Managing Director & Senior Partner
Related Expertise: Innovation Strategy and Delivery, Data and Analytics, Digital HR
This article is a chapter from the BCG report, The Most Innovative Companies 2018: Innovators Go All In On Digital.
Digital technologies change innovation strategy by expanding the horizon of the possible in terms of new products, services, business models, and the internal processes that enable the new offerings. This shift both raises the stakes and accelerates the pace of the innovation game.
Business leaders today need to think differently about innovation strategy. They should take into account the following five questions as they rethink—if not revamp—their innovation strategies for the digital age. (This article primarily examines digital’s impact on innovation strategy; for a related discussion on how to put these strategies into action, see the companion article “A Digital Overhaul for Innovation Operations.”)
Just about anything—and at lightning speed. Companies can develop and test new products—for example, through digitally enabled simulations, 3D printed prototypes, or minimally viable products released in the actual marketplace—much faster and more cheaply than ever before. Plenty of digital disruptors began with a beta test, among them Airbnb, Spotify, and Zappos.
At the same time, besides adapting to a faster tempo of competition, innovation strategists need to engage on a broader playing field. For example, competitive advantage increasingly is driven less by products and more by the digitally enabled services that surround them. From today’s predictive maintenance offerings for industrial goods to tomorrow’s Internet of Things (IoT), strategists need to explore and master new innovation domains. Already, connected cars have drawn automakers into the software business, and autonomous vehicles are bringing tech companies into transportation and mobility. As more advanced technologies, such as artificial intelligence, enter the mainstream, the stakes keep climbing.
This boundary blurring also means that innovators need to expand their competitive set as digital-native companies seek to bring their own advantaged capabilities to more traditional markets. If you’re a traditional insurer or credit rating agency, for example, it’s worth considering whether Google or Facebook could use their data and machine-learning expertise to create new approaches to underwriting and assessing credit risk. Less speculatively, if you’re a traditional grocer, it’s important to determine how to counter the innovations that Amazon’s acquisition of Whole Foods will inevitably unleash.
Traditional companies are increasingly trying to innovate more expansively and digitally. In financial services, for example, it’s hard to find a company that is not investing heavily in digital innovations. Global insurer AXA put €100 million into its venture lab, Kamet, with the goal of developing disruptive new insurance tech businesses. Citibank set up Citi Ventures to accelerate work on disruptive products that are based on such technologies as the IoT and blockchain. Allianz has created a digital lab to work with startups in such areas as data analytics, mobile, and social media. And Santander Group formed InnoVentures, a $100 million fund to make strategic investments in fintech products and services.
Data (including mobile data) and software are essential to the identification and delivery of many digital innovations. At digital retailer Stitch Fix for example, data-driven algorithms perform hundreds of functions, including matching products to clients, pairing stylists with clients, calculating how happy customers are with the service, and figuring out how much and what kind of inventory the company should buy.
Data and software enable idea generation and exploration. When combined with human intelligence and creativity, natural language processing and network analytics make it possible to gain valuable insights about customer trends and competitor moves from information stored in huge, unstructured databases. Companies can explore patterns in patenting, venture capital funding, scientific literature, and customer data. They can also develop new value propositions, such as personalized offers, and new capabilities for traditional products, such as autonomous vehicles.
The wealth of data served up by mobile devices—much of it location-specific—is another powerful fuel for R&D and product and service development. Starbucks has built a personalization program largely around mobile data. Insurance companies are using mobile data to develop new products and services for transportation.
Software adds value to physical products. But software development often occurs in much faster cycles than hardware innovation, creating management challenges for innovation programs. Digital natives have used speed as an advantage, establishing a new product or service (often exclusively online), gaining popularity through digital channels, and then scaling up fast. The need to accelerate innovation and shorten R&D and go-to-market cycles has big implications for how companies manage innovation programs and think about innovation strategy.
Digital innovation generates a host of questions. What new strategic capabilities must be developed or acquired? How can a company create a competitive advantage in data and in gaining insight from that data at an accelerated pace? Is it possible to go it alone, or are partners required?
Technical skills are an obvious need, but they are both technology-specific and in short supply. Every company looking to take advantage of data analytics, not to mention artificial intelligence, needs data scientists. However, data scientists are not experts in mobile devices or mobile engagement. Neither are they software engineers. Furthermore, industry knowledge is critical: consumer goods companies need people with e-commerce experience, and industrial manufacturers need people with expertise in Industry 4.0 and the IoT. Complicating matters further is the need to train technical talent in what makes the business tick and business talent in what technology and the techies can help them achieve. And then there is the issue of digitizing legacy IT and the supply chain so they can support digital processes at digital speeds.
Even the largest organizations find that they can’t do everything themselves; they need partnerships and alliances, which open up all kinds of issues related to their place in the innovation system, ownership of intellectual property (IP), and the like. BCG research shows that the number of digital joint ventures has increased by almost 60% in the past four years. Some traditional companies—such as auto OEMs, which have long collaborated closely with multiple suppliers—may be better positioned to adapt to this new paradigm than others. But even for those companies with prior collaboration experience, differences between digital and traditional companies in approaches and cultures, as well as in ways of working, may be challenging to navigate.
