Papers: Incorporating user needs into engineering design

Pattern Analysis of IDEO's Human-Centered Design Methods in Developing Regions

[+] Author and Article Information
Mark Fuge

Department of Mechanical Engineering,
University of Maryland,
College Park, MD 20740
e-mail: fuge@umd.edu

Alice Agogino

Department of Mechanical Engineering,
Berkeley Institute of Design,
University of California,
Berkeley, CA 94709
e-mail: agogino@berkeley.edu

IDEO.org has since change the name of HCD Connect to simply the DesignKit, which can be found at: http://www.designkit.org

For example, the difference between intra- and inter-stage correlations is +0.04 for the full 809 cases, but reduces to −0.03 when one analyzes only cases that use methods from all phases. This difference is confirmed via statistical permutation tests (with p ≈ 0.0054 and p ≈ 0.99, respectively) available via the paper's supplemental research code.

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received September 14, 2014; final manuscript received January 18, 2015; published online May 19, 2015. Assoc. Editor: Wei Chen.

J. Mech. Des 137(7), 071405 (Jul 01, 2015) (10 pages) Paper No: MD-14-1571; doi: 10.1115/1.4030047 History: Received September 14, 2014; Revised January 18, 2015; Online May 19, 2015

While there is increasing interest in designing for the developing world, identifying appropriate design research methods for understanding user needs and preferences in these unfamiliar contexts is a major challenge. This paper demonstrates how to apply a variety of statistical techniques to an online design case study repository, Human-Centered Design (HCD) Connect, to discover what types of methods designers use for identifying user needs and preferences for developing-world problems. Specifically, it uncovers how the following factors correlate to method usage: application area (e.g., farming versus healthcare), affiliation of the person using the method (IDEO designer versus not), and stages of the user research process. It finds that designers systematically use certain types of methods for certain types of problems, and that certain methods complement each other in practice. When compared with non-IDEO users, professional designers at IDEO use fewer methods per case and focus on earlier stages of the process that involve data gathering. The results demonstrate the power of combining data-driven statistical techniques with design case studies to identify user research methods for different developing-world problems, as well as locating which research methods complement each other. It also highlights that professionals designing for developing-world contexts commit more time to earlier stage user research efforts, rather than in concept generation or delivery, to better understand differences in needs and design contexts.

