Design Thinking Meets IoT: A Deep Dive into the 6 Essential Personas

The design thinking methodology has recently gained popularity in academic institutions and is often linked exclusively to the notion and practice of innovation. In this article, we provide comprehensive guidance for participants in the innovation ecosystem on the suitable utilization and timing of the design thinking methodology and IoT application.

It is a process that must start from the understanding of the public’s consumption habits, without preconceived ideas to identify what gives value to a product or service and therefore generate said value in the offer to the market. Frequently, many entrepreneurs make the mistake of assuming that their ideas will satisfy the needs of others for the simple fact of satisfying their own, without focusing on what is essential for any business: the human factors that influence and determine the actions of a person. 

Design Thinking evaluates 5 channels of experience: senses, emotions, thoughts, actions, and relationships. By evaluating them, it allows teamwork to reveal the challenges we face. Design Thinking helps us redesign manufacturing or creation processes of both physical and digital products or services, it will allow us to design new ways of interacting with machines and will give us the possibility of creating more personalized experiences for our users.

The analysis of these users’ data will be increasingly important in the manufacturing or creation processes of products or services, so although we are presented with a dehumanized horizon full of intelligent machines and robots, the future lies more than ever in people-centered innovation. Design Thinking also allows us to work on the identification and development of social innovations.

Design Thinking

Technological innovation has traditionally been a linear process with a clear sequence of activities including research, development, production, marketing, and commercialization.  For each of these steps, teams are created with clear functions that elaborate and add value to the delivery of the previous step, so researchers test the concepts and demonstrate the technology, developer engineers transform it into a product, while development engineers production is produced under-market conditions, and marketers generate demand and/or meet the supply of the product.

 However, the very definition of this model is known to be not correct because on multiple occasions it is necessary to go back in the process until the product is fine-tuned with the market therefore it is an interactive process between the different steps, which gives rise to present the alternative technological innovation model to the linear one called chain-linked or links in a chain. This model is based on:

  • Development can move forward or backward in the process
  • There is continuous communication between all those involved in the different links
  • Scientists and engineers work together as equals and even generate technological platforms from which different products emanate
  • Capabilities are developed and implemented by groups, and not by individuals, who may be inside or outside the organization
  • Technology users are one of the most important sources of information for technological innovation
  • The acceptance of new technology by society almost always depends on a small group of potential users whom we must convince.

Deep Dive into the 6 Essential Personas IoT

1. Recognise the context

IoT application

AI and IoT are examples of emerging technologies that can bring various advantages, including intelligence, automation, efficiency, and personalization. However, they also provide several difficulties, including moral, social, environmental, and security concerns. To develop and adopt, you need to understand the context in which they will operate, the problems they will solve, and the impact they will have on the Internet of Things. It can help you conduct user research, stakeholder analysis, and scenario planning to gain a holistic and empathic view of the situation.

It is very tempting in the early discovery phase to start with a solution in mind like “we have to use AI/IOT”. Design thinking is about flipping that on its head and starting with the customer in mind. AI and IoT are just tools. They might not be the best solution for every problem. If we specifically want them as a solution, We would recommend doing that later on in the brainstorming stage (after understanding the problem). You can allocate time to specifically think about “How might we solve this problem using AI/IOT/or other emerging tech”.

Understand user needs– By empathizing with users, you can gain valuable insights into the specific challenges you are trying to solve, and design AI solutions that address those needs.

Define the problem and interpret the results– You can use design thinking to synthesize the user research data; identify patterns/trends, and define the specific AI challenge you want to tackle. 

Ideation and prototyping – Brainstorming allows you to explore a wide range of ideas that can then be quickly prototyped & tested with users to gather feedback & refine the AI concepts.

Testing and Refinement The iterative approach can help you to continuously refine & improve AI solutions based on the ongoing feedback from users.

2. Confine the problem

Upon grasping the context, it is essential to pinpoint the issue that you aim to address using cutting-edge technology. It can help you frame the problem from the user’s perspective, using tools such as personas, journey maps, and problem statements. It can help you frame the problem from the user’s perspective, using tools such as personas, journey maps, and problem statements. By defining the problem clearly and concisely, you can focus your efforts and resources on the most relevant and valuable aspects.

