FEATURE : MACHINE LEARNING
Tony Nkuna , Solutions Consultant , TechSoft International revolutionise an enterprise ’ s business how should CIOs and their IT teams go about selecting the right tools and systems ?
Dr Nicola J . Millard , Principal Innovation Partner , BT , reiterated that no amount of secret sauce will revolutionise a business unless its data is in order and of high quality .
According to Millard , Machine Learning does not work by magic as it depends on data and if that data is unstable , inconsistent , and spread among multiple legacy systems , it becomes more difficult and far more expensive to do . “ Aside from data , enterprises also need to step back and ask what problem they want Machine Learning to solve and whether it will actually solve it . For example , if they want to deploy a chatbot to improve customer experience , does it actually improve it or just add another level of frustration for customers if the ‘ bot ’ hits a dead end and abandons them if it can ’ t understand what they want ,” she said .
Ramprakash Ramamoorthy , Product Manager , ManageEngine Labs , said your model is as good as the data you train on and spurious correlations , biases , data imbalance present in your data can adversely affect the quality of Machine Learning model ’ s prediction .
“ Organisations should track datasets and make sure they comply with local regulations and are free from inherent biases . Sometimes labelled data availability would be a challenge . For example , there are practically no commercial grade labelled datasets for service desk sentiment analysis , but you have a wide range of datasets available for e-commerce product reviews , hotel reviews and movie reviews ,” he said .
Ramamoorthy pointed out that transfer learning techniques can help bootstrap your small service desk dataset with the learning from the larger consumer datasets and whatever process used to generate and label datasets , will have to run fairness checks before deployment .
Enterprises need to understand how Machine Learning will integrate with legacy systems , processes like in the contact centre , how much training it will require and what the business case is given that return on investment ( ROI ) may take some time .
Tony Bartlett , Director , Data Centre Compute at Dell Technologies South Africa , agreed with Millard and adding that : “ Firstly as with most systems , enterprises are advised to look to vendors who can provide an endto-end solution . Machine Learning systems are part and parcel of a broader business strategy , which includes Digital Transformation , cybersecurity , Edge Computing , automation and data analysis to name a few .”
Bartlett said enterprises should consider whether the vendor they rely on for Machine Learning solutions has the technology depth , breadth and specialisation to meet their requirements whether it be at the Edge , core or cloud .
“ As the volumes of data increases and systems are tasked with processing more data , in real time , IT systems will need to depend on high performance computing to keep up with the demands and technologies such as GPU ’ s , FPGA ’ s , high speed memory and storage are essential in deriving outcomes in real-time ,” he said .
Data quality
With data and AI playing a crucial role in any Machine Learning deployment , experts are urging CIOs and business line executives to ensure data quality .
Getting business buy-in
Most CIOs and IT leaders have faced resistance from their C-level peers when securing buy-in for a Machine Learning system deployment in their organisations .
BT ’ s Millard said that CIOs and IT leaders need to ensure that the wider business doesn ’ t get carried away by the hype around AI and Machine Learning .
“ They need to work with the wider business to identify where deployment of Machine Learning is appropriate , likely to deliver ROI and above all deliverable . There may be a need to completely re-engineer legacy IT infrastructure , data and processes . CIOs and IT teams need to engage with the rest of the business to gauge their appetite to do this and ensure that investment budgets are realistic ,” she advised .
Rudeon Snell , Senior Director : Industries and Customer Advisory , SAP MENA , believes it is imperative to lead with business value and AI is a tool that can be used to drive business outcomes that matter to the organisation .
“ By leading with business value and showcasing how potential solutions are able to impact the metrics that matter to the organisation , whether they are internal or external AI solutions , it will provide CIOs and IT leaders with the credibility among their peers for how technology can drive business differentiating capabilities that move the organisation forward ,” he said .
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