Overcoming Implementation Challenges
Many companies have high hopes for the use of AI-powered automation in their organizations, but they remain slow in adopting it and face many challenges.4 One issue tends to be a heavy focus on technology without thinking about the underlying end-to-end processes that they are hoping to automate. The best approach is to start by fully evaluating the needs of the end customers and then analyzing and re-engineering the existing processes. Technology should be used strategically to automate the processes where it will have a major benefit, while other processes can be eliminated. For some functions, it is more efficient and effective to use manual workers, located in onshore or offshore locations. Understanding what technology to use, and in what areas, takes experience.
The optimal solution combines automation technology and a skilled workforce, operating seamlessly together. This is made possible through careful process design. Just deploying technology without thinking holistically about the whole operation will lead to failure.
Also, the underlying infrastructure should be based around the process rather than a specific technology. A flexible architecture is important to be able to exchange technology if needed in a fast and easy manner. Without this flexibility, companies can invest heavily in digital transformation, only to find that their systems are obsolete in a few years.
This highlights an issue that KPMG believes is due to a ‘talent gap’.4 Many companies don’t have the in-house expertise to manage major transformation projects, or the experience to select the right technologies and apply them effectively in an operations environment. As a result, they end up with multiple technology vendors all working in different areas, leading to disjointed systems. Partnering with an experienced end-to-end provider can mitigate some of these risks.
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