Big Data

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The Coming Consumer Data Wars

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  • Read Time: 4 min 

With tough new EU regulations on data security coming in 2018, global companies will soon be faced with a choice: Protect consumers’ data and reap the rewards of having access to it, or face the competitive consequences of consumer distrust. But companies caught unprepared for the change may lose the privilege of keeping consumers’ data altogether.

When Jobs Become Commodities

Most of us view our jobs as specialized or somehow differentiated, but the world of business and management increasingly feels otherwise. For many organizations today, the next big driver of job commoditization is automation driven by smart machines. Simply put, if a job is viewed as a commodity, it won’t be long before it’s automated. The key for workers whose jobs have traditionally seemed safe: Highlight the tasks that require a human touch.

Balance Efficiency With Transparency in Analytics-Driven Business

Algorithms are affecting many aspects of daily life, but most people have no clarity as to how they work — even in the companies that create and use them. But individuals and organizations need to carefully consider what this lack of transparency means when it comes to fairness and honesty in commercial interactions and decide where to draw the line on data ethics.

Romantic and Rational Approaches to Artificial Intelligence

Organizations have made rapid gains in their ability to generate big data sets, but the ability of managers and executives to develop insights from that data has lagged behind. Data processing by artificial intelligence offers the prospect of speeding things up — but it also risks expanding the gap, as managers lack understanding of how AI reaches its data-based conclusions.

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AI and the Need for Speed

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AI is rapidly changing how organizations make decisions, serve customers, increase quality, and reduce costs. But the pace of change may be too fast for managers to effectively manage processes, react to new problems, and learn from data whose usefulness has a shorter and shorter lifespan.

How Analytics and AI Are Driving the Subscription E-Commerce Phenomenon

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  • Read Time: 6 min 

Box subscription companies are growing dramatically, using a high level of personalization and artificial intelligence algorithms to keep customers satisfied and eager for more. Their astute use of social media and influence marketing has also contributed to their startling success.

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Why Your Company Needs Data Translators

When it comes to putting data to use, communication — or rather, lack of it — between the data scientists and the executive decision makers can cause problems. The two sides often don’t speak the same language and may differ in their approach to and respect for data-based decisions. Given these challenges, organizations may need to call upon a “data translator” to improve how data is incorporated into decision making processes.

Why Big Data Isn’t Enough

There is a growing belief that sophisticated algorithms paired with big data will find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and potentially risky, as spurious correlations and “noise” may lead analysts astray.

Free Video Panel: Creating a Data-Driven Enterprise: Real-Life Cases

In a video panel and Q&A, MIT SMR editors discuss key insights from a recently completed series of in-depth case studies on how prominent organizations are using data and analytics to transform their operations. They review Intermountain Healthcare, GE, Nedbank, and the City of Amsterdam’s efforts to become more data driven. This set of diverse organizations offers a unique perspective on the challenges and opportunities associated with becoming a data-driven organization.

Lessons from Becoming a Data-Driven Organization

Organizations across the business spectrum are awakening to the transformative power of data and analytics. They are also coming to grips with the daunting difficulty of the task that lies before them. It’s tough enough for many organizations to catalog and categorize the data at their disposal and devise the rules and processes for using it. It’s even tougher to translate that data into tangible value. But it’s not impossible, and many organizations, in both the private and public sectors, are learning how.

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Customer Relationships Get the Data Treatment

A case study by MIT Sloan Management Review, “A Data-Driven Approach to Customer Relationships,” details how the South African bank Nedbank is using its rich access to a trove of transactional data from credit card use — from the time of transactions and size of purchases to retailer locations, and even specific details like the age, gender, race, marital status, and income bracket of some users — to help merchants make strategic decisions to better serve those customers.

Achieving Trust Through Data Ethics

Eight out of 10 executives surveyed say that as the business value of data grows, the risks their companies face from improper handling of data increase exponentially. While digital advancements enable new opportunities for businesses to compete and thrive, they also create increased exposure to systemic risks. Success in the digital age will require a new kind of ethical review around how companies gather and use data.

Digital Today, Cognitive Tomorrow

Digital transformation is happening all around us, but it’s the foundation for a much more profound transformation still to come. With huge challenges facing humanity on many fronts — climate, disease, population, food and water — we need cognitive technologies to augment human problem-solving capabilities. And those technologies are almost here.

Showing 1-20 of 78