As we’ve discussed in previous posts on the Modern Equipment Manufacturer, there are a lot of benefits that equipment manufacturers can realize if they cloud-enable their devices and establish a way to aggregate the device data from their equipment in the field. This data can be used to monitor device health, enable better, more efficient service calls and even enable device manufacturers to extend their core solution with complementary service offerings.
However, it’s one thing to aggregate and collect device data, it’s another thing entirely to do something meaningful with it. As more and more original equipment manufacturers (OEMs) adopt getaways and cloud-enabled devices, the amount of device data being harvested and stored will inevitably increase. OEMs will have to identify the best way to use that data to generate actionable insights.
One company that is helping OEMs accomplish this is Mnubo, the creators of a leading Industrial Internet of Things (IIoT) analytics solution that enables manufacturers to analyze their device data, gain valuable insights and optimize their products and services.
We recently had the opportunity to sit down with Jean-François Martin, the Vice President of Products at Mnubo, and Racha Slaoui, an IoT Data Solutions Specialist at Mnubo, to learn more about the transformative potential of data in manufacturing, and the role that Mnubo plays helping manufacturers get the most out of their device data.
Here is what they had to say:
Modern Equipment Manufacturer (MEM): Can you tell our readers a bit about Mnubo? What does the company do?
Jean-François Martin: Mnubo is based in Montreal, with a satellite office in Tokyo, and currently has over 60 employees including an excellent team of Data Scientists and IoT Data Engineers.
The company’s name, “Mnubo,” actually comes from the Esperanto word for cloud, “Nubo.” The silent “M” stands for machine. So, our company name literally means machine cloud.
Mnubo’s platform sits in the IIoT stack, where it serves as the analytics layer – a one-stop-shop for customers looking to maximize their investment in connected equipment.
Our platform helps our customers with digital transformation – which requires more than just pulling asset information into a dashboard. With our platform, users are able to analyze their data and then leverage those insights within their own business.
MEM: Why should an equipment manufacturer be aggregating and analyzing their equipment data? What insights can they extract from it?
Jean-François Martin: Many of our customers are in the commercial and industrial equipment space. For them, what’s truly important is ensuring that their installed equipment – their assets out in the field – are running and functioning for as long as possible and as effectively as possible.
They’re looking for insights around those assets so that they can monitor and analyze their performance, identify problems in advance and maximize the uptime of those devices.
Racha Slaoui: For many of our customers, aggregating and analyzing device data is a competitive advantage. Being able to aggregate data and analyze it has been a differentiator that has allowed them to gain more market share. That’s because they’re able to minimize downtime, monitor usage, better understand their products and better service their products in the field.
For example, a key differentiator for them is predictive maintenance. Analyzing device data allows them to know in advance when a failure might happen or when parts need replacement. Using this information, they can dispatch maintenance teams more quickly or even proactively and optimize operations costs.
Jean-François Martin: When a manufacturer retrofits a product to make it connected, or launches a new, connected product, they’ve put in place a mechanism to better understand their products in the field. This enables them to better understand their own products and get a 360-degree view of these assets.
MEM: Is this something that’s widespread in equipment manufacturing today – aggregating and analyzing device data? Or is this something that’s just gaining traction?
Jean-François Martin: We’re seeing more and more manufacturers retrofitting their devices to be connected devices, or are creating new data-driven products. We’re seeing a lot of these manufacturers investing in IoT. But, while we see a lot of investment in connecting these devices, we’re not seeing as much time, effort and money being invested in analyzing and using their data.
There are some early adopters that are investing in analytics for early detection and anomaly detection for predictive maintenance. However, there are much older, established device manufacturers that are simply not familiar with taking a “data first” approach to device design and maintenance.
Racha Slaoui: Many manufacturers have started developing product lines that are cloud-enabled and connected because IoT has become very trendy. But they didn’t know what to do with the data that they were aggregating and they didn’t have a strategy for it.
Now, people are starting to talk about machine learning and data analysis and they’re starting to realize they should do something with [that data]. Before that can happen, there’s a cultural shift that needs to happen within their organizations. They have to put a strategy in place and figure out how data can play into their business strategy.
MEM: Before equipment manufacturers can analyze their equipment data, they need to connect their devices to the cloud so that they can aggregate it. How are equipment manufacturers that you’ve worked with accomplishing this? Are there different ways to do this?
Racha Slaoui: Sometimes, some of the manufacturers with technical teams will try to build cloud connectivity into their devices themselves. We have seen some of them attempt to build something proprietary. However, the preferred method is often working with a gateway provider that can more quickly and easily enable them to connect their devices.
Jean-François Martin: Once they’ve implemented a gateway solution and have the data they need, they then need a solution like ours to help them leverage that data.
There is a build or buy approach to both the connectivity and data analytics part of the stack. If they try to build it themselves, there are a lot of challenges. It can take years to get them there. They can bypass that development process by using a prebuilt platform. Then, they just need to embed these insights into their own business and learn to utilize the data and insights to improve their operations.
MEM: We’re hearing a lot about HVACaaS and equipment manufacturers evolving more into service providers. How does a solution like Mnubo’s enable this?
Racha Slaoui: Traditionally, HVAC manufacturers have been product-focused companies. They focus on building the best product so that they earn customer loyalty and repeat customers. Now, they’re working to become more customer-centric companies. They want to engage with the customer more frequently. They want to predict their problems and work to proactively solve them.
Our expertise and our platform help them become more proactive and to build better products while driving down operational costs. It also allows them to analyze and diagnose anomalies. This allows them to not only sell a better product but also to sell monitoring, management and other services, enabling them to transition into supplementing product revenue with services revenue.
MEM: Can you provide our readers with an example of your platform in action? Do you have any customer case studies you can share?
Racha Slaoui: One particular customer of Mnubo’s is a global HVAC manufacturer. This particular customer was looking to reduce operational cost with connected products. They also wanted to better understand the capacity and utilization of their products in the field.
Mnubo’s solution has helped them to increase the efficiency of their devices and reduce operational cost for their customers. Predictive maintenance has resulted in 20 to 50 percent savings in call-center costs. Demand planning optimization has resulted in 20 to 30 percent savings in warehousing costs.
The solution has also enabled them to make another important change within the organization that increased transparency and visibility into their device data. As a global company, each continent had a dedicated team that was aggregating and storing data differently. Mnubo brought that all together and aggregated it in a central location and in the same format – bringing it all together so that they could analyze data globally.
Jean-François Martin: That same customer was also trying to productize the IP they were building. They were creating innovative energy utilization algorithms, but they couldn’t share them internally or bring them to market. Mnubo has helped to centralize the company’s IP and has even enabled them to productize and monetize that IP by ensuring that their tools and algorithms can be leveraged by the rest of the organization.
For additional information about Mnubo, visit them online at www.mnubo.com.