Business Process Optimization

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Winning With Open Process Innovation

  • Research Feature
  • Read Time: 11 min 

Managers in manufacturing companies often keep process innovation activities tightly under wraps. Some companies have good reasons for keeping process innovations concealed. However, the authors’ research suggests that for most manufacturers, such defensiveness deprives companies of a valuable source of ideas for productivity improvement. Many manufacturers, they argue, can benefit from sharing process innovations rather than keeping them secret.

Your Company Doesn’t Need a Digital Strategy

  • Blog
  • Read Time: 6 min 

As sexy as it is to speculate about new technologies such as AI, robots, and the internet of things, the focus on technology can steer the conversation in a dangerous direction. Because when it comes to digital transformation, digital is not the answer. Transformation is. In various industries, including banking, paint, and shipbuilding, digital leaders are finding that technology’s value comes from doing business differently because technology makes it possible.

The Fatal Flaw of AI Implementation

Many managers are excited about smart machines but are struggling to apply machines’ limited intelligence. Indeed, computers can process data just fine, but to generate competitive advantage from machine learning applications, organizations must upgrade their employees’ skills. Companies will also need to redesign employee accountabilities to empower and motivate them to deploy smart machines when doing so will enhance outcomes.

Participant Questions From the Recent Data and Analytics Webinar: Round 2

On March 15, 2017, MIT SMR held a webinar to share insights from our report, “Analytics as a Source of Business Innovation.” Many participants asked questions during the webinar that we didn’t have time for, so we decided to answer them in blog format instead. This post is the second set of responses.

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Questions and Answers About Analytics as a Source of Business Innovation

On March 15, 2017, MIT SMR held a webinar to share insights from our report, “Analytics as a Source of Business Innovation,” which summarizes our findings about the increased ability to innovate with analytics and its benefits across industries. Many participants asked questions during the webinar that we didn’t have time for, so we’ll answer some of them in blog format instead.

Saving Money Through Structured Problem-Solving

  • Blog
  • Read Time: 6 min 

As busy as they are, leaders need to find ways to observe fundamental work processes in their organizations. When they do, they usually discover that there are gaps between theory and reality in how works get done. Michael Morales’ experience — in which identifying and addressing such gaps led to his company saving $50,000 in just 60 days — is a case in point.

Managing With Immature AI

  • Blog
  • Read Time: 4 min 

Though the current state of AI falls short of its promise, managers should find ways to incorporate it into business practices now. Using pragmatic, thoughtful experiments and being transparent with customers and suppliers, organizations can learn and develop their own capabilities as AI continues to rapidly evolve.

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How to Monetize Your Data

Companies can monetize their data by improving internal business processes and decisions, wrapping information around core products and services, and selling information offerings to new and existing markets. Adopting any of these approaches, however, requires management commitment to specific organizational changes and targeted technology and data management upgrades.

Taking a Value-Chain Perspective on Innovation

Market leaders have many advantages when adopting new technologies such as e-business, but they don’t always make the move. Why? It’s partly because new technology can be leveraged along a chain of related companies only if business partners also make the leap to adopt these changes. And research reveals that when large companies are significantly concerned about customer adjustment costs of new innovations, these powerful and otherwise highly capable organizations often resist change.

Building a Better Car Company With Analytics

Using data and analytics to understand the complexities of modern business has become not only common, but essential. Gahl Berkooz joined Ford Motor Co. in 2004, eventually becoming head of data and governance and a member of the company’s global data insights and analytics skill team. Berkooz became acutely aware of how important analytics is to the company’s ability to thrive in the global marketplace. “What it boils down to,” he told MIT SMR’s Michael Fitzgerald, “is that we know how to make decisions. It’s about finding the opportunities to bring data and analytics to make better decisions.”

Tech Savvy: February 26, 2016

Peter Drucker defined the work of business leaders by three principal tasks: delivering financial results, making work and workers productive, and managing a company’s social impacts. Technological advances have transformed — and continue to transform — the world in myriad ways since Drucker published that definition in 1974. But technology hasn’t changed Drucker’s tasks. Instead, it is giving rise to new and better ways of executing them. This new column aims to help you identify big ideas and new tactics at the intersection of technology and management.

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How Time-to-Insight Is Driving Big Data Business Investment

With the emergence of a digital economy over the course of the past two decades, leading companies have learned that they must act faster to respond to customer needs and competitive dynamics. The fourth annual Big Data Executive Survey confirms that Fortune 1000 firms recognize that faster time-to-insight correlates with success and will be the driving force behind Big Data investment for the years ahead.

Ready or Not, Here IoT Comes

The Internet of Things is on the brink of transforming business, but most businesses aren’t ready for the changes to the marketplace that the IoT will bring. There is very little time for companies to prepare for the changes coming as data-collecting devices proliferate. The good news is that by recognizing certain challenges, organizations can begin the possible, albeit difficult, process of getting ready.

Overcoming Legacy Processes to Achieve Big Data Success

Most large corporations are saddled with fragmented analytical processes, limiting their ability to operate with agility, flexibility, and insight. As a result, larger firms are often challenged when it comes to innovation and responsiveness. But Big Data approaches that enabled the flexibility and rapid growth of newer, smaller firms are being adopted by mainstream corporations. The goal: overcome legacy challenges and introduce greater corporate speed.

Deodorizing Your Data

Problems with data quality come from a lot of sources — short-term solutions, mergers or acquisitions, or even the mundane complications of living in a complex society. The “stench” that develops when data quality declines can create serious issues for data-driven business. If a foul odor is emanating from your data, one solution might lie in refactoring analytics processes.

Innovating with Airborne Analytics

Hong Kong’s premier airline is using a blend of data and know-how to guide its daily operations. In an interview with MIT Sloan Management Review, Cathay Pacific CIO Joe Locandro describes how the airline uses analytics to make decisions that balance data with what it knows from the field. “Analytics will give you statistical spreads, give you training, but you still need to have this thing called experience and insight,” he says.

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