Data Management

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Improving Strategic Execution With Machine Learning

Our 2018 Strategic Measurement research shows that companies using machine learning to optimize business processes and decision-making have distinct advantages over those that aren’t investing in ML. By using ML technology to make KPIs more predictive and prescriptive, these data-driven companies are redefining how to create and measure value.

Technical Debt Might Be Hindering Your Digital Transformation

Data reveals the C-suite recognizes that technical debt — the “price” companies pay for short-term technological fixes — hinders their ability to innovate and adapt in the digital age. One strategy to combat technical debt? Digital decoupling.

Following the Digital Thread: Creating a Smart Part and Managing Its Life Cycle

  • Video | Runtime: 0:06:37

  • Read Time: 1 min 

In Part 2 of our eight-part video series, we explore how technology affects product and component design. The digital thread not only streamlines product design via the ability to digitally scan an existing part or design a new one using computer-aided design (CAD) software, it can also accelerate the development process by affording previously unattainable levels of transparency and input.

How Big Data and AI Are Driving Business Innovation in 2018

According to a 2018 NewVantage Partners survey, executives now see a direct correlation between big data capabilities and AI initiatives. For the first time, large corporations report having direct access to meaningful volumes and sources of data that can feed AI algorithms to produce a range of business benefits from real-time consumer credit approval to new product offers.

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Your Data Is Worth More Than You Think

Data has become a key input for driving growth, enabling businesses to maintain a competitive edge. Given the growing importance of data to companies, how should managers measure its value? An increasing number of institutions, academics, and business leaders have begun tackling the valuation problem to help organizations realize more value from their data.

Give Technical Experts a Role in Defining Project Success

Poor communication between managers and technical experts is an obstacle to technology innovation that literally has been present for centuries. To overcome these issues, leaders need to absorb three key lessons about how to manage the inherent tensions between defining technical requirements and achieving valuable business outcomes.

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IoT and Developing Analytics-Based Data Products

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.

Free Webinar, Dec. 1: IoT and Developing Analytics-Based Data Products

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.

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Six Lessons From Amsterdam’s Smart City Initiative

The city of Amsterdam is becoming a model for “smart cities” through its innovation efforts to improve the lives of its employees and inhabitants. This case offers insights into what it takes to achieve these goals, including: taking the crucial step of doing an initial inventory of data available; using and integrating data from the private sector; and experimenting and learning from pilot projects.

Blockchain Data Storage May (Soon) Change Your Business Model

Blockchain is a data storage technology with implications for business that extend well beyond its most popular application to date — the virtual currency, Bitcoin. Managers need to build their organization’s absorptive capacity around this topic for at least three reasons: (1) the potential effects on organizational value chains, (2) communication within and between organizations, and (3) benefits from cooperation.

Variety, Not Volume, Is Driving Big Data Initiatives

The past several years have been period of exploration, experimentation, and trial and error in Big Data among Fortune 1,000 companies, and the result has been a different story. For these firms, it is not the ability to process and manage large data volumes that is driving successful Big Data outcomes. Rather, it is the ability to integrate more sources of data than ever before — new data, old data, big data, small data, structured data, unstructured data, social media data, behavioral data, and legacy data. Guest blogger Randy Bean, CEO of NewVantage Partners, explains why the “variety challenge” has emerged as the top data priority.

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