A shortage of reliable information is common in emerging markets. Because such markets are heterogeneous, the sources and methods for market intelligence require modification before they can be transferred from one emerging market to another. Market intelligence is thus best viewed and managed as a strategic asset that multinationals should invest in keeping up to date.

Companies often don’t know what their employees’ experience contributes until employees leave, taking their unique knowledge assets with them. But digital tools have the potential to reshape the relationship between organizations and retiring employees. First, when used for collaboration, advanced social media platforms can record all interactions between employees and preserve them for later use. And second, digital platforms introduce the possibility of redefining the relationship companies have with retired staff.

The Winter 2016 issue of MIT Sloan Management Review explores how increased transparency — and, in particular, the ready flow of information in a digital world — is changing the environment in which corporations operate. Transparency also is changing the distribution of power between large organizations and those who challenge them. Executives need to anticipate the possibility that any issues related to their company could someday be public knowledge.

When faced with information overload, it can be easier to make good decisions if you’re able to remove yourself from all the details of the decision and consider the choices more abstractly. Research shows that such distancing, which can be either temporal or physical, can help people to filter out the less-vital details and enable them to focus on the gist of the matter.

What differentiates data scientists from other quantitative analysts? It’s partly their skill set and partly their mind set. “The recent emergence of the digital enterprise has created a seemingly insatiable management appetite to amass and analyze data,” write Jeanne G. Harris and Vijay Mehrotra. Data scientists are particularly able to make sense of so much information. For instance, 85% said their projects often or always address new problems, compared to 58% of analysts who made that claim.

Curiosity about the decision-making process has heated up, attracting academics from neuroscience, management, behavioral economics and psychology. Researchers have found, for instance, that a willingness to ask for advice on difficult problems can increase a person’s perceived competence, and that too many choices can cause people to make less-than-optimal choices. Here, we highlight six scholarly articles that have intriguing insights into the factors that can affect decision-making.

As data analyses get more complex, how can companies best communicate results to ensure that decision makers have a proper grasp of the data’s implications? Research has found that letting decision makers gain experience on the outcomes of different possible actions by interacting with simulations helps those executives make better decisions. Simulations narrow the often a large gap between what analysts want to share and what decision makers understand, and more clearly illustrate complex statistical information.

A recent data and analytics survey sheds light on what large organizations are actually doing with big data initiatives. The survey of nearly 100 senior executives from Fortune 1000 companies found that executives are reporting anincreasing commitment to big data projects. As well, most executives, 70%, are looking to improve their “time to answer” with big data.

Companies’ use of sophisticated Six Sigma tools and similar improvement activities often creates information overload for workers, writes Satya S. Chakravorty of the Coles College of Business at Kennesaw State University.

How do you win with data? MIT SMR surveyed global executives about turning the data deluge and analytics into competitive advantage. Here’s an early snapshot of how managers are answering the most important question organizations face.

“To heck with what the technology can do,” says Michael Schrage of the MIT Center for Digital Business. Great managers, he says, first think about what kind of value they want to create and then consider how IT can help them create it.

There’s no sense in denying it: interpreting weak signals into useful decision making takes time and focus. These three stages can help you see the periphery—and act on it—much more clearly.

New research offers insights into the factors that affect how much an organization learns from its innovation activities.

It often seems that changes and threats come out of nowhere – until we learn later that the signals were there all along and we just didn”t read them correctly. One step toward reading them better is understanding why we misinterpret them in the first place.

Informal decision networks – both within teams and throughout organizations – can systematically bias the way decisions are framed and carried out. Here”s how to build your networks right.

In surveys, customers have long claimed that they’d pay more for ethically produced goods. But is that what happens when they actually buy things? New experiments offer answers.

Knowledge sharing between partners has more upsides than downsides, provided that the right kind of knowledge goes back and forth.