Most business decisions that change the course of a business are very hard to make, but there is one that should be a no brainer—the implementation of predictive machine learning (ML).
If the market is a stage upon which there is an ongoing battle, then one of the best weapons any organization has is its data. But of course, it’s what you can do with your data that counts. Predictive machine learning technology doesn’t just continually rely on analyzing archived data, but rather draws upon the old to create new data and identify patterns.
Artificial intelligence (AI) and ML have brought self-updating algorithms that uncover hidden patterns in past data, strengthening the backbone of predictive capabilities that inform business decisions and outcomes in the future.
This self-updating process means that the more predictive machine learning is used, the more data that is created and brought together in new ways, resulting in different perspectives and value. It also means that while, the machines are doing the repetitive work through automation, employees are available to focus on higher value tasks that may draw upon such insights to enhance the end-to-end customer journey, generate profits, and/or reduce spending costs.
The value of ever-evolving predictive machine learning capabilities took center stage as the table topic this week on Episode 2 of the Game-Changing Predictive Machine Learning radio series (available on demand now). Once again, host Bonnie D. Graham extended the talk beyond boardroom walls by giving the global microphone to the experts. They shared their own experience and thoughts on the value that predictive ML brings to businesses in terms of efficiency and ROI, as well as the challenges that come with it. This week’s guests were:
- Gil Gomez, Managing Director of Enterprise Operations—SAP for Deloitte Consulting LLP
- Hudson Harris, Chief Engagement Officer, HarrisLogic
- Timo Elliott, Global Innovation Evangelist, SAP
The discussion was full of new ideas, interesting perspectives, and intelligent predictions. Panelists touched upon various concepts such as data governance, data confirmation bias, and job-automation.
Here are some episode highlights:
- Gil Gomez “is a big fan of customer insights. There is so much information available, and this provides huge value for getting a 360-degree view of your customer, what they want, what they need, etc.” which he suggests will ultimately lead to greater retention and ROI.
- Hudson Harris predicts that predictive machine learning will “free us to restart the innovation cycle” by automating tasks and allowing the focus to be directed towards building upon what we know to generate new meaningful knowledge and insights that will boost your business.
- Timo Elliott suggests that predictive machine learning “and new technologies give us the ability to intervene before things go wrong, rather than continuing to simply looking at why they did. Companies are going from reactive to proactive, which creates a better outcome for both customers and saves time and money for businesses”
Predictive analytics continuously evolves and grows in fascinating ways that can save us time, money, and energy. As a technology that brings wide-spread efficiencies, uncovers new intelligence, and improves ROI while reducing costs, it’s bound to remain a hot topic for the business world.
We’ll keep the conversations going in our “Game-Changing Predictive Machine Learning” radio series. (All episodes will be available for replay on the series webpage after they air. You can go to the series page and bookmark the show to stay up-to-date.)
Tune in for the next episode on August 8th at 2pm EDT on VoiceAmerica Business Channel.
- Listen to Episode 1, The Making of a Citizen Data Scientist: Challenges and Hacks
- Listen to Episode 2, ROI beyond Cool
- Read the other blogs in our Machine Learning Thursdays blog series for more on topics like this one.