Growth initiatives for today’s companies come in many forms. Some will partner with startup accelerators or other innovation ecosystems. Others may bank on a product to be so valuable to customers that it sells itself. Others may attempt to establish a foothold in China.
The latest insights from MIT Sloan Management Review help companies navigate these types of initiatives. Leaders likewise learn how to avoid being stymied by lackluster interest in artificial intelligence tools or preventable cybersecurity incidents.
3 questions for engaging with innovation ecosystems
Around the world, innovation ecosystems bring together entrepreneurs, investors, research institutions, and corporate and government sponsors to develop new ideas and fund new companies. Executives facing competitive pressure to innovate clearly benefit from engaging with these ecosystems, but they are unlikely to reap any benefits without a structured, focused approach to partnership.
MIT Sloan senior lecturer and professor the associate dean for innovation and inclusion, suggest that enterprises need a sound strategy for engaging with innovation ecosystems that answers three important questions: what, who, and how?
What do you want to acquire from and offer through your engagement? Are you looking for new hires — or are you hoping that membership in an innovation will reenergize internal corporate culture? As for what you can offer, remember that access to information and infrastructure is just as valuable as funding.
Who do you want to engage with: early-stage ventures, established corporations that have met development milestones, or late-stage startups with a viable product and market presence? The executive engaging with the innovation ecosystem, meanwhile, should be well-skilled at helping external entrepreneurs navigate internal processes.
How will you engage, and how will you ensure effective interactions through the engagement opportunities you provide? This approach depends largely on what a company needs and who it wants to connect with. Identifying the innovation ecosystem that best aligns with these priorities is likely to lead to successful engagements.
Why innovation in China is so different
Most enterprises are working to centralize innovation, particularly in places such as Silicon Valley. They’re also more likely to partner with universities and startups to develop new ideas than to seek input from internal business units, suppliers, or partners.
Innovation trends in China are almost exactly the opposite, according to research from MIT’s Neil C. Thompson and Wenjing Lyu, and colleagues. As a result, they conclude, companies hoping to capture market share in China will need to adopt a different model than what they have for the rest of the world.
Whether domestic or foreign, firms operating in China are twice as likely to view customers, competitors, or operational employees as a source of innovation. Here’s how the most successful companies stay on top of these market needs:
- Create online communities that let customers provide product recommendations and use machine learning to distribute information to the right employees. This has helped Xiaomi launch more than 100 smart consumer electronics.
- Look at competitors as potential collaborators, especially if they have a domestic presence. Daimler, which sells four times as many electric vehicles in China as the United States, has created a joint venture with Chinese firm Geely to produce a rebranded smart car.
- Learn from repair technicians and sales representatives who have firsthand knowledge about how customers use — or want to use — products. From this feedback, Haier developed a refrigerator with a built-in foldout table for students living in cramped quarters.
The 5 characteristics of product-led growth
Many of today’s software companies thrive on product-led growth. In this business model, a product with a low introductory price and easy-to-use features becomes so valuable to users that companies can grow rapidly with little need for customer support. Zoom is a clear example, with profits increasing from $7 million in 2018 to $1 billion in 2021 as the product became ubiquitous with video conferencing.
Thomas Davenport, a visiting scholar at the MIT Initiative on the Digital Economy, and Barry Libert, the CEO of AIMatters, identify five lessons learned from Zoom, Slack, and other product-led companies.
Lean and agile product development lets customers evaluate products early and often while making it possible to deliver frequent updates.
Products evolve continuously, with new functionality added frequently (and sometimes through partnerships with other vendors).
Qualified leads emerge organically from users of a free or a trial version, dramatically reducing the sales and marketing costs often associated with growth.
Product engineering is highly prioritized, in large part because customer service is embedded in the product itself (though large customers still get a dedicated sales force).
Analytics plays a vital role, both in using customer behavior data to drive future product decisions and in adding AI capabilities to products.
These lessons can be applied at enterprises operating in markets beyond software, Davenport and Libert write, given software’s growing role as a channel to help companies connect to customers. The key is incorporating digital capabilities that scale without the need for additional staff.
6 tips to increase AI buy-in and adoption
Employees tend to resist adoption of artificial intelligence tools because they bring few benefits, lead to additional work, and decrease autonomy. This is largely because those who sponsor adoption of an AI tool aren’t the ones expected to use the tool.
Research from MIT Sloan professor has identified six tactics to increase AI tool adoption, particularly among front-line workers in human resources, sales, and purchasing roles.
- Develop AI tools that address users’ true pain points.
- Reward the outcomes the AI tool is designed to improve.
- Reduce data work.
- Reduce integration work.
- Avoid infringing on end user core tasks.
- Let end users evaluate the AI tool.
Kellogg offered examples of all six tactics in a recent MIT Sloan Management Review webinar.
The benefit of learning why cyberattacks happen
News stories about cyberattacks focus primarily on what happened, rarely on how it happened, and almost never on why it happened. However, failing to understand why an attack was possible makes it difficult for enterprises to learn from mistakes. A study led by MIT Sloan professor concluded that nearly all cyberattacks stem from semiconscious decision-making, or the failure to consider the consequences of a choice.
In simple terms, it’s a bank manager not replacing a burglar alarm without realizing that could result in a robbery. Cyberattacks are much more difficult, as getting into the computer system is just the first step. In the case of the infamous 2017 Equifax breach that exposed personal information for 148 million people, Madnick’s research identified 19 separate safety controls where semiconscious decisions at all levels of the organization left the company vulnerable. For example, data was not encrypted — despite compliance requirements to do so — and security monitoring systems were malfunctioning due to expired certificates that had been deemed a low priority.
Executives need to do a better job of understanding cybersecurity risk, Madnick writes. He recommends that cyber risk assessment be part of any company-wide plan to increase revenue or decrease costs —and that the company proceed only if the cyber risk has been deemed acceptable.