Page 23 - Bizmod Thought Leadership Articles 2020

One of the main reasons that businesses decide to embark on an IA or robotics process is for cost reduction and improved efficiency.
When evaluating cost reduction,
the leadership team will typically
look at a headcount reduction to generate savings. As much as these initiatives have the potential to reduce headcount, there is a definite requirement for additional headcount – individuals who are data and data clean-up professionals are a precursor for IA, as well as individuals with the technical skills required to maintain what has already been built.
The business may find itself saving costs on the volumes of lower skilled employees, but at the same time it will need to introduce higher skilled technical resources. Opportunities will open up for humans to focus on the skills that only humans possesses and these can be applied to create more innovative, customer centric advantages.
The focus of the business is usually on launching the IA and robotics initiative.
This is a short term objective that is aimed at technology adoption. The longer-term view is ignored. This
is needed to focus on determining the impact and cumulative effect
of all the IA initiatives on employee skills. If the decision is taken at a business level to reskill employees it is important to realise that this is a process that will take time. Therefore,
the sooner a clear view is established on what kind of skills are required, the better.
If the mundane, repetitive, large volume, data capturing, process
steps are automated – what is the organisation doing with the human capacity that it will be releasing? Some of the future skills identified talks to improved customer service, data cleaning and management, upskilling business users to develop and maintain their own intelligent automation initiatives. If the business choice is to re-skill people these kinds of initiatives have to be formalised and directed.
The focus on data, prior to embarking on an IA initiative, cannot be overstated.
The pace at which ROI can be achieved is directly linked to the quality of data available. Many IA initiatives come to a grinding halt because of data that has not been cleaned and maintained previously. Theoretically the technical part of the project can be “ticked off” because the bot was built and it is working, but the ROI can’t be achieved because the quality of the data is insufficient.
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