In recent years, a handful of Chinese companies like Alibaba, Haier, and Tencent have garnered a lot of attention as they have emerged as global innovators. They are challenging the R&D strategies of foreign companies and offering lessons on how to make ideas commercially viable. But there’s another, less obvious force to be reckoned with in China: thousands of innovative companies that are quietly disrupting numerous industries and developing new products and new business models.

Do consumers care enough about companies’ environmental and social practices to give them more business? Caesars Entertainment tested the question at one of its hotels, where one group of customers was told about its green efforts and the other group was told nothing. The casino company got encouraging results: The group who got the message spent 1.5% more. That group also recommended the hotel more enthusiastically.

Converging technologies are realigning how organizations operate in an increasingly connected world. Companies that take the time to understand and invest in crucial technologies will benefit from lower barriers to entry in new markets and sectors and greater ease in developing and scaling new capabilities in the next generation of business.

Each month, the MIT SMR Strategy Forum poses a single question to our panel of experts in the fields of business, economics, and management. This month’s question asks our panel whether, in the next five years, blockchain technology will have a transformative effect on emerging markets in the global economy.

As leaders of established businesses focus on becoming digital, they often embrace the mantra, act like a startup. A startup is an experiment, and its early goal is to learn, as quickly and inexpensively as possible, if an idea has merit. That same ability to figure out how a new value proposition might create revenues and profits is key to digital success. Established companies that want to test ideas for such propositions should be nurturing four traits of startups.

This episode of Counterpoints examines the strategic value of data analytics — and more to the point, whether the data scientists creating the analysis are being rewarded appropriately for their contribution to strategy.

The traditional method for selling — typically framed around asking the customers’ needs — is not enough. Why? Because often customers don’t recognize their core problem. To increase sales, managers should direct their teams on taking a problem-centric approach.

Platform companies with the largest user networks offer significant value for consumers. Yet total network size isn’t the only key to competitive advantage; platform users may place equal or greater weight on having access to specific, local, or higher-quality platform users or information about the network or its participants.

From what “being digital” really means for organizations to how developing strategy can feel akin to finding cadence in jazz, there was no shortage of insightful comments from our readers in 2018.

Just a few years back, IBM was betting the farm on artificial intelligence with Watson. But with its recent acquisition of Red Hat, IBM has now turned its attention to cloud computing and infrastructure in a strategic move that may have long-term impact in the software industry.

The value of big data is being captured by large companies, but many small businesses are being left behind. One reason: Investors get more data from larger companies, so that’s where they place their bets. Startup and small business owners must think about their data as a new class of economic asset and understand their data helps investors assess them—which affects their ability to raise capital.

Each month, the MIT SMR Strategy Forum poses a single question to our panel of experts in the fields of business, economics, and management. This month’s question asks our panel whether industry self-regulation can help mitigate climate change.

In 2018, MIT Sloan Management Review readers gravitated toward new articles that will help them prepare for the future of work, including topics as varied as skills needed in the age of AI and digital communication tools for virtual teams. The most popular article of the year focused on an area high on the list of most CEOs’ agendas: how to transform your organization successfully.

Companies are racing to apply machine learning to important business decisions, only to realize that the data they need doesn’t even exist yet. In essence, the fancy new AI systems are being asked to apply new techniques to the same old material. The result is a visible arms race as companies bring on machine learning coders and kick off AI initiatives alongside a behind-the-scenes, panicked race for new and different data.

CEOs discussing business model transformation. Innovation that drives sales. Bots as (actually useful) customer service agents. How to charge for the things you used to give away. These are a few of our favorite things in MIT SMR’s Winter issue.

In the world of cloud computing, the spotlight has mostly been on cloud providers and their ability to help organizations digitally transform. With new scrutiny around data localization and privacy, enterprises must consider localization impacts on their cloud computing strategy as they invest and innovate with emerging technologies.

Examining skill sets and mind-sets will help leaders understand what it means to be a leader in the digital economy. This will include requirements such as changing mastery, executing excellence, nurturing relationships, and, notably, building a culture of radical trust.

Travel marketers who take advantage of the large volumes of data their organizations collect to generate new KPIs and ML initiatives will continue to pull ahead of their rivals.

Increasingly, military-inspired exercises are becoming standard elements of corporate risk mitigation and resiliency efforts. They include tabletop exercises,” designed to help executives envision how they would handle different risk scenarios; “red team exercises,” designed to ferret out weaknesses through contained attacks conducted internally to see how cybersecurity teams respond; and engaging ethical hackers to test the organization’s cybersecurity defenses.

Our research on KPIs suggests there is no clear best practice when it comes to relying on data versus intuition to make strategic decisions.