Achieving a deeper understanding of the information that's already available to you can trigger major breakthroughs for your business, helping you exceed your goals and propelling you toward opportunities that you might not have even considered.
The key to those breakthroughs is figuring out how to unlock the hidden insights in your data. That can seem like a daunting task, given the truly dizzying amounts of data available to businesses in the Industry 4.0 era — especially if they're getting real-time data from thousands of IoT devices.
Connecting the dots isn't so hard when you've got a small and manageable set of dots to connect. But as the number of data points increases, the possible connections between them grow exponentially, and it takes a lot of computing power to precisely map all those connections and surface the important patterns and trends.
That's part of why the neural networks that power AI and machine learning are so transformative. They make it possible to cut through the noise and detect patterns that would otherwise get missed.
How AI Provides Superior Insights
You might also think of AI as functioning a bit like a pair of 3D glasses: It helps you see things that would be unclear without it.
By using Microsoft's Power BI dashboards, for example, you can draw on the power of AI to monitor your data, surface the important metrics, and then tell the story through powerful and easy-to-understand visualizations. These robust data dashboards can help you do everything from detecting security breaches to figuring out which products are most successfully driving your revenue.
Boosting Sales with Better Product Pairings
Some product pairings are obvious: syrup with pancakes, or paintbrushes with cans of paint. But others are more subtle and may not be apparent without the powerful combination of a strong foundational set of data and AI-powered analytics, which can help identify those less obvious complementary sales products. For instance, using AI can highlight that when you position product A alongside product B, you can experience a substantial boost of 5% in sales—a significant advantage for your business.
How Machine Learning Helps Stop the Churning
Spotting and addressing customer churn is another great example of what machine learning can do. It costs more to acquire new customers than to hold on to the ones you have, so the ability to use analytics to detect customers who are drifting way, or at risk of being captured by your competitors, is potentially game-changing. Using predictive analytics, you can reach out to those customers whose interest is waning with well-timed discounts and promotions, or even develop subscription-based models or loyalty programs to help keep them in the fold.
Defeating Downtime with Predictive Insights
We frequently see manufacturing facilities that are depending on one or two mission-critical machines that do 80% of their business — and those machines are often running 24/7. If one of those machines goes down, the result is painful downtime that can lead to production delays, revenue losses, and unhappy customers. Both your bottom line and your top line wind up taking a hit.
But thanks to machine learning and IoT sensors, you can draw on real-time data to identify equipment that may be getting too hot, going out of tolerance, or at risk of developing other kinds of diagnosable hiccups and coughs. And then you can step in to make sure those sine qua non machines continue to function on schedule, protecting your balance sheet and keeping your customers happy.
Data That's More Than a Fair-Weather Friend
MRP is another place where predictive analytics can help put you ahead of the game. Maybe you're using a kind of "brute force" accounting to decide how to allocate costs among ten different product lines — 20% here, 5 percent there, etc.
But with predictive analytics, you can get more sophisticated. You can identify trends like seasonality and other less-apparent cycles, so you can change allocations dynamically to match trends you wouldn't have otherwise known about.
Machine learning allows you to factor in a lot of external data that goes beyond what's in your own ERP. Like weather data, for example.
Suppose you have a product line that's very sensitive to heat or humidity. You might be able to draw on weather data to augment your existing data, so you can change the chemical properties of the product to make it more humidity resistant.
Columbus recently worked with a retail organization that sells high-end outdoor products as a major component of their business. They found that some sizes and products sold better in certain stores than others, and they wanted a better understanding of the optimal product mix in each store. That's the kind of complicated data picture that machine learning can help you bring into focus.
One of the other key questions they needed to answer was weather-related: when to bring out the heavier gear, like winter gloves or insulated vests and jackets. So, the ability to analyze weather trends and patterns offered an opportunity to achieve better timing and improve their margins.
There are plenty of other ways that the capabilities of AI can help you make it rain — or provide an umbrella to get you through downturns and disruptions. To learn more, schedule a call with Columbus so we can help your organization tap into the full capabilities of AI.