Unlocking the value of automated data management
Author : Simon Burgess, Xerini
22 August 2024
Simon Burgess, COO at data and process orchestration consultant Xerini, explains how businesses can optimise their existing systems to improve data collection and free up time.
According to a study by McKinsey Global Institute, over 45 percent of the manual work done by employees could be automated, with emails, data collection and data entry reported as the activity that took up most of an individual’s time. Manual data entry, or moving data from one place to another, is time-consuming, introduces human error that we must then spend time fixing, and takes valuable team members away from more creative tasks – so why do we still do it?
Moving away from manual processes is becoming increasingly essential in today’s fast-paced, AI-aware world so that businesses remain competitive and relevant. Manual data collection is time-consuming, error-prone and lacks scalability, which can result in inefficiencies, inaccuracies, and delays in decision-making. Yet, there are still businesses that haven’t jumped to implement these new technologies. Why?
Legacy
There are a variety of reasons why businesses still manually collect data. First, is that typically there are still legacy systems in place that were established before automated solutions became available. If a system has been working well for the last decade, most organisations don’t feel the need to overhaul their system. Businesses can also be nervous about unpicking their legacy systems, especially if those that originally implemented the infrastructure are no longer at the company.
Businesses may also have concerns about the reliability or cost of implementing such systems, often believing it is too difficult or expensive a project to bother starting. This is usually paired with a lack of awareness on the benefits of automating data collection, where infrastructure isn’t routinely checked to identify potential risks, issues or opportunities.
However, many businesses across all sectors are seeing the benefits of AI, and choosing to invest. Automated processes are a solution that offers improved efficiency, accuracy, and scalability. AI tools can also better handle larger data volumes, enhancing security, productivity and growth.
Security
Manual processes can introduce a variety of security risks such as human error, data loss, or unauthorised access to sensitive information. For example, misplacing documents that contain sensitive data may result in someone gaining unauthorised access, or potential data breaches. Manual processes also lack consistency and auditability across departments, creating gaps in security protocols that could be exploited.
Automated methods can mitigate these risks and enhance security by implementing consistent security policies like encryption, access controls, and audit trails. These processes also improve data quality, using data validation and cleansing techniques that can restore data and centralise it so that everything is in one place.
Productivity
Manual data entry is often time-consuming, with McKinsey stating that 40 percent of workers spend a quarter of their work week on repetitive tasks. Many people argue that AI risks removing jobs from employees as technology becomes more sophisticated, to the point of potentially over-taking manual decision-making. In reality, the same McKinsey report found that less than five percent of jobs can be fully automated. So, the consequence of fearing AI implementation is a team of employees that spend more time doing repetitive tasks than the job for which they were originally hired. Not only does this waste time, but can negatively affect staff retention.
Automated methods can significantly improve efficiency by reducing the need for manual labour, allowing employees to focus on more value-added tasks. This not only enhances overall productivity and streamlines operations, but AI will also offer more support, producing happier employees that are more motivated and can do their jobs better than before.
Growth
Manual data collection limits scalability and hinders the ability to process and analyse large volumes of data effectively, if at all – limiting potential business growth. Alternatively, automation and AI-driven methods can handle massive amounts of data from multiple systems to derive valuable insights. The ability to access their data more effectively enables businesses to make more data-driven decisions that foster growth and can offer a significant competitive advantage.
Implementing automated processes enables real-time data capture and integration from multiple sources, enhancing the accuracy of collected data and providing insights and analytics much faster. Data-driven decision making reduces the guesswork for strategic decisions, and can provide a competitive advantage by uncovering valuable insights and trends.
Getting started
Knowing that your data management needs improvement is one thing, but getting started is another. AI still holds a lot of scepticism and often isn’t considered until issues like data breaches occur. Instead of reacting to an issue, businesses should encourage proactivity when exploring the potential of new technologies and processes. Then, once businesses know that their data management needs improvement, having a strong strategy outlined can help them stay on track. If businesses have knowledge gaps on AI technologies, it’s easy for them to spend far more money than necessary without seeing many benefits.
To implement AI processes effectively, a cultural change is often necessary before manual processes can be overhauled. Employees must understand and embrace the benefits of automated and AI-driven approaches, requiring training and support to adapt to new systems and workflows. Leadership commitment, effective communication, and employee engagement are all crucial to drive cultural change and foster a data-driven mindset across the organisation.
Getting a fresh set of eyes on current data collection and management processes can also help to identify what needs changing early on. Particularly for organisations where data management processes have been in place for a long time, it can be difficult to take a step back and think about what could be improved.
The journey of upgrading data collection should not be underestimated, and isn’t something you can do in the background. The entire organisation must be trained and supported in using the new system to ensure its success. If managed properly, businesses can reduce costs by ensuring that AI tools are compatible with current infrastructure and offer a better user experience.
Want to improve your data management strategy? Visit https://xerini.co.uk.
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