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Science Experiments

Assessing Biorepository Customer Needs

UX Research       2018       Lead Researcher

Key activities in human centered design research consulting

  • Partner mapping

  • Research & analysis plan

  • Interviews for lived experience data

  • Surveys

  • Performance metrics

  • Relationship diagramming

  • Data analysis: versus coding & affinity diagramming

  • Transforming findings into actionable solutions

Key Area of Inquiry

How do customers perceive the biorepository’s ability to safely & effectively store and share important samples?  What services might improve trust & satisfaction?

Photo of theme categorization that led to the data analysis decision to use versus coding, a qualitative coding method.

Collecting the Data

  • 1 customer satisfaction survey

  • 2 interview guides based on input from biorepository leadership and an analysis of 54 historic interview summaries. 

  • Selected maximum variation sampling strategy to ensure advisory board members and custodians (direct users) from diverse areas (e.g., infectious, noninfectious, etc.) included

  • Interviewed 10+ customers  

Using Empathy to Probe for Rich Data

During customer interviews, I probed for examples and stories to understand user's lived experiences; how people feel about the services and what they value.​

Generated 40 Versus Codes

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Culture Shift VS Sequester Collections

Dead Weight VS Alleviate Burden         

Free for All VS Tightly Controlled 

Hoarding Closet VS Opportunity                    

Authority VS Assistants           

Quality Assurance VS Expansion                        

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Data Analysis:

Versus Coding &
Affinity Diagramming

I led analysis of key informant interviews by identifying emerging themes, consulting with SMEs, and leading affinity diagramming.

I selected inductive & versus coding strategy since affinity diagramming showed conflicting goals across and among customers, advisors, and service providers. 

  • Assigned data labels (codes) using actual interview data (in vivo coding)

  • Generated 40 versus codes from interview summaries (see examples here)

Photo of relationship diagramming. Illustrates process of paring down codes and identifying relationships in the data

Relationship Diagramming 

  • Led 3 analysts to pare down codes into 6 categories and define the relationships

  • Transformed categories into a smaller set of concepts defined by opposing viewpoints (e.g., biorepository’s responsibility includes or excludes sample ownership, data ownership, and sharing with partners)

Survey Data Analysis

Perceptions on the value of each of the biorepository services were averaged and explanatory information from interviews was included. 

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Survey Data Visualization 

Services were displayed in order by those rated, on average, as most valuable. For comparison, the biorepository's overall satisfaction rating was displayed at the bottom in a contrasting color. 

Bar chart data vizualization of customer satisfaction suvey data
Sample data placemat formatted for printing large uses qualitative and quantitative customer data to explain customer satisfaction.

Transforming Findings into Actionable Solutions

I led the development of data placemats, including findings for SME’s to review.

Example Findings

  • Respondents believe that the biorepository should be a conduit for sharing collections and their epi and lab data with internal and external researchers.
     

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Example Performance Metrics

  1. Percentage of samples transported from the biorepository annually that maintain their original integrity (viability)

  2. Number of biorepository transactions (withdrawals and deposits) each year

  3. Percentage of collections that are “low value” and “high value” collections as measured by the frequency or size of deposits/withdrawals

  4. Percentage of freezer space used by “low value” and “high value" collections.

“To ask someone to... package everything, all their SAS code, is a lot...On the other hand, people leave... emails are deleted... So, I do think there is a gap, which is if someone does find specimens useful and interesting, and the critical information that's associated with the metadata would be unavailable, then [samples] become useless. So, we need to be able to figure out a way to make sure that they don't die… and I think it probably is the biorepository’s role.” - Biorepository customer

Real world impact: Expanding services to advance science

  1. Finding
    Customers believe the biorepository should adopt new services to share collections and their data with internal and external researchers.

    Impact
    The strategic plan was informed by these findings. Over time, the biorepository expanded its services to share collections and their data with internal and external researchers. This transformative shift advances science, globally.
     

  2. Finding
    Custodians & advisors would like the biorepository to help programs adopt open-data release policies and informed consent forms allowing for future data use.

    Impact
    The strategic plan was informed by the findings, Over time, the biorepository expanded its services to centralize and manage data associated with collections, ensuring standardization, and accessibility for internal and external researchers. These transformative shifts advances science, globally.

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