By Dami Adebayo
Business Process Re-engineering also called BPR is focused on the analysis of business processes and workflows. It is a management strategy that requires a review of how a business operates to identify areas of improvement, cost cutting areas and the adoption of best practices.
Artificial Intelligence also called AI is a computer technology that learns and simulates human intelligence processes and performs them via machines. They perform tasks exactly the way humans would through machine learning and intelligence i.e. ability to spot patterns. Some of the AI management technology that can be adopted by organizations include: Machine Learning, Speech Recognition, Natural Language Processing.
More and more organizations are moving towards the integration of AI or technology in general with their business processes to ensure a faster and more efficient process. The general belief is that with the introduction of AI, processes become more efficient and output increased. For example, one of the benefits of machine learning in process engineering is its ability to refine large amount of data directly, learning from the source and not depending on a pre-set formula structure, a task that is difficult and more time consuming for humans to carry out. Because of its ability to self-learn using algorithms of the input data, it can easily detect data pattern hence producing appropriate results and its ability to automate system processes help reduce risk that could arise with humans doing the same task.
Automation on the other hand is the ability of machines to carry out repetitive and mundane tasks quickly based on the pre-programmed set up. It can generally help businesses operate effectively and more efficiently but this depends largely on how fundamentally flawed or not the processes are. A fundamentally flawed process which isn’t lean cannot automatically result into better performance because of automation.
The ability of AI to simulate human behaviors and be able to eventually think for itself makes it an attractive long-term cost saving option for many businesses, this can also be a flaw because its ability to think for itself means its inability to follow pre-set rules or orders like automated systems. In automation, the system simply follows the instructions it has been given while AI looks to understand system patterns and reacts based on its understanding of those patterns.
Both AI and automation have lower rate of errors compared to humans. This is largely dependent on how they have been coded or set up and their ability to take up repetitive and mundane tasks. This means human skills can be explored in other areas giving organizations the opportunity to utilize new skills. The worry for most human beings is the ability of these machines replace them, thus rendering their skills useless and inevitably increasing unemployment.
Will the introduction of either AI or automation result into better business processes or improved output for businesses is always the question that’s asked by most organizations. There isn’t a yes or no answer to this as the success of either depends largely on the processes which are being automated. When thinking automation or AI, don’t just think speed of carrying out processes or reduction in the number of human labor required. For these to be as effective and efficient as required, it is important to review and analyze existing process to avoid using technology to carry out old habits. Automating processes that have fundamental performance issues will not make them better. It is imperative to re-engineer processes, addressing all performance issues before introducing technologies such as automation and AI.
Another question often asked is, Automation or AI? The answer to this question largely depends on what’s being automated. Automation and AI offer different benefits and their use largely depends on what the intended output is. Though they are both driven by data, the way they use it is inherently different as automation collates data and performs an output based on what it is told; AI understands the data and performs an output based on what it has learnt about the data. These systems work best together as they complement each other.
The final question often asked is, will they replace humans eventually and what does this mean for unemployment data? This is highly unlikely to happen because human interaction will still be valued and seen as better customer experience in some cases. Due to its absence of emotional intelligence and its ability to deal with unique and rare scenarios, the need for human intervention in some business process areas will still be very important.
On their own, AI, automation or humans will not give the best customer experience or give the best operational benefits. It is important to consider the aspect of BPR before introducing technology to make them efficient. The collaboration of highly skilled employees with a well programmed AI and automation will deliver the best customer experience and operational benefits for organizations.