The issue at hand is less related to technology and more related to psychology. When looking at it broadly, the process of innovation can be broken down into three main stages: Exploration, experimentation, and implementation. From a frog’s-eye view, there are countless tapping steps, some of which follow each other and between which the innovators keep going back to incorporate newly acquired knowledge into the development process. But it always starts with listening, understanding, asking questions, listening again, and so on. 

3. Create ideas

The next step is to generate ideas for possible solutions that use the emerging technology. This is the place where you are free to express your creativity and discover various opportunities, unrestricted by concerns of practicality or profitability. Design thinking can help you brainstorm, diverge, and converge ideas, using techniques such as mind mapping, sketching, and voting. By generating a wide range of ideas, you can increase your chances of finding innovative and original solutions that address the problem effectively.

4. Ideal solutions

Once you have identified the most promising concepts, it is essential to create prototypes to evaluate their effectiveness, user-friendliness, and desirability. It allows you to transform your ideas into tangible and interactive solutions, enabling you to gather feedback from both users and stakeholders. Additionally, it provides an opportunity to gain valuable insights from both failures and successes. Design thinking encourages the utilization of either low-fidelity or high-fidelity methods for prototyping, depending on the level of intricacy and specificity necessary for each solution. For example, you can use paper, cardboard, or Lego to prototype an IoT device development or use mockups, wireframes, or code to prototype an AI system.

It means how fast you can materialize and test an idea. The best way of testing an AI or IoT idea is first of course to try manually, make exactly the process manual before bringing the AI technology, then quickly without any coding or experience, you can simulate many possibilities before the hard programming aspect.

A prototyping mindset is more important than the tools itself. If you possess a mindset inclined towards building, it is crucial to have a clear understanding of the tools needed to bring your vision to life at each stage of the development process.

  1. At the first stage, lead with sketches, clay models, etc.
  2. At secondary, lead with wireframes, make-shift prototypes, etc.
  3. At the last stage, lead with 3d renderings, hi-fi prototypes, visionary videos, etc.

5. Test and Restate

The final step is to test your prototypes with real users and stakeholders and collect data and insights that can help you improve your solutions. Testing is not a one-time event, but an ongoing process of learning and iterating, until you reach a satisfactory level of performance and satisfaction. Design thinking can help you test and iterate your solutions using methods such as interviews, surveys, observations, and experiments. By testing and iterating your solutions, you can ensure that they meet the needs and expectations of your users and stakeholders and that they leverage the potential of the emerging technology.

Your targeted audience may come from different backgrounds, have various motivations, face different challenges, and hold varying expectations towards the technology. They could have varying degrees of familiarity with technology and, on occasion, alter their opinions without clear cause. Therefore, there is no substitute for usability testing with your users.

AI can help for example in speeding up tests on compliance with heuristics, Heuri,x, or by allowing you to quickly summarize and analyze various test sessions. By essentially defining a solid design to begin testing on, we will likely need fewer iterations and should have a shorter and more efficient design process. The phase of “Test and Restate” in design thinking plays a vital role in enhancing AI and IoT solutions. By subjecting prototypes to real-world situations during testing, valuable user feedback is gathered to refine and improve them.

This feedback is invaluable, as it highlights the strengths and weaknesses of the solution in actual use cases. Restate follows, where insights from testing are used to make improvements. This iterative process is particularly important in AI and IoT due to the complexity and rapidly evolving nature of these technologies. Continuous testing and iteration ensure that the final product not only meets user needs effectively but also remains adaptable and up-to-date with technological advancements and changing user preferences. 

The goal is to be quick, as soon as you start collecting feedback from your stakeholders you can quickly change the course of action if needed, which means, you can make enhancements to the workflow of your AI, in any layer, like Data, ML or the DS aspect of the solution, other than enhancements you can add new inputs, remove or drop everything in case the success criteria was not achieved, fail fast and redo faster.

6. Global Prediction

The Global Design Thinking market is expected to experience significant growth between 2024 and 2031. With a steady growth rate observed in 2022 and an increasing implementation of strategies by major industry players, the market is projected to expand beyond expectations.

The worldwide market for Design Thinking is valued at $6900.0 million for this year and is projected to grow at a compound annual growth rate of 7.25% through the predicted period, adding a total of $10500.0 million by 2027.


Design thinking is a method to reach a creative and entertaining resolution of problems to achieve a good result, so we can apply this methodology to any area that “accepts” a creative approach. Over the years it has become a practice carried out by many companies internationally with excellent results. home