Usually, you are not an expert in the field of expertise for which you are asked to develop an ICT solution. In these cases, domain or context information you receive from stakeholders and users, might not be clear enough for you to interpret and understand well. The clarifying pattern helps you to ‘dig into the matter’ and get a better understanding of the information you have collected, before you can start to explore a solution.
How?Field methods, into Library and vice versa. Once your understanding develops and the Field information becomes more meaningful, you can break out of the loop to start thinking about a matching solution using Workshop methods.
The solidifying pattern can be used during the early stages of a project, especially during the problem analysis. It helps you to understand how project specific aspects can be solved by investigating how they are solved in other contexts, comparable environments or in a more generalised form.
The loop between Field and Library generates a solid knowledge foundation to work on but it does not necessarily bring you closer to a relevant and applicable solution. Solution explorations, including methods from Workshop, need to be included regularly.
Taking Field information into the Library is useful but an overly extensive library-based research may take you away from the context. Make sure the loops are short and your enriched information flows back into the context regularly. Your objective should be to obtain a better understanding of the context and not to do an extensive literature study.
If you are not able to find relevant resources you might have to repeat or refine your Field methods. It might, for example, turn out you did not filter out the right keywords for a proper literature study. Extending your Library methods (e.g. with an expert interview) can also help and sometimes, when the information from your Field methods is too fussy, you might need to use the Clarify Research Design Pattern first to be able to return to the Solidify Pattern.
Examples from practice
Building a backend to host large datasets
A technical university asks you to build a backend that hosts large datasets generated during scientific experiments. Your backend should be able to (securely) support scientists around the world to analyse the data. In order to be able to think about a solution, you need to understand what the scientists mean by ‘performing research on the data’. Your project starts in Field with interviews and/or exploring user requirements. The scientists may talk about statistical data manipulations and calculations that you need to understand in more depth by using Library methods such as literature studies. They might even bring you in contact with one of their experts (expert interview) to help you.
On the other hand, community research might lead to the idea that machine learning functionality should be part of the solution, and you take this suggestion back to the scientists (your stakeholders). Furthermore, the loop between Field and Library helps you to understand what ‘secure’ in this context means. International standards (ISO) found through conducting literature studies and evaluated during an expert interview with one of the staff members at the university, are used as input for a discussion with the scientists. This helps to clarify the level of security needed for the project.
Break-out - at a certain moment your insights are developed enough for you to break-out of the Field-Library loop and to start thinking (concepting, brainstorming) about the solution (IT architecture sketching). You take your sketches and ideas back to the scientists and discus your solution (direction). This helps you to validate your sketches.
|(1) What do the researchers need?|
|(2, 4) How can I increase my knowledge on topics (e.g. architecture, Machine Learning, security) that are involved?|
|(3, 5) How does my increased knowledge help me to better understand what the researchers need?|
|(6) Break-out Create sketches, scenarios etc. that help you make your ideas about a matching solution more concrete and discussable.|
Fire fighters and IoT
You are asked to work on an IoT project with the objective to enable fire brigades to use their own local area network (LAN) communication whilst fighting a fire.
Fire brigades have their own protocols and standards when it comes to how they fight fires, and they use a lot of ‘lingo’ (specific terminology) when they talk about their protocols and strategies. Being aware of this, you decide to first read up on these terms using online available resources (Literature study, Library). Only after you have prepared yourself properly, will you conduct the interview (Field) with the fire brigade in order to contextualise the assignment.
During the interview, some new domain specific terminology might be introduced as well as other information that requires further research (such as examples of other solutions) and this might bring you back to the Library methods.
|(1) What are typical terminologies and protocols/strategies that fire brigades use?|
|(2, 4) How can I use this knowledge of terminologies and protocols/strategies to find out what fire brigades need?|
|(3) How can I refine my knowledge of the fire brigade domain?|
|(5) Break-out Create scenarios, sketches, (throw away) prototypes, etc. that make your ideas for a matching solution tangible.|