The research firm has identified five areas across the enterprise in need of digital transformation, including running the corporation, servicing, selling, making and delivering, innovating and developing products and services.
"Advanced industries have been slower to digitize than many other sectors," says Venkat Atluri, co-author of the study and senior partner at McKinsey. "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."
When companies adopt a piecemeal approach to digital transformation, it's more likely they will fail, says Atluri.
"Many companies are adopting artificial intelligence, machine learning, cloud services, and a host of other technologies on a case-by-case basis, instead of selecting technologies to serve their strategy or meet specific business goals," he says. "Success depends on a holistic approach to transformation. That means defining your aspirations, linking them to sources of business value, working out which technologies will help achieve them, and then doubling down."
The explosion in data, connectivity, and cheap processing power and storage means that industrial companies should be looking to technology-enabled transformations for growth. Few do. Many get stuck in what the McKinsey authors call "pilot purgatory" and never advance to the next stage.
"When McKinsey surveyed executives developing IoT solutions in 2017, more than half had been running customer pilots for one to two years, and more than a quarter for even longer," Atluri says.
The automotive sector – car companies, Tier 1 suppliers and auto dealers – represents the biggest missed opportunity. The McKinsey authors see opportunities to increase revenue by $367 billion and expand margins by $259 billion.
Other industries are not squeezing the most out of the digital transformation include mobility, aerospace, and defense as well as broader industrials such as component suppliers, equipment manufacturers, engineering and service providers, electrical, power and test equipment, food processing and handling, and industrial automation.
How to start with digital transformation
Alturi suggests using 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. He calls this design thinking.
- Companies should also find partners to share data and insights and create mutually shared value, or what McKinsey calls an ecosystem
- 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
- Take a step back and consider what you want to achieve. "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," Alturi says. "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."
- Transform; don’t settle for incremental gains. 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.
- For those charged with running the corporation, look at establishing "data lakes to pool data across multiple functions" and automate reporting and other manual tasks in finance and Human Resources.
- Sales organizations need to consider adopting e-commerce channels and digital tools to enhance the productivity of the sales force.
- The aftermarket service process is ripe for disruption. As tools such as predictive maintenance mature, manufacturers can use them to create stronger links with end customers, form a clearer view of how these customers use their products (and how the products perform), and capture increasing revenues from services. Look at field-force management, scheduling and parts management for opportunities.
- Advances in automation, machine learning and robotics present companies a chance to be more cost-efficient, flexible and responsive to customer needs. The new era of automated production and data exchange opens a broad range of use cases that can cut cost, increase yield and support new manufacturing methods.
- Successful innovation relies not only on sound data and technology but on a deep understanding of how to use them to tap into new sources of value. For industrial companies, this begins with an intimate knowledge of end users’ needs and pain points.