Analysis
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- 06 Apr 2020
- Working Paper Summaries
A General Theory of Identification
Statistical inference teaches us how to learn from data, whereas identification analysis explains what we can learn from it. This paper proposes a simple unifying theory of identification, encouraging practitioners to spend more time thinking about what they can estimate from the data and assumptions before trying to estimate it.
- 09 Dec 2019
- Research & Ideas
Identify Great Customers from Their First Purchase
Using data from their very first transaction, companies can identify shoppers who will create the best long-term value, says Eva Ascarza. Open for comment; 0 Comments.
- 29 Oct 2019
- Working Paper Summaries
Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders
Research on the traumatic 1947 partition of British India has most often been carried out by scholars in the humanities and qualitative social sciences. This article presents mixed methods research and analysis to explore tensions within current scholarship and to inspire new understandings of the Partition, and more generally, mass migrations and displacement.
- 30 Jun 2019
- Working Paper Summaries
The Comprehensive Effects of Sales Force Management: A Dynamic Structural Analysis of Selection, Compensation, and Training
When sales forces are well managed, firms can induce greater performance from them. For this study, the authors collaborated with a major multinational firm to develop and estimate a dynamic structural model of sales employee responses to various management instruments like compensation, training, and recruiting/termination policies.
- 07 Jan 2019
- Research & Ideas
The Better Way to Forecast the Future
We can forecast hurricane paths with great certainty, yet many businesses can't predict a supply chain snafu just around the corner. Yael Grushka-Cockayne says crowdsourcing can help. Open for comment; 0 Comments.
- 28 Nov 2018
- HBS Case
On Target: Rethinking the Retail Website
Target is one big-brand retailer that seems to have survived and even thrived in the apocalyptic retail landscape. What's its secret? Srikant Datar discusses the company's relentless focus on online data. Open for comment; 0 Comments.
- 01 Nov 2018
- Working Paper Summaries
Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning
Passengers arriving at international hubs often endure delays, especially at immigration and security. This study of London’s Heathrow Airport develops a system to provide real-time information about transfer passengers’ journeys through the airport to better serve passengers, airlines, and their employees. It shows how advanced machine learning could be accessible to managers.
- 29 Apr 2018
- Working Paper Summaries
Analyzing the Aftermath of a Compensation Reduction
This study of the effects of compensation cuts in a large sales organization provides a unique lens for analyzing the link between compensation schemes, worker performance, and turnover.
- 11 Dec 2017
- Working Paper Summaries
The Use and Misuse of Patent Data: Issues for Corporate Finance and Beyond
Corporate finance researchers who analyze patent data are at risk of making highly predictable errors. The problem arises from dramatic changes in the direction and location of technological innovation (and patenting practice) over recent decades. This paper explains the pitfalls and suggests practical steps for avoiding them.
- 21 Aug 2017
- Lessons from the Classroom
Companies Love Big Data But Lack the Strategy To Use It Effectively
Big data is a critical competitive advantage for companies that know how to use it. Harvard Business School faculty share insights that they teach to executives. Open for comment; 0 Comments.
- 06 Jul 2017
- Working Paper Summaries
Do All Your Detailing Efforts Pay Off? Dynamic Panel Data Methods Revisited
Personal selling in the form of detailing to physicians is the main go-to-market practice in the pharmaceutical industry. This paper provides a practical framework to analyze the effectiveness of detailing efforts. The method and empirical insights can help firms allocate sales-force resources more efficiently and devise optimal routes and call-pattern designs.
- 09 Dec 2015
- Working Paper Summaries
Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life
Michael Luca, Scott Duke Kominers and colleagues describe a number of new urban data sources and illustrate how they can be used to improve the study and function of cities.
