Visualizing and Measuring Software Portfolio Architecture: A Power Utility Case

Robert  Lagerström; Carliss Y. Baldwin; Alan   MacCormack

Article | Journal of Modern Project Management

Visualizing and Measuring Software Portfolio Architecture: A Power Utility Case

by Robert Lagerström, Carliss Y. Baldwin and Alan MacCormack

Abstract

In this paper, we test a Design Structure Matrix (DSM) based method for visualizing and measuring software portfolio architectures. Our data is drawn from a power utility company, comprising 192 software applications with 614 dependencies between them. We show that the architecture of this system can be classified as a “core-periphery” system, meaning it contains a single large dominant cluster of interconnected components (the “Core”) representing 40% of the system. The system has a propagation cost of 44% and architecture flow through of 93%. This case and these findings add another piece of the puzzle suggesting that the method could be effective in uncovering the hidden structure in software portfolio architectures.

Keywords: Software; Infrastructure; Utilities Industry;

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Citation:

Lagerström, Robert, Carliss Y. Baldwin, and Alan MacCormack. "Visualizing and Measuring Software Portfolio Architecture: A Power Utility Case." Special Issue on DSM Conference 2014. Journal of Modern Project Management 3, no. 2 (September–December 2015): 114–121.

Case | HBS Case Collection | October 2018 (Revised February 2020)

Innovation at Uber: The Launch of Express POOL

Chiara Farronato, Alan MacCormack and Sarah Mehta

Set in March 2018, the case follows ride-sharing company Uber as it develops and launches a new product called Express POOL. This product offers a reduced price to riders willing to carpool, walk a short distance to/from their pick-up and drop-off points, and wait a few minutes before being matched to a driver. Two weeks after the launch of Express POOL in six U.S. cities, Uber’s product managers discover that if riders are made to wait five minutes to be matched to a driver—rather than the standard two minutes—rider cancellation rates increase, but Uber’s costs per ride are reduced. Together with data scientists, engineers, and product operations specialists, the product managers must decide whether to keep rider wait times at two minutes or increase wait times to five minutes in the six newly launched cities. The decision is complicated by the fact that Uber’s data science team normally places a five-week moratorium on changes to any new product, to allow robust data to be collected on its performance. This case is paired with a supplementary dataset from Uber (HBS No. 619-702). In advance of the class discussion, students can analyze the data and draw their own conclusions about the trade-offs of maintaining the standard wait times or increasing them.

Keywords: Innovation and Management; Innovation Leadership; Innovation Strategy; Technological Innovation; Technology; Mobile Technology; Software; Technology Platform; Decision Making; Technology Industry; California; San Francisco;

Citation:

Farronato, Chiara, Alan MacCormack, and Sarah Mehta. "Innovation at Uber: The Launch of Express POOL." Harvard Business School Case 619-003, October 2018. (Revised February 2020.) View Details

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This multimedia supplement accompanies the case “Innovation at Uber: the Launch of Express POOL” (case no. 619-003). Set in March 2018, the case follows ride-sharing company Uber as it develops and launches a new product called Express POOL. This multimedia supplement features a 10-minute Q&A session with Uber data science managers Duncan Gilchrist and Eoin O’Mahony as they field questions posed by students pertaining to the case.

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Visualizing and Measuring Software Portfolio Architecture: A Power Utility Case

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