Product development is an essential part of business for original equipment manufacturers (OEMs).
Whether a company makes elevators, humidifiers, air conditioners or any other type of equipment, they undoubtedly have competitors in their market. Those competitors are constantly working to innovate new, more resilient and more advanced products to help them gain a competitive edge in their industry.
Sitting still and not doing the same means losing a competitive edge and, ultimately, losing market share to other companies over time. This means that OEMs have to be constantly developing new products, improving their existing ones and ensuring that their equipment is among the best, most resilient, and most advanced in the industry.
And data can help.
The product development testing conundrum
When it comes to the products that today’s modern OEMs are manufacturing, uptime is one of the most important factors. When industrial or manufacturing equipment goes down, time and productivity is wasted, and money is lost.
The facilities managers, building owners, and factory operators that OEMs call customers just want equipment that works the way it’s supposed to, when it’s supposed to.
When OEMs are developing and designing new products, they’ll undoubtedly create digital designs and models that they can simulate in virtual environments. Then, once those digital models are tested virtually for functionality and resiliency, they’ll create real versions of the product that they can test in real life.
And here is where the challenge lies.
If an OEM is making its equipment in Minnesota, there’s a really good chance that they’re only testing it in Minnesota. It wouldn’t be cost effective or financially responsible to take that product on a road trip of the United States or on a globe-trotting adventure, testing it in every possible environment and in every operation in which it will need to function.
Granted, that OEM will attempt to simulate other environments and use cases, but simulation can only prove and illustrate so much. Real world data, on-location and in real life situations is always more accurate and preferred.
There needs to be a better way to determine how different products and parts operate in disparate environments and disparate use cases during the product development process, so that the OEM can work to optimize the final product to function perfectly and with longevity in any situation.
Winning the resiliency game
Luckily for OEMs, they already have a way to see how different parts and products hold up in disparate environments – because they most likely have existing products in the field.
If an OEM in Minnesota has sold equipment to a user in Florida, they can see how well the different parts and materials in that product have held up in a much more humid and far warmer environment than their own. If they have products in use by different kinds of facilities and operations across the entire country – or even around the world – they effectively have a window into how their parts and materials hold up and function in practically any environment or use case.
That knowledge can then be applied to the new products that are in the product development process. By analyzing how materials, parts and other aspects of existing products perform in various environments and for various uses in the field, insights can be gained and applied to ensure that future generations of products are developed and engineered to be even more resilient and durable over time.
But how do the OEMs get access to that data? The answer lies in the cloud.
Cloud + data analytics = intelligent product development
Today’s facilities managers, building owners and factory operators have embraced the cloud to get a “single pane of glass” view into the status of their equipment. But the OEMs that have made the equipment haven’t done the same. The equipment is out there generating data, but that data has been left to die on the vine.
By cloud-enabling their equipment, OEMs can effectively harvest that data. Once the data is harvested from their equipment in the field, it can be analyzed and valuable insights can be gained from it. Those insights can be used for maintenance and diagnostics – as my associates have detailed in previous posts – or they can be used in product development to make a more durable, resilient product.
By harvesting data and then working to analyze it against other available data sets, OEMs can gain valuable insights that can be used to tweak and improve their products over time. Cloud-enabled equipment can report back usage statistics, unit temperature, operating environment data and other useful data.
By intelligently cross-analyzing these disparate data sets, the OEM can not only know about how their equipment operates when it’s first installed – or in a specific environment – they can begin to predict how that piece of equipment – in that environment – will perform into the future. This knowledge can be applied to make a more resilient piece of equipment. It can also be used to more proactively service and maintain existing equipment in the field so that downtime can be avoided.
The data is out there. It exists. OEMs just need to take that next, logical step to cloud-enable their products and harvest their own data. What it can do in product development could become a huge advantage in a crowded and competitive marketplace.