Five rules to building a future-proof automation strategy
Automation is a continuous process, and companies must be clear about what they would like for it to achieve
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The recent discussion between Elon Musk and Jack Ma has certainly stirred up another round of debate around AI and Automation. Automation, AI and Big Data platforms are being endorsed by organisations, and investments have gone into millions. In fact, it has been estimated that by 2020 almost 40 percent of basic accounting work will be eliminated by Robotics. Automation in many interesting ways has been explored and implemented to bring ease and precision in our routine jobs.
CXOs from diverse business segments are gearing up to implement Robotic Process Automation (RPA) and other emerging digital technologies such as Artificial Intelligence (AI) and Machine Learning (ML). Businesses are going digital to stay relevant and competitive within a connected world.
The idea is to blend-in these technologies within their diverse business processes to enhance cost effectiveness and drive efficiency across the organisation.
While RPA and Automation have gone further beyond conceptualisation, there have been questions around their implementation and effectiveness. Approximately 50 percent of initial automation projects or pilots are still tagged as unsuccessful based on their targeted goals.
Based on my extensive interaction with customers and our internal stakeholders in the last couple of years, here are some of the key aspects to pump up the stakeholder Happiness Quotient with automation projects. 
It is essential for organisations to define what they need to achieve with automation, as automation is not always about saving the dollar. I have come across multiple customers who intend to enhance customer experience; some want to minimise mundane activities for their team members for better employee satisfaction.
For instance, use of process mining and discovery tool is always a good solution for selecting the process. While it is a good starting point, it is important to analyse the data with a domain and operations perspective to lay out the automation strategy.
As we address various opportunities for automation, there will be a time when the process identification for automation will reverse and we will start looking for activities that require human intervention.