EDITOR ’ S QUESTION
Truthfully , Machine Learning can be applied anywhere . However , the most practical and most efficient way to get started is by focusing on decision points . Giving your employees the ability to make better decisions with more insights in an augmented fashion will increase comfort levels . Great solutions will allow you to progress from augmented intelligence to full smart automation at your own pace .
Be sure to get well beyond the marketing pitch . It ’ s important to understand the details of the solution because you should never make a selection based on one project . Using Machine Learning in your enterprise should be a long-term , repetitive engagement and therefore you will need a flexible platform to grow with your organisation . Otherwise you will be stuck with a massive TCO per project . Select a vendor whose technology matches the creative culture of your organisation .
Endless compute resources is the easy answer , but it ’ s actually more about giving users the ability to use Machine Learning without building out or connecting technologies for years . Now we have platforms that allow quick experimentation and implementation so efficient ROI is quite real with the right vendor .
Endless compute resources is the easy answer , but it ’ s actually more about giving users the ability to use Machine Learning without building out or connecting technologies for years . Now we have platforms that allow quick experimentation and implementation so efficient ROI is quite real with the right vendor .
Some industries tend to be more progressive , such as industrial manufacturing , distribution , and more . However , even within certain industries it ’ s more about the companies who aggressively embrace new opportunities and technologies that succeed . Those are companies that tend to continuously find new ways to pivot and expand their business , regardless of industry . The buy-in is important from business because ultimately IT will want to shift the mindset from “ ask ” to “ try .” We live in a world where everything doesn ’ t need to be a funded or debated ask to finance , and instead should be a solution that allows employees to be inquisitive about how the business can be better , more efficient , or more diverse .
Getting it to production and into end users ’ hands is by far the biggest challenge . Finding tools to perform the machine learning is actually the easy part . Having the right ecosystem to securely access , host , and administer those insights in a meaningful manner to users is where companies struggle . Therefore organisations should really focus their selection on
vendors that prioritise the consumption of insights as opposed to the science itself . The science becomes a commodity more quickly .
The future is not just bright , it ’ s inevitable . The companies that embrace the changes and realise that Machine Learning is just a creative medium will quickly see how they can differentiate themselves in terms of talent and other ways beyond just their products and services . However , you will need a solution that matches your desired culture and not one that simply checks the box or has the best marketing . p
RICK RIDER , VP , APPLIED INNOVATION , INFOR
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