Tech-enabled
disruption of products
and services: The new
battleground for
industrial companies
PART II
Optimizing R&D processes with tech enablement
With an estimated $8 billion to $25
billion in incremental industry revenue growth, this is the smallest
value-creation opportunity of the three. But it is still important, given that
traditional approaches to R&D efficiency—peer benchmarks, lean engineering,
trial and error—are producing diminishing returns and ceasing to confer
competitive advantage. The fundamentals of tech-enabled R&D efficiency are
a shift to agile iterative product-development cycles and the rapid deployment
of digital- and analytics-based productivity techniques. Consider a typical
company where engineers use ten or more systems in a typical day’s work,
ranging from timesheets, emails, and project plans to bills of materials and
suppliers’ systems. By integrating data from all these disparate systems into a
common structure, the company can use machine-learning algorithms to track
metrics dynamically and extract powerful insights that provide a fact-based,
granular guide to sources
of value.
of value.
One aerospace and defense company applied
advanced analytics to identify productivity drivers and metrics in its software
engineering. It began by creating a data lake that combined data from a dozen
or so sources, including the enterprise value-management system, software code
tracking, timesheets, and Microsoft Exchange. Then it ran multivariate
algorithms to identify factors that correlated to productivity metrics. It
found, for instance, that replacing late-stage software testing with
early-stage testing using automated scripting would improve productivity by 5
percent.
Finally, the company created a business
case and action plan to address target initiatives. This entire process was
completed in just 16 weeks, thanks to a sprint-based approach that combined
traditional engineering practices with advanced analytics. The company found
opportunities to reduce software defects by 35 to 50 percent and increase
engineering capacity by 20 percent.
How to
capture the value
For all their promise, few industrial
Internet of Things (IoT) products have reached full maturity and scale as yet.
In our experience, one of the main barriers to adoption is a lack of
understanding of how to capture the value of technology. Developing new
offerings is only half the battle; companies must also invest in an effective go-to-market
approach. This involves two elements:
Knowing where the value is created
Those industrial companies that have
succeeded in scaling connected products or data-enabled services understand
where the value is created (by direct customers, end users, or ecosystem
partners, for instance) and how it is created (through lower transaction costs,
improved safety, fewer defects, or some other benefit). This knowledge is
fundamental to developing appropriate business, pricing, and revenue models,
quantifying value creation, and understanding how much value accrues to each
party. For many connected products or data-enabled services, the end user is
the primary beneficiary of the value created. Component and subsystem suppliers
will need to find a path to monetization that reaches the end user, perhaps via
an ecosystem approach or partnership with OEMs.
In upstream oil and gas, for example, the
value created by reducing downtime at a fracking site or oil rig is captured by
drilling contractors but delivered by a combination of players. Data ownership
is fragmented: the drilling contractors control the data from the large
equipment they manage; manufacturers of, say, frac blenders own the algorithms
and data that generate insights into the equipment and how it works; and
component manufacturers, in turn, own performance data on individual products
such as pumps. In this environment, creating value will entail forming
partnerships with multiple manufacturers and designing a model that enables
value to be fairly shared among the partners.
Establishing the right monetization model
Industrial companies can monetize their
products directly or indirectly. Direct options include bundling products,
launching add-on services, and delivering an offering as a service. Indirect routes
include capturing new market share, developing preferred-supplier status with
OEMs, and so on. To maximize value capture, companies need to select a
monetization model that is appropriate to their position in the value chain and
the criticality of the value at stake.
Take the example of an
agricultural-equipment manufacturer selling productivity services to farmers.
In general, measuring the improvement in crop yield or quality that can be
generated by data-enabled farming equipment is difficult, as it depends on
multiple variables over the course of the year. However, on occasions when
farmers need to harvest a crop within a short timeframe—as with sugar cane, for
example—they want their equipment running at maximum productivity, opening up
opportunities to create value by optimizing uptime or output. Meanwhile, a
component manufacturer in this value chain may find that its best monetization
strategy is to develop a preferred position with the OEM.
How to
get started
Most industrial companies are still at an
early stage in transforming their innovation and product development through
technology. Some hesitate to take the first steps, others are stuck in pilot
mode, and still others struggle to build a viable business case in the face of
traditional development cycles and limited monetization opportunities. But
delay could cost companies dearly: late adopters risk not only leaving value on
the table but also losing market share to nimbler competitors. A McKinsey
Global Institute survey found that being a first mover conferred an advantage
of about 7 percent in earnings before interest and taxes—more than double the
roughly 3 percent achieved by average responders.
So where do you start? We suggest five
steps:
·
First, listen to your
customers. They know what they want when they
see it, even though they may not be able to articulate it in advance. Invest
heavily in customer insights to identify pain points in the user experience,
and pressure-test your new offerings with customers to ascertain what they are
willing to pay for.
·
Second, place big bets. It’s fine to fail fast, but avoid spreading your
investment across too many ideas. Successful organizations prioritize a few big
bets that get the lion’s share of management attention. Having identified your
big bets, consider novel ways to organize around them. Some tech-enabled
industrial companies use a VC-like governance structure with a digital
unit reporting directly to a “digital board” comprising the CEO, CTO, and CFO.
Such a structure ensures that funding is based on reaching milestones, that
issues are resolved quickly, and that the core business stays focused on the
core.
·
Third, adopt agile
product development. Set up small, autonomous,
cross-functional teams that can get close to customers, fail fast, and pivot to
the next opportunity. Traditional product development cycles are a recipe for
failure, as they can’t keep up with advances in technology and data.
·
Fourth, build out your
ecosystem. Commercial as well as technological
partnerships are essential to moving fast and scaling effectively. Building and
maintaining a robust ecosystem of partners demands dedicated resources.
·
Fifth, establish the
right go-to-market capabilities. Selling
tech-enabled products is nothing like selling traditional hardware. It requires
knowledge of consultative selling, software bundling, and unfamiliar sales
cycles and solution architectures. Expecting your traditional sales channels to
convert customers quickly or bolting a digital sales group onto a traditional
organization could spell disaster. Instead, develop a clear customer
interaction model and overhaul your sales structure, processes, enablement
strategies, and incentives.
Tech-enabled innovation and product
development has the potential to deliver enormous and much-needed revenue
growth in the industrial sector. Companies that take a rigorous approach to
finding, quantifying, and capturing value—and then move quickly—can expect to
see the greatest impact
By Venkat Atluri, Jeremy Eaton, Mithun Kamat, Satya
Rao, and Saloni Sahni
https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/tech-enabled-disruption-of-products-and-services?cid=other-eml-alt-mip-mck-oth-1811&hlkid=618679184bf8401282d097408c405f04&hctky=1627601&hdpid=40950bab-bdef-4ff9-9eb4-9ea21456999b
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