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IDEO.org, 2014, “HCD Connect: Where Optimists Take on Our Word's Challenges by Sharing Stories, Questions, and Resources,” Accessed January, 2014, http://www.hcdconnect.org
Hewens, S., 2013, “Smartlife is Open for Business Selling Pure Drinking Water,” Accessed January, 2014, https://www.ideo.org/stories/smartlife-is-open-for-business-selling-pure-drinking-water
Kumar, V., 2012, 101 Design Methods: A Structured Approach for Driving Innovation in Your Organization, 1st ed., Wiley, Hoboken.
Broadbent, G., and Ward, A., 1969, Design Methods in Architecture (AA Papers), Lund Humphries, London.
Broadbent, G., 1979, “The Development of Design Methods,” Des. Methods Theor., 13(1), pp. 41–45.
Jones, J. C., 1992, Design Methods, 2nd ed., Wiley, New York.
Helen Hamlyn Centre for Design, 2013, “Designing With People: Methods,” Accessed November, 2013, http://designingwithpeople.rca.ac.uk/methods
Roschuni, C., Agogino, A., and Beckman, S., 2011, “The DesignExchange: Supporting the Design Community of Practice,” Proceedings of the 18th International Conference on Engineering Design, ICED’11, Copenhagen, Aug. 15–19, pp. 255–264, Wiley, Hoboken.
“ The DesignExchange: Interactive Portal for the Design Community of Practice,” Accessed November, 2013, http://www.thedesignexchange.org/
Fuge, M., Peters, B., and Agogino, A., 2014, “Machine Learning Algorithms for Recommending Design Methods,” ASME J. Mech. Des., 136(10), p. 101103. [CrossRef]
Hayes, C. C., Goel, A. K., Tumer, I. Y., Agogino, A. M., and Regli, W. C., 2011, “Intelligent Support for Product Design: Looking Backward, Looking Forward,” ASME J. Comput. Inf. Sci. Eng., 11(2), p. 021007. [CrossRef]
Papanek, V., 2005, Design for the Real World: Human Ecology and Social Change, 2nd ed., Academy Chicago Publishers, Chicago.
Margolin, V., 2007, “Design for Development: Towards a History,” Des. Stud., 28(2), pp. 111–115. [CrossRef]
Oosterlaken, I., 2009, “Design for Development: A Capability Approach,” Des. Issues, 25(4), pp. 91–102. [CrossRef]
Nieusma, D., 2004, “Alternative Design Scholarship: Working Toward Appropriate Design,” Des. Issues, 20(3), pp. 13–24. [CrossRef]
Prahalad, C. K., 2006, The Fortune at the Bottom of the Pyramid, Pearson Education India, Delhi.
Subrahmanyan, S., and Tomas Gomez-Arias, J., 2008, “Integrated Approach to Understanding Consumer Behavior at Bottom of Pyramid,” J. Consum. Mark., 25(7), pp. 402–412. [CrossRef]
Polak, P., 2008, Out of Poverty What Works When Traditional Approaches Fail, Berrett-Koehler Publishers, San Francisco.
Wahl, D. C., and Baxter, S., 2008, “The Designer's Role in Facilitating Sustainable Solutions,” Des. Issues, 24(2), pp. 72–83. [CrossRef]
Donaldson, K., 2009, “The Future of Design for Development: Three Questions,” Inf. Technol. Int. Dev., 5(4), pp. 97–100. [CrossRef]
Brown, T., 2008, “Design Thinking,” Harv. Bus. Rev., 86(6), pp. 84–92. [CrossRef] [PubMed]
Dym, C. L., Agogino, A. M., Eris, O., Frey, D. D., and Leifer, L. J., 2005, “Engineering Design Thinking, Teaching, and Learning,” J. Eng. Educ., 94(1), pp. 103–120. [CrossRef]
Gasson, S., 2003, “Human-Centered vs. User-Centered Approaches,” J. Inf. Technol. Theory Appl., 5(2), pp. 29–46. [CrossRef]
Brown, T., and Wyatt, J., 2010, “Design Thinking for Social Innovation,” Dev. Outreach, 12(1), pp. 29–43. [CrossRef]
Winter, A. G., 2006, “Assessment of Wheelchair Technology in Tanzania,” Int. J. Serv. Learn. Eng., 1(2), pp. 60–77. [CrossRef]
Winter, A., 2013, “Stakeholder and Constraint-Driven Innovation of a Novel, Lever-Propelled, All-Terrain Wheelchair,” ASME Paper No. DETC2013-12588. [CrossRef]
Mattson, C. A., and Wood, A. E., 2013, “Eight Principles Derived From the Engineering Literature for Effective Design for the Developing World,” ASME Paper No. DETC2013-13108. [CrossRef]
Wood, A. E., and Mattson, C. A., 2014, “A Method for Determining Customer Needs in the Developing World,” ASME Paper No. DETC2014-35357. [CrossRef]
MIT, 2014, “D-Lab,” Accessed January, 2014, https://d-lab.mit.edu/creative-capacity-building
Taha, K. A., 2011, “Creative Capacity Building in Post-Conflict Uganda,” Ph.D. thesis, Massachusetts Institute of Technology, Cambridge.
Vechakul, J., and Agogino, A., 2013, “A Comparison of Two Transdisciplinary Human-Centered Design Approaches for Poverty Alleviation,” Proceedings of the Future of Transdisciplinary Design (TFTD13), (in press).
Benjamini, Y., and Hochberg, Y., 1995, “Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing,” J. R. Stat. Soc. Ser. B, 57(1), pp. 289–300. [CrossRef]
Fuge, M., and Agogino, A., 2014, “User Research Methods for Development Engineering: A Study of Method Usage With IDEO's HCD Connect,” ASME Paper No. DETC2014-35321. [CrossRef]
ISO, 2010, “Ergonomics of Human–System Interaction—Part 210: Human-Centred Design for Interactive Systems,” ISO 9241-210:2010, International Organization for Standardization, Geneva.
Griffin, A., and Hauser, J. R., 1993, “The Voice of the Customer,” Mark. Sci., 12(1), pp. 1–27. [CrossRef]
Gordon, P., Fuge, M., and Agogino, A., 2014, “Design for Development Online: An HCD Analysis of OpenIDEO,” ASME Paper No. IMECE2014-38751. [CrossRef]


Grahic Jump Location
Fig. 1

An example of an HCD case. Some common elements include: (a) a title and description discussing the problem and methods used, (b) information about the user submitting the case study, (c) a list of focus areas applicable to the case, and (d) a list of HCD Toolkit methods that the case used

Grahic Jump Location
Fig. 2

Percent method usage by case. Overall, users use methods from earlier design stages more frequently.

Grahic Jump Location
Fig. 3

Over every case, certain methods more positively correlate with other methods with almost no negative correlation between methods. The shaded boxes indicate the correlation coefficient between methods—darker indicates increasing positive correlation. The diagonal is thresholded to 0.4 for clarity of presentation, since it always has correlation of one. Methods from later stages (create and deliver) have higher correlation within each category, as well as across categories. Deliver, Create, and Hear methods are clustered together in that order from top to bottom [10,33].

Grahic Jump Location
Fig. 7

Differences in particular method usage between IDEO and non-IDEO members. The methods are grouped by green, orange, and purple for hear, create, and deliver, respectively. As noted in Fig. 6, IDEO members tend to use fewer methods per case overall, and particularly focus on the first design stage (hear) on user needs and preferences. The bars represent 95% confidence intervals around the usage percentage, created using bootstrap resampling.

Grahic Jump Location
Fig. 6

Method usage grouped by organizational affiliation. Combined columns, such as “hear+create,” indicate cases where at least one method from each category was used in the case. IDEO members contribute case studies that typically focus on the first design stage (hear), and rarely submit cases that combine methods across different design stages. In contrast, non-IDEO members contribute cases that use a more even distribution of methods from different design stages, and typically combine methods from different stages in a single case study. The error bars around the percentage estimates represent 95% confidence intervals calculated through bootstrap resampling.

Grahic Jump Location
Fig. 5

A normal probability plot for focus area method t-statistics. Most methods in each focus area are not appreciably difference from their usage overall; however, for selected methods on the left and right hand side, their usage patterns differ from other focus areas. Table 4 lists the methods, whose usage differs across particular focus areas.

Grahic Jump Location
Fig. 4

By restricting the cases to only those that used methods across all cases, one can remove certain temporal relationships between methods



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