Every single project leverages Intellify’s Intellectual Property and delivery frameworks, resulting in less time spent on project set-up and low-value tasks. This means more time on developing tailored, value-adding solutions – ensuring your business gets the best possible outcome.
What Exactly is Machine Learning?
Machine learning is the next progression of big data and fast data analytics. Big data involves analysing large sets of data to reveal patterns and trends in order to build stronger relationships with customers and make business processes more efficient. One step on, fast data focuses on applying big data analytics in real time to proactively solve issues and monitor operational health.
Machine learning (the task of teaching a machine to algorithmically learn a task without explicitly programming it) pertains to a variety of other fields such as deep learning (artificial neural networks that mimic the human brain) and statistical learning (using statistical algorithms to help machines formulate and validate hypotheses). In greater context, machine learning and data science facilitates predictive analytics, identifying trends and pattern in data and experience to help make more informed decisions. For example, an inventory optimisation system is able to use its information on stock levels and historical purchasing data to forecast future demand and subsequently optimise inventory holdings.
A recent survey by MIT Technology Review Custom and Google Cloud (2017) revealed 45% of implementers found they were able to extend their data analysis and insights with machine learning – with 26% feeling they have achieved a competitive advantage of measurable value in the marketplace. According to Chappell and van Loon (2016), companies using machine analytics are:
2x as likely to use data to make well-informed decisions
5x as likely to make decisions faster than competitors
3x as likely to execute decisions faster than without machine learning
2x as likely to have financial results in the top 25% of similar companies
Machine learning can be applied in almost any industry and enable companies to use their existing data to improve their business efficiency. According to MIT Technology Review Insights (2017), the most common applications include:
Image recognition, classification, and tagging (47%)
Emotion/behavioural analysis (47%)
Text classification and mining (47%)
How Machine Learning Can Benefit your Company
Machine learning can benefit a company in many ways, including:
When there is no available human expertise
Human expertise takes a large magnitude of time and effort to manifest. Machine learning algorithms are able to learn from experience in a fraction of the time it takes for a human.
When decision making is based on human intuition
Machine learning algorithms reduce key-person risk by consolidating intellectual property and expertise. Moreover, machine learning algorithms are able identify and capitalise on subtle patterns that would normally be missed or identified as intuition
When solutions should be personalised
With the prevalence of hyper-personalisation, machine learning enables businesses to effectively target and personalise brand engagements and solutions based on customer attributes and preferences at a massive scale
When solutions are monotonous
Machine learning systems perform best when solutions are monotonous and repetitive. The adoption of this technology will enable employees to work on the things that matter more to them.
When scalability is required
Machine learning systems scale to the compute power of the organisation. In contrast, tradition systems are limited to human capital. For example, an automated chatbot agent exhibits accessibility and scalability that is far beyond even the largest customer service workforce
Overall, it’s not hard to see how machine learning can help streamline processes and decision-making with superhuman accuracy. With the right strategy, adoption of machine learning processes will drastically boost a company’s competitive advantage.
Chappell, N, van Loon, R 2016 ‘Machine Learning Becomes Mainstream: How to Increase Your Competitive Advantage’ Data Science Central<http://www.7wdata.be/data-analysis/machine-learning-becomes-mainstream-how-to-increase-your-competitive-advantage-3/?utm_source=newsletter&utm_medium=email&utm_campaign=machine_learning_becomes_mainstream_how_to_increase_your_competitive_advantage&utm_term=2017-12-13>
MIT Technology Review Insights 2017 ‘Machine Learning: The New Proving Ground for Competitive Advantage’ MIT Technology Review <https://www.technologyreview.com/s/603872/machine-learning-the-new-proving-ground-for-competitive-advantage/>
Van Loon, R 2017 ‘Securing Competitive Advantage with Machine Learning’ Dataconomy<http://dataconomy.com/2017/09/competitive-advantage-machine-learning/>