Accelerating product development: The tools you need now PART I
To
speed innovation and fend off disruption, R&D organizations at incumbent
companies can borrow the tools and techniques that digital natives use to get
ahead.
Between rising customer expectations and unpredictable moves by digital attackers,
R&D organizations at incumbent companies are under intense pressure.
They’re being asked not only to push out innovative products and services—which
is key to ramping up organic growth—but also to support
the formation of digital business models that compete in new markets. Yet many R&D
teams, particularly at companies that make industrial products, find themselves hampered by longstanding aspects of their approach, such as rigidly sequenced
processes, strict divisions of responsibility among functions like engineering
and marketing, or a narrow focus on internal innovation.
Some
product-development teams have begun to overhaul the way they work as part of
wider digital transformations at their companies. Those transformations can take a long time, though, as companies modernize their IT architectures,
adopt new technologies, reorganize people, and learn agile ways of working.
Since digital rivals aren’t waiting, product developers at incumbent companies need
innovation accelerators that they can put to use almost immediately. But with a
wide range of technologies and methods to choose from, where should they start?
In our experience
helping incumbents update their R&D practices, four solutions stand out for
their substantial benefits, as well as for their ease of integration with
existing activities. With so-called digital twins of in-use products, R&D
organizations can make sense of product data across the entire life cycle, thereby reaching new insights
more quickly. Once incumbents identify promising concepts, they can shorten the
product-development cycle by staging virtual reality (VR) hackathons. Some will
need a jolt of inspiration to speed up the R&D process. In that case, they
can try holding “pitch nights” to collect and sift through ideas from outside
the company, or setting up in-house design studios, or “innovation garages,” to
stimulate internal collaboration. Here, we explain how established companies
are using these approaches, either singly or in various combinations, to
develop winning products rapidly against threats posed by digital challengers.
Using full life-cycle data to drive innovation in real
time: Digital twins
To track customer
experiences and product performance closely, many digital natives have
developed sophisticated mechanisms for gathering data about items they have sold. These
companies then analyze these data and use their findings to guide the
development of new products, as well as software updates that correct flaws in
existing products or add features to them. The potential applications, however,
are moving beyond digital natives alone. Sensors embedded in mechanical
equipment, for instance, can reveal more than companies have ever known about
how well their machines work in the actual world. And all manner of digitally
equipped products, from smartphones to farm equipment, can now be monitored and
maintained using Internet-of-Things (IoT) applications.
Yet traditional
incumbents often encounter complications when it comes to gleaning and acting
on insights from the data generated by in-use products. Companies issue many
different versions of their products—for example, models tailored to
requirements that vary across geographies. The challenge that arises is keeping
track of all these versions. And when companies need to issue software updates
for their products, they find it difficult to first ensure that each update
will work on every version of a product.
Some incumbents have
started to address these limitations by employing “digital twins,” which are
virtual counterparts of physical products. By closely syncing existing product
information (such as the exact software and hardware configuration and
performance parameters) with real-world data on the usage and performance of an
actual product throughout its life cycle, companies can precisely monitor
problems and discover customers’ unmet needs. Such insights can point companies
toward breakthroughs in the design of new products, as well as significant
reductions in the time and expense associated with such activities as
performing maintenance, recalling products, complying with regulatory
requirements, and retooling manufacturing processes. And before incumbents push
out software patches remotely, they can test fixes and new functions on digital
twins.
One automotive OEM
struggled to provide effective maintenance services as the variety, complexity,
and geographic footprint of its product lineup increased. Yet it also knew that
the data emitted by its products would say a lot about how they perform and
what support they require. The company chose to build a new, more flexible data
architecture that would pour live product data into an array of digital twins.
Based on what the company learned from the digital twins, it identified a range
of services to boost customer satisfaction and, ultimately, sales. These
included remotely delivered software updates and digital tools for customer
engagement. By sending new software out “over the air,” for example, the
company was able to replace the 500 or so different versions of a single
model’s core operating system with one new version—a shift that greatly
streamlined the development of subsequent updates. All told, the company thinks
that these improvements could increase its earnings before interest and taxes
by up to five percentage points.
Shortening the concept-to-product time frame: Hacking in
virtual reality
Emerging evidence
suggests that in the digital economy, which favors first movers and fast followers, issuing a well-developed product too late is more
costly than being first to market with a good product that still has some rough
edges. The latter approach borrows from the hacking methods of software
developers, who release beta versions of new products to get early reactions
from customers, define customers’ preferences through A/B testing, and then
deliver on their feedback with changes made in brief, frequent cycles. As long
as companies are quick to turn around each new version of a product, various
styles of hacking can benefit incumbents, not just those that sell software and
services.
Visualization
technologies like VR, augmented reality (AR), and 3-D printing can bring still
greater improvements in the rate and flexibility of R&D efforts. Whereas
designers might spend five or six weeks assembling a physical prototype, they
can build a VR prototype in a matter of days. With the right tools in place,
cross-functional teams can alter those prototypes even more quickly and
estimate in real time the cost implications of potential design improvements.
In our experience, the effective use of VR can reduce R&D costs and time to
market significantly—as much as 10 to 15 percent for each measure—while achieving
gains in product performance.
VR technology helped
one advanced-equipment manufacturer to make a breakthrough with its
next-generation model of a large stationary electronic device. Competitors had
been nibbling away at the company’s market share for years because their
versions of the device were less expensive and easier to install. But the
company couldn’t figure out what made its competitors’ designs superior.
Gathering information from a range of sources, the company created 3-D models
of competitors’ products. Its engineers could then closely examine those models
from every angle with VR headsets. Their research convinced the R&D team to
revisit certain assumptions about how its next model of the device should be
designed.
With those outdated
assumptions in mind, the company held a series of hackathons to develop the new
version, bringing people from various departments together in the same room,
either physically or virtually, to push a VR prototype through multiple cycles
of review and adjustment. It placed its own prototype and competing models in
the VR environment to make direct comparisons that would have been impractical
in the physical world. The cross-functional team then adjusted the prototype on
the fly as improvements were suggested. Not only did the VR technology speed up
the design process, but inviting all the relevant departments to hack the
virtual prototype at the same time made it possible to solve problems quickly
and build new capabilities, such as working in an agile manner.
CONTINUES IN PART II
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