The trillion-dollar opportunity for the industrial sector: How to
extract full value from technology PART II
Running the corporation
The many industrial
companies that have pursued growth via acquisition end up running their
business on multiple enterprise resource-planning (ERP) and legacy systems. Not
surprisingly, across the advanced industrial sector, the median spend on
general and administrative expenses accounts for 4 to 8 percent of revenue.
Automating manual processes via robotic process automation (RPA) can
significantly reduce these costs. Other measures to cut costs and improve cash
flow include building data lakes to centralize data sets across ERPs,
automating financial reporting and invoice generation, and using advanced analytics
to improve cash management.
Pulling it all together
To maximize value
creation in a tech-enabled transformation, smart companies start by
establishing a sound set of use cases across all five of these business
elements. That’s a critical step in setting aspirations, capturing value, and
tracking value capture over time. Whether a company focuses on two or three of
the business elements or looks to create value from all five through tech
enablement, like the example in Exhibit 4, will depend on the nature of its
business and its position in the value chain. But to avoid leaving value on the
table, leaders would be well-advised to examine all the elements in detail
before deciding on the best approach.
Exhibit 4 SEE IN ORIGINAL ARTICLE
The other imperative in
starting out on a transformation journey is to check that your organization has
all the supporting elements it needs, as described below.
Ensuring
the right enablers are in place
In considering the
capabilities, structures, and practices that industrial companies need for a
successful transformation, we find it helpful to define three sets of
prerequisites that executives can use as a checklist in prioritizing
initiatives and allocating resources.
Foundation: Data strategy, cybersecurity, cloud infrastructure,
and analytics
A comprehensive data strategy involves
identifying the data sets you need to drive insights across your priority use
cases, understanding the sources of those data sets, and forming partnerships
to access those that you need but don’t own. For instance, a manufacturer
seeking to reduce downtime for its mining equipment will need to combine its
own data with a host of maintenance and usage data from the mining operators
that use the equipment. Establishing which data sets you need and then building
productive partnerships with OEMs and component manufacturers to access them
will be critical in maximizing value capture.
As companies connect
enormous numbers of devices and develop ever-more-complex data
structures, cybersecurity becomes
increasingly important. Once, cyberrisk was mainly confined to IT functions,
but as businesses hook up their production systems to the Internet, operating
technology comes under threat as well.3 Seventy-five
percent of the experts who took part in a recent McKinsey survey said that IoT
security was important or very important, yet only 16 percent felt their
organization was well-prepared. Building resilience will involve prioritizing
assets and risks, improving controls and processes, and establishing effective
governance.
Establishing the
right cloud infrastructure involves
creating flexible environments and sound application programming interfaces.
Companies also need to think through which data should be in the cloud and
which on the “edge”—on the devices themselves. Such decisions will largely
depend on how much real-time processing is required. For instance, autonomous
driving lends itself to an edge architecture, whereas analyzing consumption
trends by aggregating data from connected appliances can be handled in the
cloud.
Equipping your
organization with data analytics capabilities
to drive insights will be critical in capturing value. Whether you build the
capabilities in house or outsource them will depend on your circumstances and
needs. Often it makes sense to do both in the early stages, building
capabilities over the long term while using outsourcing to accelerate
short-term impact. Regardless of which route you take, data analytics and
insight generation must be linked to actions that you can take to generate
impact. For instance, if you are introducing analytics-driven dynamic deal
scoring to improve margins, your reps will need a quoting tool that shows them
the recommended prices, and leaders will need a performance-management system
that tracks improvements across the whole sales team over time.
Organization: Agile operating model and culture
The ability to respond
quickly to changes in the business environment relies on an agile operating model with small,
flexible teams and clear processes that allow timely decision making on issues
relating to governance, funding mechanisms, resource allocation, and so on.
Old-style yearlong development cycles must give way to rapid iterations in
which teams repeatedly test and refine concepts and products with customers.
Such an approach
requires corresponding changes in an organization’s culture. Successful companies take
great care to foster a mind-set that embraces change, is comfortable taking
risks, and views failure as a springboard for learning.
Accelerators: Design thinking and ecosystem
Using customer insights
to rapidly innovate on products, services, and offers calls for new
capabilities and tight linkages between a company’s sales channel and its
product organization. Design
thinking uses closed-loop processes to generate customer insights,
translate them into product features and services, rapidly deploy these
elements with the customer, test the impact, and repeat as necessary until the
desired impact is achieved.
Building an ecosystem is the final enabler
and involves establishing a set of technology and go-to-market partnerships.
The complexity of a tech-enabled transformation requires partners to share
data, insights, and the value created in a mutually satisfactory and sustainable
manner.
Getting started
·
Though tech-enabled
transformations in the industrial sector are still in the early stages,
companies have no time to lose. An early mover with the right strategy could
not only grow profitably across the board, but also leapfrog over competitors
and capture disproportionate value by gaining market share from peers or being
the first to respond to radical shifts in customer behavior.
·
Every company’s
approach to transformation will reflect its individual starting point and
business priorities, but any leader would do well to follow a few basic steps:
o
Analyze
every aspect of the business. When embarking on a tech-enabled transformation,
the best way to start is by taking a step back and considering exactly what you
want to achieve. Obvious though that might sound, it’s not so easy to act on.
Some companies are so overwhelmed by, say, the promise of the Internet of
Things that they jump straight into working out how to introduce IoT
applications into their products and operations. Instead, evaluate your whole
business to see where technology could unlock the greatest value. If you are an
industrial distributor, for instance, you may be able to improve your margins
much faster by adopting analytics-based pricing or digitizing your selling
process than by creating IoT-enabled services. Implementing and scaling basic
technologies is a quick way to learn and capture value before venturing into
more sophisticated territory such as remote diagnostics and maintenance.
o
Reimagine
your business model and aspirations. Don’t use technology to make your current model
marginally more efficient. Set a bold aspiration to ensure the changes you make
don’t just reinforce the status quo. Define metrics and operational performance
indicators to track improvement, and ensure you have leadership support. Treat
your program as a transformation, not an incremental initiative.
o
Understand
how new technologies affect working processes. To succeed, new technologies
need to operate in conjunction with legacy systems and existing workflows.
Consider an OEM adopting IoT-enabled solutions to offer predictive maintenance.
When a client’s system detects an equipment problem, it automatically notifies
the OEM to send a service rep to carry out unscheduled repairs. But for this to
work, the OEM has to integrate these notifications into its service-dispatch
processes so that reps are sent out promptly. Closing the loop on workflows in
this way is a critical step in capturing value.
o
Understand
where you are and build your transformation roadmap. Too often, companies deploy
solutions without first taking care to understand their current situation. Set
a baseline and be realistic about your starting point and digital
maturity—which will partly determine how much value you can expect to capture.
Then, work out where the value lies, assess your capabilities, and build a
roadmap that prioritizes and sequences the key elements in your transformation.
Develop a clear view of the value-chain elements your business touches, your competitive
environment, and the ways technology could disrupt it: for instance, through
customer-service apps. Think in terms of three-to-five-year horizons to ensure
you keep pace with the evolving technology and business landscapes.
Though the industrial sector
has been slower to digitize than many other sectors, advanced technologies now
allow companies to reshape all their activities from product development to
sales and servicing. Our experience indicates that taking a bold, strategy-led
approach and identifying opportunities systematically across the entire
business is the best route to a successful outcome.
By Venkat Atluri, Saloni Sahni, and Satya Rao
https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/the-trillion-dollar-opportunity-for-the-industrial-sector
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