Implementing differential privacy in an organisation's systems involves several steps. Firstly, it requires understanding the specific privacy needs and data characteristics of the organisation. This involves determining the appropriate level of epsilon, the privacy parameter, which dictates the degree of noise to be added for privacy preservation. The organisation must then integrate differential privacy algorithms into their data processing pipelines. This often involves employing software libraries or frameworks designed for differential privacy, which can handle the addition of noise to data queries or the data itself. Additionally, staff training and awareness are crucial, as differential privacy introduces new concepts and practices in data handling. Organisations also need to monitor and update their differential privacy practices continually to adapt to evolving data landscapes and regulatory requirements.