Since the launch of our Cloud-enabled sensor portfolio in 2018, Miros has become a staunch advocate of co-creation processes, finding great value in collaborative development alongside key customers. By following a more market-led path towards scalable, in-demand applications, we can better ensure that our output is directly relevant for the markets in which we operate.
But why are we on this digitalisation journey in the first place? And why do we want to support our customers on theirs? Well, for our part, the objective is to keep getting better at solving customer problems and, in doing so, to continuously offer better and more fit-for-purpose solutions. For customers, the objectives are often rooted in the efficiency gains and improved decision-making abilities facilitated through broader data access, scalability of solutions, and an understanding of what can – and should – be optimised in the first place.
In order to make meaningful progress in any digitalisation journey, however, there are four key ingredients that need to be in place:
- The right data with the right quality. By this, we mean in terms of resolution, accuracy, sampling rate, etc.
- An efficient platform for accessing, downloading, and working with that data. The same goes for storing, processing, visualising, distributing, and integrating the data too. Security is also fundamental here.
- Competence, both in terms of data science as well as building robust platforms for data handling from sensor to cloud and, crucially, a thorough understanding of the application domain. This is also true for the development of the applications themselves and, of course, the hardware!
- Deep insight into the problems affecting the end users, targeting problems with a large business impact that can be solved in a cost-efficient way with the available data, platform, and competence.
The Four Pillars of Digitalisation: What Happens When One is Missing?
In many digitalisation efforts, however, one or more of these essential ingredients is often missing. The data may be of poor accuracy, or may not be sampled at a fast enough rate. There might be gaps in the data too, or it may simply be too complex to handle due to sub-optimal formatting or structure.
Meanwhile, the available platform might not be efficient enough in the way it solves the core tasks of collecting, storing, processing, visualising, distributing, and integrating the data. If problems arise and there’s no easy way of processing the data due to issues with access (for example, having to download to a PC before any work can be carried out, then having to prepare reports based on the findings locally before sending them onwards), things are going to slow down. If it’s not possible to do the data science where the data is (either in real time or as retrospective analysis) before making the results directly available to the customer, then there’s room for improvement!
At the same time, though there may be a great deal of competence available, some essential parts might be missing. Vital elements such as data science proficiency, knowledge about the end application or the pain points of the end user, or even an inability to innovate on the platform itself. This can be stifling to any digitalisation effort. There could be one or many problems, but they might be poorly defined or understood. Without a deep understanding of the real issues at hand, there will likely be no meaningful outcome and the customer won’t benefit from any of the desired efficiency gains or decision-support tools.
How Does Miros Work With Customers?
At Miros, we try to step back and see the big picture. We work alongside key customers on frequently-occurring problems in order to ensure that we’re solving real-world issues. In this way, we can remain laser-focused on overcoming our partner’s challenges, whilst creating something applicable to others in similar situations.
Additionally, we work ceaselessly to keep the four pillars in place, offering high-quality data, a high-quality platform that gives easy access to the data and makes it easy to share, a competent team that aids our customers determine and access the most relevant and insightful analytics for each given case and, finally, unending curiosity, interest, and competence to get a deep understanding of the challenges our customers are facing.
In short, through collaboration with customers, we are able to bring together the data, the platform, the competence, and the specific domain knowledge required to be able to bring about tangible, impactful results.