2019 May Course

May 7 - 9, 2019

LOCATION:
The Williamsburg Lodge
Colonial Williamsburg, Virginia

COURSE FEE: $1,975

Registration fee includes:

  • Food and beverage refreshments and lunch each day
  • A group dinner on Tuesday and Wednesday evenings
  • Printed manuals of slides and
    software exercises
  • A 3-month free trial of the IFPrograms®Professional software
  • Complimentary IFP webinar - you can choose to attend
    an upcoming presentation or download a past recording
  • A copy of our latest books:

    - Readings in Advertising Claims Substantiation
    - Tools and Applications of Sensory and Consumer Science
    - Thurstonian Models: Categorical Decision Making in the Presence of Noise

Register 2 or more from the same company, at the same time, and receive a 20% discount on the 2nd registration. (Contact us for larger group rates and for academic discounts). Please contact Susan Longest at mail@ifpress.com before registering for more information.

The instructors for this course will be:

IN THIS NEW COURSE, we will link techniques from quality assurance – control charts, action standards, and quality function deployment (QFD) – with sensory methodology and Drivers of Liking®.

Consumers’ liking or satisfaction with products can be unfolded to sensory
characteristics that are important to them. This information can then feed into a QFD process to ensure product quality.

While reviewing basic sensory testing methodologies involving difference testing, ratings and hedonics, we will address two practical problems, an ingredient change and the development of a new product to appeal to a segment of consumers with an unmet need.

The course is cast in the context of a cookie company with staff similar to the participants. This means that the learning will resonate immediately and can be easily incorporated into the participants’ normal projects.

WHY ATTEND?

  • To consider new concepts that challenge common assumptions and practices.
  • To listen, learn, and interact with experienced leaders and peers from the sensory and consumer science community.
  • To focus on mental enrichment, away from the ever-present demands of the office, and to return refreshed with new ideas.

The topics covered follow. For more details, please see the course brochure and do not hesitate to contact us with any questions. To register, please call (804) 675-2980 or use our on-line registration form. Enrollment is limited.

EXAMPLES

  • Quality assurance in practice: Acceptable and rejectable quality levels, alpha, and beta risks
  • Ingredient change dilemma: Different methodologies lead to different conclusions
  • Review of 15 published experiments confirming scaling theory
  • Resolving the differential performance paradox using Thurstonian ideas

    TOPICS

  • Overview of quality function deployment (QFD), control charts, and action standards
  • Applying quality control ideas to create an optimal internal sensory program
  • Sensory quality assurance
  • Review of discrimination testing methods
  • A reliable approach to estimate the size of sensory differences: The Thurstonian framework
  • Perception variability and a psychological decision process
  • Increasing testing efficiency: The tetrad test (requires 1/3 the sample size of the triangle test)

    GROUP EXERCISES

  • Use the binomial test to establish a difference
  • Estimate values from experimental data: Which of two prototypes is more similar to a reference? Reconcile apparently inconsistent results
  • Predict relative method performances with computer generated simulations

EXAMPLES

  • Confirming the value of using the tetrad method with children
  • Replicated testing: Expected variability from 50 industrial results
  • Applying risk management ideas to a major food company’s sensory program
  • Sensory action standard: Same-different vs. paired preference estimates
  • Linking a trained panel and consumer sensitivities for ice cream testing

    TOPICS

  • A risk management approach to sensory quality assurance
  • Best practices in replicated testing
  • The 5 cornerstones of product testing: alpha, power, sample size, size of the difference, and protocol
  • Establishing a sensory action standard using the same-different method
  • Relating internal panel to consumer data to ensure the consumer relevance of an action standard
  • Using confidence intervals to establish difference or equivalence
  • Consumer relevant confidence: How statistical significance can result in missed opportunities

    GROUP EXERCISES

  • Calculate optimal experiment samples sizes based on study specifications
  • Find the sensory action standard using the same-different method
  • Establish the optimal sample size for a discrimination testing program based on the methodology, alpha, power, and the consumer relevant sensory standard
  • Study the relevance of a difference by comparing experimental results to the sensory standard

EXAMPLES

  • Identifying drivers of consumer acceptability using factor analysis
  • External preference mapping of 10 brands of low fat chocolate chip cookies
  • 27 grocery product category appraisals comparing LSA and internal preference mapping
  • Three issues in the beer market addressed using LSA
  • Blind-branded LSA and determining concept equity vs. product equity

    TOPICS

  • A conceptual framework for new product innovation
  • Unfolding using Landscape Segmentation Analysis® (LSA)
  • Segmentation based on individual ideals and connecting them to demographics
  • LSA vs. factor analysis: The issue of dimensionality
  • LSA vs. internal preference mapping (IPM): Accounting for individual ideals
  • LSA vs. external preference mapping (EPM): Finding a space relevant to the consumer
  • 2D vs. 3D solution: How to choose
  • How to predict new product performance using a preexisting LSA solution
  • Portfolio optimization – finding the best team of products in a portfolio

    GROUP EXERCISES

  • Unfold liking data to generate a sensory space defined by attributes driving liking
  • Study and qualify consumer segmentation
  • Uncover a product category’s drivers of liking
  • Predict prototype locations in a previously generated LSA
  • Find an optimal portfolio by optimizing liking