SMEs, or small to medium enterprises, also have a duty to lessen their environmental impact. One way this can be achieved is by applying data science techniques. Here is how this can be done.
Companies generate mass amounts of data. For example, whenever a sale is made, a business contract is signed or a supplier alters their prices, data is generated and stored. With this data, there will also be a link to data concerning the environment, and this may be direct and easy to gather, for example quantity of carbon released into the atmosphere, or it could be less direct or indirect, such as energy required to run their servers. As such, there is not always a clear picture of a business’ environmental impact.
Data science can change this in various ways. One way is through aggregation of data, and subsequent visualisation of data. By doing so, categorising and clustering data can make it more clear what services or products may be more polluting, for example. However, this works more for data where you have statistics such as carbon released into the atmosphere.
Data science can also be leveraged to find less direct links. By bringing together multiple data sources, it can be easier to find less direct and indirect or hidden relations between data. This is also good in terms of the carbon footprint and ecological impact across the supply chain, as by aggregating data from vendors and suppliers you would be able to have a more comprehensive and holistic idea of your wider impact.
Identifying waste is another way in which data science can lead to SMEs being more eco friendly. Data science techniques can identify where optimisations can take place.