- 09 Apr 2014
- Working Paper Summaries
Visualizing and Measuring Software Portfolio Architectures: A Flexibility Analysis
Contemporary business environments are constantly evolving, requiring continual changes to the software applications that support a business. Moreover, during recent decades, the sheer number of applications has grown significantly, and they have become increasingly interdependent. Many companies find that managing applications and implementing changes to their application portfolio architecture is increasingly difficult and expensive. Firms need a way to visualize and analyze the modularity of their software portfolio architectures and the degree of coupling between components. In this paper, the authors test a method for visualizing and measuring software portfolio architectures using data of a biopharmaceutical firm's enterprise architecture. The authors also use the measures to predict the costs of architectural change. Findings show, first, that the biopharmaceutical firm's enterprise architecture can be classified as core-periphery. This means that 1) there is one cyclic group (the "Core") of components that is substantially larger than the second largest cyclic group, and 2) this group comprises a substantial portion of the entire architecture. In addition, the classification of applications in the architecture (as being in the Core or the Periphery) is significantly correlated with architectural flexibility. In this case the architecture has a propagation cost of 23 percent, meaning almost one-quarter of the system may be affected when a change is made to a randomly selected component. Overall, results suggest that the hidden structure method can reveal new facts about an enterprise architecture. This method can aid the analysis of change costs at the software application portfolio level. Key concepts include: This method for architectural visualization could provide valuable input when planning architectural change projects (in terms of, for example, risk analysis and resource planning). The method reveals a "hidden" core-periphery structure, uncovering new facts about the architecture that could not be gained from other visualization procedures or standard metrics. Compared to other measures of complexity, coupling, and modularity, this method considers not only the direct dependencies between components but also the indirect dependencies. These indirect dependencies provide important input for management decisions. Closed for comment; 0 Comments.
- 10 Jun 2013
- Research & Ideas
How Numbers Talk to People
In their new book Keeping Up with the Quants, Thomas H. Davenport and Jinho Kim offer tools to sharpen quantitative analysis and make better decisions. Read our excerpt. Open for comment; 0 Comments.
- 25 Apr 2012
- What Do You Think?
How Will the “Age of Big Data” Affect Management?
Summing up: How do we avoid losing useful knowledge in a seemingly endless flood of data? Jim Heskett's readers offer some wise suggestions. What do you think? Closed for comment; 0 Comments.
- 05 May 2010
- What Do You Think?
Is Denial Endemic to Management?
Poring over reader responses to his May column, HBS professor Jim Heskett is struck by the fact that they include behavioral, structural, and even mechanical remedies. (Forum now closed. Next forum opens June 3.) Closed for comment; 0 Comments.
- 15 Apr 2010
- Working Paper Summaries
The Consequences of Entrepreneurial Finance: A Regression Discontinuity Analysis
What difference do angel investors make for the success and growth of new ventures? William R. Kerr and Josh Lerner of HBS and Antoinette Schoar of MIT provide fresh evidence to address this crucial question in entrepreneurial finance, quantifying the positive impact that angel investors make to the companies they fund. Angel investors as research subjects have received much less attention than venture capitalists, even though some estimates suggest that these investors are as significant a force for high-potential start-up investments as venture capitalists, and are even more significant as investors elsewhere. This study demonstrates the importance of angel investments to the success and survival of entrepreneurial firms. It also offers an empirical foothold for analyzing many other important questions in entrepreneurial finance. Key concepts include: Angel-funded firms are significantly more likely to survive at least four years (or until 2010) and to raise additional financing outside the angel group. Angel-funded firms are also more likely to show improved venture performance and growth as measured through growth in Web site traffic and Web site rankings. The improvement gains typically range between 30 and 50 percent. Investment success is highly predicated by the interest level of angels during the entrepreneur's initial presentation and by the angels' subsequent due diligence. Access to capital per se may not be the most important value-added that angel groups bring. Some of the "softer" features, such as angels' mentoring or business contacts, may help new ventures the most. Closed for comment; 0 Comments.
- 22 Aug 2005
- Research & Ideas
The Hard Work of Failure Analysis
We all should learn from failure—but it's difficult to do so objectively. In this excerpt from "Failing to Learn and Learning to Fail (Intelligently)" in Long Range Planning Journal, HBS professor Amy Edmondson and coauthor Mark Cannon offer a process for analyzing what went wrong. Closed for comment; 0 Comments.
Time Dependency, Data Flow, and Competitive Advantage
The perishability of data has strategic implications for businesses that provide data-driven products and services. This paper illustrates how different business areas might differ with respect to the rate of decay in data value and the importance of data flow in their operations.