giving you a hand in finding a strong value proposition for your customers. It is great to know what your product is, but why is it? What solution does it provide to your customers and how does it support your clients on their journey?
Before we look closer at the value proposition, let’s take a step back and look at who we are talking to. After all, if you are using a business canvas to vet your idea the question of who you are selling to is one of the first to answer. If you are coming from the software industry and try to tackle the Internet of Everything, you will likely run into your first hurdle in identifying your target persona within a company. Classically you sold to the IT department. They use your product, they implement it, they pay for it. When you talk about devices though, about things that run within a company, you often need to talk to operations. They need to know when and how something fails. IT will certainly implement it within your client’s company, but operations will call the shots what to implement and how much to pay. This also means that you are more likely to deal with the CEO rather can the CIO. Especially now, at the break of dawn in IoT, visionaries are the ones who will buy your products. A strategic and complete vision for a company is needed to understand the value a connected world can create for a company. While a CIO should think strategically, it is the job of the CEO to think and act holistically.
On first look the Internet of Things enables companies to collect data on devices and act accordingly. Go beyond monitoring and include machine learning and you pivot from a break-fix culture to managed services. All in the spirit of the bottom line and making sure that your costs kept low and production is up.
This is surely already a compelling and strong value proposition and only few would deny the benefit. From a CIO perspective, this all makes sense and goes a long way. After all this is what we are doing since years. What worked in the PC world with RMM systems and the mobile world with MDM becomes Smart Device Management. I would like to encourage you to think beyond the managed devices concept and look at the opportunities IoT can bring like a CEO. Think how this could transform your business model and improve, pivot or excel your company.
One of the most interesting panels I participated in during IoT World was “Transforming Industries: The IoT Impact in Aviation” held by a Senior System Engineer at Boeing. It is highly impressive how a company this size adapts and implements new technology concepts on a broad concept, be it manufacturing, supply chain or to enhance the customer experience. In its core his presentation answers how a massive collection of information (read “Big Data”) brings value to an already existing process or product.
If you haven’t come across the idea of a “Digital Twin” I encourage you to do some more reading on this topic. In a nutshell, a “Digital Twin” is the incorporeal representation of a real-world thing. A digital twin incorporates all information you can collect from original inception (3D model) to its inevitable retirement (recycling). In other words, it is the digital representation of your product over its whole life cycle. Within the life-cycle of a product there are 4 key value propositions data will help you to improve: Product design, quality, service-ability and residual value. Let’s look at these 4 areas in detail.
Nowadays product design, at least for actual real objects, starts with a 3D model and stress tests e.g. via a finite element analysis (FEA/FEM). Every good engineer will first test his design in a CAD program. Information that had been collected during the life cycle of a previous generation can give invaluable insight in how a product is used, in what environment the product lives and what forces are present and a given time. These insights can improve modelling of new features or improve methods to make safer, better and stronger things.
Especially in an industrial environment on a large scale, production monitoring is a tedious and highly complex endeavor. You will not find a device or machine with more than 10 parts where all parts have been produced at the same location by the same company and then assembled. Parts are produced in different countries by different companies and the married and assembled in one place and most often just in time for delivery. This is the supply chain. Getting insight in production, quality testing and delivery of your parts can give you tremendous gains and ease of mind for your final assembly line. Parts carry digital twins that can be constantly improved and reassessed. Even beyond delivery, as with product design, insights in usage, stresses and end of life can improve your quality testing methods and improve them from a theoretical testing to matching real life scenarios.
This has already been mentioned above. It is simply the way you give service and a transition from break-fix to a managed service. It can either be part of your standard support scenario or can create an additional value with paid services or outsourced managed service providers. After all, 70-80% of the value of a device is created after it has been sold. Be it services, replacement parts or refurbished/recycled material.
Every new car owner knows that there will be a time when your motorized vehicle will be sold to get the next best thing. And as much as it hurts us the value of the car will be less than you original paid. To increase the residual value, we try to catch all planned annual service appointments and make sure the service check book is in order. If you are more into buying used cars you most likely contemplated if you are buying from a private seller or certified pre-owned from a licensed dealer. What’s the difference? And what is the link to IoT? The difference is the information you can collect and make available. A filled service check book makes the potential buyer more likely to buy. A certified pre-owned ensures that a dealer certifies that all maintenance has been done properly. Now let’s envision a digital twin of your car that includes all information since the time it was build. And let us assume this data shows that everything with the car is just right. Would you pay more or would you still go for a car you know nothing about? Trusted information is key.
Big business demands knowing and mitigating risks. The bigger the company the more likely you will have a department just dealing with risks. You will likely deal with 3 main topics when creating digital twins. Who owns the data? How do I manage it? Is it secure?
For the first question: The manufacturer of the device owns the data. Period. As much as it hurts from a consumer perspective, if you read the terms and conditions, a manufacturer reserves the right to collect anonymized data. If it serves a purpose this data can and will be shared with the end user, allowing insights for each participant of the value chain.
The data a digital twin demands highly performance systems being the backend for storage and analytics or the front end for visualization and interaction. Data science as a function within a company has become key for a successful execution and should not be neglected. It is the heart of any industrial manufacture that seriously wants to excel in a smart device world. Systems like IBM Watson, Google Deep Mind or Microsoft Project Oxford will lead the way but companies will need to invest in a strong analytics department.
In a world where cyber threats are omnipresent no discussion about a project will be held without covering security thoroughly. Often enough security is not taken as “Is it secure?”, but as “Is it secure enough?”. Security should be a key company value of any company you are dealing with and I encourage you to do your research and homework before engaging a hardware or software vendor. Security always costs if done diligently and you should not compromise when dealing with your most valued asset: Data.
If there is one lesson to be learned here, think about your customer’s journey when creating your value proposition. To be exact, think about the whole journey. We are often focused on one single item and do not see the big-ticket items. If you are thinking to make your product a part of the IoT story, make sure that you are improving your processes not only from a simplicity standpoint but also from an opportunity standpoint. Think beyond current state and dare to experiment.
No matter if you are pitching an idea internally or if you are selling to a client: Your value proposition needs to be smart.