Summary: The Internet of Things (IoT) has changed product development for the better. By closing the feedback loop and providing real-time data, manufacturers can now embrace true customer-centricity.
That’s why we’re going to look at what IoT technology actually is, how it’s transforming linear product development, and what IoT product development would look like.
Here we go!
What is the Internet of Things?
Let’s just get a few things clear.
Officially, IoT is defined by IBM as:
the concept of connecting any device (so long as it has an on/off switch) to the Internet and to other connected devices. The IoT is a giant network of connected things and people – all of which collect and share data about the way they are used and about the environment around them.
In reality, IoT is a bit of a catch-all for any device that’s “smart” enabled, from toasters to cars, and it quickly becomes bewildering.
For us, the key parts of IoT are:
- Devices have sensors built into in them that communicate back a broader system (e.g. the internet).
- The data generated is used by other systems and people to make decisions…
- … And that data is available both in real-time and in the aggregate.
Now that we’re on the same page, let’s look at how product development works today.
Product development to date
Traditional product development has been generally linear.
That is, a product moves through different product development stages from conception from the product marketing/product management team through to design, engineering, manufacturing, and delivery.
Each of these stages is punctuated by handoffs between teams, and each total product development process will usually finish at product delivery.
Linear product development has two key characteristics:
- Product development is discrete: Products move from team to team and there’s little to no bidirectional data flow. What’s more, there’s limited data integration between products and product iterations.
- Information only moves down the value chain. Data flows internally within companies, with little to no information being gathered from the customer. Essentially, once the product launches, that’s it.
The problem with linear lifespans
The one-way flow of data leaves companies with little information on how products perform after they’re purchased.
Yes, companies can (and do!) secure customer reviews, either when products are released or when a new product is being developed.
But customer reviews only get you so far:
They’re few and far between
With only a few reviews, it can be difficult to extract meaningful insight from that data. Caution must be used when you’re painting a picture of product performance.
What people say and what people do are very different
Someone might give you a scathing review based on a function of the product not working, but that doesn’t actually reflect their behavior, purchasing or otherwise.
That is, even if someone is unhappy, they might not be unhappy enough to pay for a better product. Ryanair is a great example of this. Reviews? Terrible. But people love paying $20 to get from A to B, as evidenced by their rising stock price and host of imitators.
Reviews are very subjective
Reviews usually represent two extremes of customer experience: highly satisfied or highly dissatisfied. They’re often not reflective of the experience of the silent majority in the middle. What’s more, it’s not necessarily true that the concerns of your reviewers are the same as the concerns of your users in general.
Why customer-centricity matters
As we mentioned, traditional product development has a one-way flow of information. The problem with this is that customer feedback isn’t incorporated as readily into additional iterations of the product or into new products as they’re developed.
And this isn’t just lip service for customers: According to a 2015 IDC report, customer satisfaction rates increase by 90% when manufacturers are able to understand the product functions and quality customers want.
Customer satisfaction increased 90% when manufacturers understood the product quality and requirements their customers desired.
And one of the best ways to secure customer input into manufacturing processes? IoT.
IoT product development
The product development process shouldn’t be linear. It should be circular.
But the persistent challenge has been to gather and feed customer input back into processes further up the product development chain.
The answer is IoT.
IoT product development allows data on how products are used to be fed back to manufacturers in real time, allowing for iterative correction and rapid design improvement based on that data.
And this feedback can have a serious impact on the business.
Manufacturers get a better idea of how people use their products
IoT product development allows organizations to understand how customers actually use their product rather than how they say they use a product. It means that manufacturers can be more aware of maintenance challenges and product flaws earlier, and design out product problems.
For instance, say you’re making a car, and you’ve created brake pads that are designed to be replaced every 65,000km. You know that people drive about 20,000km every year, so you can reasonably expect the brake pads to last 3-5 years.
But what if your IoT sensors within the car are telling you that the brake pads are wearing out after only two years? This might be a product problem, or people just brake more than you thought. Maybe your car is mainly purchased by people who live in a city. Who knows?
The point is, it’s very unlikely someone would say this in a customer review:
“Great car, but the brake pads wore out after two years when according to the product spec, they should have lasted 3-5 years.”
IoT product development can provide that unspoken data and gives companies the opportunity to fix the product before it’s a problem, and take that learning and adjust for the next iteration. In this case, putting better brake pads on the car.
In short, companies are making decisions — design or otherwise — based on how the product is actually used, rather than how it’s intended or spec’d.
Manufacturers can reduce inventory cost
IoT product development data reveals patterns in product usage that allows more accurate demand forecasting, including when products are most likely to break down.
This information lets manufacturers predict when customers will need to replace products and manage inventory accordingly.
Drive profitability from aftermarket services
McKinsey reported in 2017 that the margin on aftermarket services was 25% for industrial OEMs, compared to 10% for new equipment sales.
The margin for aftermarket services [is] 25 percent, compared to 10 percent for new equipment.
By knowing exactly at what point products begin to deteriorate, businesses can strategically offer aftermarket services when they are needed most.
IoT product development allows companies to drive revenue through extended warranties, part replacement, and preventive maintenance — all completed at a lower cost because companies know with more warning what’s going to break and when.
IoT & cloud PLM
The business advantages of IoT are great, but how do you actually use IoT data to make them a reality?
For some, this is going to be an IoT platform.
But for most SMEs, these specialized software solutions are priced out of reach.
Which is where cloud PLM comes in.
A direct ROI of PLM is its potential as a tool in IoT scenarios.
Let’s unpack this a little.
IoT product development is all about data — taking product use data and connecting it with the product development lifecycle, feeding every stage of product development.
… Which fundamentally is what a cloud PLM does.
Cloud PLM connects the product development lifecycle with product data rather than product feedback data. And with cloud PLM openly embracing best of breed ideas with APIs and flexible data structures, it just means it’s the perfect tool to leverage IoT data without buying a whole new platform.
Cloud PLM allows data to be used effectively by organizations by making said data accessible throughout the value chain.
For instance, the insights IoT data reveals about product performance helps:
- Product designers: they can use IoT data about product performance to refine product design and optimize new product initiatives.
- Procurement and supplier management: they gain insights into how their supplier decisions unfolded for the end-user.
- Sales and marketing teams: they can use product feedback data to identify pain points and feed further product development.
The product lifecycle is already shifting from a linear chain to an interconnected network.
IoT product development is just the next node in the network.
It connects product usage data in real time back to product teams to iterate and improve faster and more effectively.
To fully realize this potential though, that data has to go somewhere. There has to be someone to catch what sensors are tossing.
While a dedicated IoT product development platform is great, lots of SMEs don’t have the capacity to support that additional software overhead.
That’s where cloud PLM comes in. According to Forrester, cloud PLM can fulfill duel functions for manufacturing organizations:
- Connect the product development network from design ideation to the shop floor.
- Pull IoT product use data back into the product development network.
And that’s where we think cloud PLM and IoT product development are headed.
We see it as two sides of the same coin — product data on one side, and product usage data on the other.
Together, they bring product development full circle.
Image credit: Octavian Rosca via Unsplash