New “markets for judgment” like the Creative Destruction Lab are bridging critical gaps between scientific breakthroughs and commercial applications — fueling tech-based entrepreneurship far from Silicon Valley.

Companies tend to compete not as individual entities, but as members of networks — which makes collaboration a strategic necessity, not merely a tactical choice. But while many executives say they want win-win solutions, in reality, they usually seek victories that don’t excessively annoy their counterparts. In other words, “win/no-lose” is a more accurate description.

Leaders today must wean their companies away from three pieces of conventional wisdom about digital strategy: agility, first-mover advantage, and minimum viable product. These ideas have anchored technological decision-making for over a decade but are highly unsuitable for the emerging world. In conditions of environmental uncertainty and interconnected technology, we need more thoughtfulness rather than more speed.

Innovation, much like marketing and human resources, can be made less reliant on artful intuition by using information in new ways. But this requires a change in perspective: We need to view innovation not as the product of luck or extraordinary vision but as the result of a deliberate search process.

For over 30 years, MIT Sloan’s Eric von Hippel has investigated the ways general users of products and services have improved them through tinkering and invention. “The Age of the Consumer-Innovator,” which he co-authored for MIT Sloan Management Review in 2011, was an important marker in explaining how user communities were changing product development. It laid the groundwork for von Hippel’s current research, which looks at the way some of today’s innovation is given away as a “free good.”

Coauthors Thomas H. Davenport and Stephan Kudyba discuss the many ways for organizations to monetize data, including selling “data products” directly to consumers. A seven-step model shows the way real-life companies are developing those products and services.

On Dec. 1 at 11 a.m. EST, join MIT SMR coauthors Thomas H. Davenport and Stephan Kudyba in a free, live webinar, where they will discuss their recent article, “Designing and Developing Analytics-Based Data Products.” The authors will look at the ways in which the internet of things, market forces, and evolving technology are changing how companies plan the development of data products. This new product category requires a reworking of the traditional phases of product development.

The combination of new analytical capabilities and burgeoning data assets are being used to form value-added “data products.” Such products have powered rapid growth in the value and success of online companies, but the expansion of analytics means the standard model for developing these products needs to evolve. An updated model needs to reflect new “time to market” expectations and input from a variety of stakeholders.

What’s happening this week at the intersection of management and technology.

Fast, iterative “virtual research centers,” where hypotheses are tested and improved before they are scaled into new products, are edging out traditional R&D approaches.

Bringing high-tech inventions built on patented technologies to market can be complicated and risky. The threat of added costs from patent infringement lawsuits has led technology companies to pool their talents — and patents — in technology consortia. Joining a tech consortium requires managers to weigh intellectual property value against the value of future collaborations and assess the consortium’s pros and cons for innovation, competition, and market creation.

A better strategy for managing digital disruption; enhancing product development with micro-factories; the untapped potential of supply chain digitization.

The Spring 2016 issue of MIT Sloan Management features a Special Report on new product development. Articles include “Why Great New Products Fail,” “Finding the Right Role for Social Media in Innovation,” “Developing New Products in Emerging Markets,” “Why Learning is Central to Sustained Innovation,” and a look at the opportunities presented by the Internet of Things, in “Now That Your Products Can Talk, What Will They Tell You?”

Many innovative new products don’t succeed. One common reason: Companies don’t focus on understanding how customers make purchase decisions. But paying attention to how customers search for information about what to buy, and how they make guesses about details they can’t easily find, helps predict whether customers will embrace certain product innovations. Companies need to focus on innovations that customers will easily recognize or find ways to alert them to innovations they may not detect on their own.

Products connected to the Internet of Things are providing unprecedented levels of information that can be used to improve both products and customer experience. For instance, a company does not have to wait until a customer calls with a complaint to know that a product connected to the Internet of Things is not working correctly. Instead, the product could already communicate the information, giving the company the ability to provide proactive service. Result: more loyal customers.

How can multinational companies turn ideas from their emerging-market subsidiaries into global products? A successful innovation developed by Cisco’s R&D unit in India offers practical insights into how to make that process work effectively. Key enablers in the Cisco case included well-developed R&D capabilities at a company center in Bangalore, a large market opportunity, and the support of executive champions. The process also demanded clarity about what product to develop, and how — including working on a shoestring budget.

Many managers think they can create better products just by improving the development process or adding new tools. But it’s skilled people, not processes, that create great products. So-called “lean” organizations invest heavily and continuously in the skills of product developers, and rather than developing single products, they think in terms of streams of products. By making people the backbone of the product development system, companies can achieve a triple win: increased innovation, faster time to market, and lower costs.

Beijing-based smartphone maker Xiaomi Inc. has actively involved enthusiastic customers — known as “Mi Fans” — in both software and hardware development processes. Tech-savvy users test interfaces and products as volunteers, doing much of their communication on the Internet. Customer involvement in the product development life cycle has not only helped Xiaomi reduce R&D costs but also enabled the company to cultivate a sense of participation and pride among lead users.

At its roots, life-cycle assessment (LCA) is a method to quantify total sustainability impacts — like resource use and environmental damage — over the entire life of a product, from “cradle to grave.” While there is informational value in the basic exercise, the real utility of LCA is comparison — that is, comparing one product’s sustainability impacts with another’s. Given the effort and cost involved, what are the strategic benefits of LCA? And should you be employing such a process?

When is the best time to enter a new industry? As it turns out, understanding the product category dynamics in an emerging industry and when a dominant category label has been introduced are important to identifying the “window of opportunity” to enter. Dominant category labels typically are introduced right before the industry starts a phase of rapid growth and consolidation. Companies would do well to track category labels before introducing a product in a nascent industry.