Disconnected systems are an inevitable consequence of the way that IT and organisational processes evolve. IT solutions are generally introduced incrementally. This means many companies introduce software department-by-department, separating elements such as finance, customer management, and supply chain management. This leads to numerous accidental inefficiencies, such as overlaps, miscommunications, and data errors.
Duplication is one of the most prevalent issues in data management. Duplication can result in incorrect information in multiple systems, resulting in a range of negative outcomes. Many companies expend unnecessary resources on de-duplication efforts. However, as data duplication is normally caused by a combination of disconnected systems and human error, it is something that can be more efficiently tackled by training, empowerment, and having the correct preventative technological tools in place.
Transparency and authenticity is an increasingly important element of business management. Most people recognise the problem of GDPR breaches, which led to Google being given a £44m fine in January 2019 – just one of over 200,000 reported cases since GDPR began. However, data errors of any type can cause significant problems and result in poor business decisions. Inaccurate accounting due to data duplication can land companies in very hot water, and issues such as inaccurate human resources data can lead to costly mistakes in terms of personnel management.
There is nothing more frustrating for a customer than their request being ignored. More and more companies are using automated systems to ensure that transactions are completed successfully and consumer queries are answered. Chatbots can be an excellent way of ensuring this happens of course. However, automating customer interactions relies entirely on data accuracy.
Disconnected systems place a significant burden of responsibility on humans to take on the role that a good software system would normally do. That errors result is inevitable. The ideal solution is one that makes life easier by reducing the error risk by connecting and fact-checking data flows and consistency, whilst being easy and accessible to use. This approach minimises the potential for problems such as data duplication and data errors , but also empowers employees to feel in control of data.
The ideal system is designed to require minimal training, and should be a comfortable working space that invites familiarity and enhanced data awareness.
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