Understanding the importance of building a Data Driven culture

<p><span style="font-weight: 400;">Although lithium batteries are becoming increasingly popular and are widely used in industries as important as consumer electronics and electric vehicles, their operating principles and the processes required to produce them are unknown to the vast majority of people.</span></p> <p><span style="font-weight: 400;"><img class="alignleft wp-image-1309" src="https://nanomate.es/wp-content/uploads/2022/04/Informatico-Mindcaps-scaled.jpg" alt="Informático | Mindcaps" width="470" height="264" />The process of making a battery involves hundreds of steps, from the construction of their electrodes and assembly of the device to its validation and final testing. Each of these steps involves new information, ranging from the characteristics of the materials used, to processing conditions, to testing and quality control. This includes both structured information, such as the plant's environmental conditions, and unstructured information, such as images generated by advanced equipment like SEMs (scanning electron microscopes).</span></p> <p><span style="font-weight: 400;">The fierce competition in the industry to continuously improve characteristics such as energy densities and recharge rates at increasingly competitive prices, demands a </span>Data Driven working culture<span style="font-weight: 400;"> from the R&D teams of companies developing new materials and energy storage cells to ensure the necessary agility in decision making and the ability to manage highly complex developments.</span></p> <p><span style="font-weight: 400;">Even though the data challenge is usually seen as a purely technological challenge, building a solid data culture requires an increased focus on the people whose way of working we want to change. That is </span>why at Nanomate we have decided to commit to a data strategy that seeks to achieve its goal through the following three lines of action: Willingness-Knowledge-Capacity.</p>

<p><i><span style="font-weight: 400;">Willingness</span></i><span style="font-weight: 400;"> is about the </span><b>attitude of the organisation and its members towards data</b><span style="font-weight: 400;">. It requires an open and curious mindset, a willingness to explore data and a hunger to learn from them. It is </span><b>also essential to value and understand data as a valuable and strategic asset for business growth and improvement</b><span style="font-weight: 400;">. Willingness requires that the people who face data challenges every day fully understand its importance and have the necessary motivation to change the way they work. To do so, we have to take them out of their comfort zone, challenge and inspire them so that they can make this step up.</span></p>

<p><i><span style="font-weight: 400;">Knowledge</span></i><span style="font-weight: 400;"> is about the </span><b>skills and competencies needed to work with data</b><span style="font-weight: 400;">. It is not just about having access to data analysis tools. It is not just about having access to data analysis tools, but knowing how to use them effectively, and to ask the right data questions to get the answers needed to solve everyday challenges. Team members need to have </span><b>backgrounds in statistics, programming, data visualisation and other related areas</b><span style="font-weight: 400;"> to understand and work with data. In addition, organisations need to include data experts such as data engineers and data scientists in the teams to further stimulate analytical thinking.</span></p>

<p><span style="font-weight: 400;">Finally, </span><i><span style="font-weight: 400;">capacity</span></i><span style="font-weight: 400;"> ensures that </span><b>people who work with data on a daily basis have the right tools to store, handle and analyse them</b><span style="font-weight: 400;">. A single battery tester used to analyse the energy capacity of a battery over continuous charge and discharge cycles can generate up to 54GB of data per day, or in other words, the equivalent of 10,000 high quality MP3 songs. In such a scenario, where the amount of information to be analysed is growing exponentially, we need to provide teams with much more advanced tools than those currently used: new measurement and characterisation devices capable of collecting process parameters and laboratory test results in real time; cloud platforms where large amounts of information can be easily stored, experimented with and innovated on; visualisation tools to explore the information collected and validate hypotheses; and advanced analytics tools to extract insights from the data that are impossible for the human eye to perceive.</span></p>

<p><span style="font-weight: 400;">At Nanomate, we are committed to a Data Driven culture as a mechanism to ensure the success of the company. We know that this challenge implies a demanding journey, and therefore we rely on the best partners to help us: we have chosen </span><b>AWS </b><span style="font-weight: 400;">(Amazon Web Services), a global leader in cloud services, as our preferred cloud computing provider, and </span><b>Galeo Tech</b><span style="font-weight: 400;">, a Spanish startup specialised in building data products, as our extended team for strategic data projects. Together with them, we have already built our first data product, the </span><b>R&D DataLake</b><span style="font-weight: 400;">, which we will talk about in future posts.</span></p> <p><img class="aligncenter wp-image-4110 size-full" src="https://nanomate.es/wp-content/uploads/2023/04/blog-datadriven-18-05-2023-en.jpg" alt="Data Driven | Nanomate" width="1536" height="1024" /></p> <p> </p>