The biggest risk, of course, is finding that your company’s product or technology no longer has a market; think about what happened to Kodak and Wang Laboratories, for example. The more immediate challenge is simply to avoid being left behind by those that invested sooner or more heavily in digital innovation. Our research shows that strong innovators assign much greater importance than weak innovators to big data, speed of technology adoption, mobile products, digital design, and technology platforms generally. There are even bigger gaps in how aggressively companies are pursuing these innovation avenues. (See the companion article “Innovation in 2018.”)
For traditional companies seeking to embrace digital, IP is a critical potential obstacle. Companies that want to embrace the IoT, for instance, must confront the fact that four of the top ten IoT patent holders are licensing companies whose business model is built on collecting rent from companies that need their IP. The connected car provides another example: most dashboard patents are held by Microsoft, Apple, and Google—not by auto OEMs.
All of the foregoing has major implications for how companies approach innovation, from their allocation of resources to their measures of success. Companies and industries differ, of course, depending on individual circumstance—their starting point and the extent of disruption. Nonetheless, we see some common themes among those that are moving most aggressively to digitize their innovation programs. These leaders are opening a divide with those that are slower to adopt digital approaches, and this gap will only expand as more advanced technologies, such as artificial intelligence and blockchain, enter the mainstream. Laggards will be increasingly challenged to catch up.
Leaders dedicate resources. Leaders recognize the importance of digital, and they are shifting their investment allocations accordingly. Data analytics, rapid adoption, mobile products, and digital design are all rising in importance, and the number of companies pursuing them is also increasing, according to our 2017 innovation survey. Leaders are both digitizing internal processes and funding enablers, such as incubators and accelerators. They are also digitizing how they monitor and manage IP.
They invest in speed. Leaders are revamping their innovation engines, looking to shorten cycles, move faster, and cut the time to market. They test more ideas earlier in development and use digital techniques for simulation and prototyping. They iterate rapidly until they find a good product-market fit. Development often focuses on producing a minimally viable product, rather than a fully finished version, that companies can launch, collect data on, adapt, and relaunch—all in an iterative, agile style. Product launches increasingly take place online using e-commerce or e-customer platforms.
They take smart risks. Leaders are willing to make big bets that have a high-risk, high-reward profile, in part because they understand that there is greater risk in doing nothing. Tesla has accelerated to the top of the auto industry with big bets on technology, including batteries and autonomous driving. The company is not afraid to fail and to do so publicly. But it has also maintained its reputation, market capitalization, and willingness to push boundaries. Leading companies focus on what they are good at, too. Once they’ve established a viable product or service, they expand to other ideas. Amazon, for instance, built an innovation behemoth on one simple idea: selling books online. The cornerstone of Nike’s success was a better running shoe.
Many larger, more established companies are averse to taking risks and reluctant to try out new approaches, technologies, and products. Indeed, our 2017 innovation survey found that the top two obstacles to generating a return on investment in innovation and product development were a risk-averse culture and overlong development times.
They invest in data. Leaders use their own data combined with data from industry sources and third parties (such as partner companies and social media) at all stages of the innovation process—from idea generation to testing. They mine data for new ideas, and they connect with customers, suppliers, and partners using digital platforms to incorporate real-time feedback as they iterate new-product development. They use data throughout the innovation process. (See Exhibit 1.) Many use data to extend the capabilities of their products and services. For example, Schneider Electric, Deere & Company, and Schindler Group (a manufacturer of elevators, escalators, and moving walkways) all employ many types of new information-based services, analytics, and insights by adding internet-connected devices—such as sensors, microprocessors, radios, and GPS locators—to their products. In some cases, digital data has led to new disciplines, such as precision farming, and new forms of collaboration, such as communities of customers who develop answers to common questions.
They build advantaged capabilities. Leaders recognize the need to build and expand their skills and capabilities at many levels. They invest in acquiring and developing talent: technical, business, and cross-disciplinary. They establish cross-functional teams and seek to work in more agile ways. (See “Taking Agile Way Beyond Software” BCG article, July 2017.) And, as we explored in an earlier report, they are not afraid to incorporate external innovations through a variety of mechanisms, including acquisitions, partnerships, joint ventures, and licensing. (See The Most Innovative Companies 2016: Getting Past “Not Invented Here,” BCG report, January 2017.) As the technical basis of so many innovations increases, leaders access new technologies and capabilities from outside the company and use a variety of models for doing so, including corporate venture capital, accelerators and incubators, and innovation labs. They also overcome the not-invented-here mentality when bringing a new idea, capability, or model into their organizations.
A clear target product profile was the most important factor in creating value from innovation, R&D, and product development efforts in our 2017 innovation survey. Fully 85% of respondents from strong innovators said that their company has a clear target product profile, compared with only 46% from weak innovators. Strong innovators also have clear portfolio management and digitized processes. (See Exhibit 2.)
Digital technologies present a trifecta of innovation challenges: they blur boundaries, raise the stakes, and up the speed at which new competitors with new ideas can seize sales and share. Traditional companies, no matter how large, can’t afford to pursue innovation, R&D, and product development in traditional ways. To do so cedes competitive advantage to the disruptors. Companies need to determine their own digital strategies and start playing the innovation game by today’s rules.