Using Marketing in High Technology Product & Service Development Dr. Alan Carsrud FIU Center for Global Entrepreneurship and Innovation.

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Presentation transcript:

Using Marketing in High Technology Product & Service Development Dr. Alan Carsrud FIU Center for Global Entrepreneurship and Innovation

Overview of the Stage Gate Process Stage V: Productionand Market Launch Adapted from the Stage Gate process by Robert J. Cooper Stage IV: Testingand ValidationStage III:DevelopmentStage II: DetailedInvestigationStage I: PreliminaryInvestigation Idea Generation

Detailed Investigation Adapted from the Stage Gate process by Robert J. Cooper Stage II: DetailedInvestigationStage I: PreliminaryInvestigation Idea Generation

Key Activities Market Analysis Competitive Analysis User Needs & Wants Study Customer Wish List: Product Rqmts Technical Assessment: Translation Technically Feasible Concept(s) Mfg Costs/ Production Needs Project Plan: Development, Test, Marketing & Production Financial Justification: Financial, Risk, Business Justification Product Definition: Target Market, Concept, Position & Benefits Requirements & Specs Expected Sales Financial Analysis Concept Test: Purchase Intent

Identify User Needs & Wants Gather raw data –Interviews –Focus Groups –Observation Interpret raw data –Affinity Diagram –Needs Statements Organize needs & establish importance –Surveys –Conjoint Analysis Karl T. Ulrich and Steven D. Eppinger 2nd Edition, Irwin McGraw-Hill, 2000.

Traditional Demographic Segmentation Non-Traditional Segmentation Gather Raw Data- Interview Segmentation Mark Martin, Acting Assistant Professor Stanford University, 2000

* Per major market segment How many interviews are needed? *

Focus Groups Two hours of one-on-one interviews = Two-hour focus group * Focus groups can cause “group-think” –Participants agree with a question in focus group –Participants give opposing answers when asked individually * Silver & Thompson 1991

Interviews vs. Focus Groups From: Griffin, Abbie and John R. Hauser. “The Voice of the Customer”, Marketing Science. vol. 12, no. 1, Winter One-on-One Interviews (1 hour) Focus Groups (2 hours) Percent of Needs Identified Number of Respondents or Groups

Interpret Raw Data : Screwdrivers Example

Affinity Diagram (a.k.a. KJ diagram) Organizes subjective information Example: Group the following CR’s “ease of handling”“portability” “number readability”“dose metering” “load handling”“ease of use”

Five Guidelines for Writing Needs Statements

Things to Remember Capture “What, Not How” Collect visual, verbal, and textual data Props will stimulate customer responses Interviews are more efficient than focus groups Interview all stakeholders and lead users Develop an organized list of need statements Look for latent needs Survey to quantify tradeoffs

Translating CR’s into Technical Specs Customer Needs Good image Easy to transport Keeps present. flowing Image visible in bad conditions Minimizes unplanned interruptions Design makes the product attractive Device sets up quickly Works well for short present. Engineering Metrics Brightness Weight Dimensions (girth + width) Time/Tasks required to start present. Distortion Distance from presenter Time to insert/pull-out slide Attractive product Portable Slide Projector Example Mark Martin, 2000

Phase I - Portable Slide Projector

Phase II - Portable Slide Projector % Worth of components

Concept Development Funnel

Clarify the Problem Generate Product Concepts Select Product Concept Concept Screening Concept Scoring Search Externally Search Internally Existing Concepts New Concepts Reflect on the Process Continous Improvement Karl T. Ulrich and Steven D. Eppinger 2nd Edition, Irwin McGraw-Hill, 2000.

Concept Generation Exercise: Vegetable Peelers

Vegetable Peeler Exercise: Voice of the Customer "Carrots and potatoes are very different." "I cut myself with this one." "I just leave the skin on." "I'm left-handed. I use a knife." "This one is fast, but it takes a lot off." "How do you peel a squash?" "Here's a rusty one."

Clarify the Problem: Key Customer Needs 1.The peeler can be used for a variety of produce. 2.The peeler can be used ambidextrously. 3.The peeler creates minimal waste. 4.The peeler saves time. 5.The peeler is durable. 6.The peeler is easy to clean. 7.The peeler is safe to use and store. 8.The peeler is comfortable to use. 9.The peeler stays sharp or can be easily sharpened.

External Search Lead Users –Benefit from improvement –Innovation source Benchmarking –Competitive products Experts –Technical experts –Experienced customers Patents –Search related inventions Literature –Technical journals –Trade literature

Internal Search Suspend judgment Generate a lot of ideas Infeasible ideas are welcome Use graphical and physical media Make analogies Use related stimuli Use unrelated stimuli Set quantitative goals Trade ideas in a group

Concept Selection Process Prepare the Matrix –Criteria –Reference Concept –Weightings Rate Concepts –Scale (+ – 0) or (1–5) –Compare to Reference Concept or Values Rank Concepts –Sum Weighted Scores Combine and Improve –Remove Bad Features –Combine Good Qualities Select Best Concept –May Be More than One or None –Beware of Average Concepts

Example: Concept Screening

Example: Concept Scoring

Things to Remember The goal of concept selection is not to Select the best concept The goal of concept selection is to Develop the best concept So remember to combine and refine the concepts to develop better ones!

Beware of the best "average" product Perform concept selection for each different customer group and compare results Check sensitivity of selection to the importance weightings and ratings May want to use all of detailed requirements in final stages of selection Note features which can be applied to other concepts Things to Remember

Concept Testing Define the purpose of the test Choose a survey population Choose a survey format Communicate the concept Measure customer response Interpret the results Reflect on the results and the process

Concept Testing is Used for... Go/no-go decisions What market to be in Selecting among alternative concepts Confirming concept selection decision Benchmarking Soliciting improvement ideas Forecasting demand Ready to launch?

Concept Testing Example: emPower Electric Scooter

Scooter Example Purpose of concept test: –What market to be in? Sample population: –College students who live 1-3 miles from campus –Factory transportation Survey format: –Face-to-face interviews

Communicating the Concept Verbal description Sketch Photograph or rendering Storyboard Video Simulation Interactive multimedia Physical appearance model Working prototype

Verbal Description The product is a lightweight electric scooter that can be easily folded and taken with you inside a building or on public transportation. The scooter weighs about 25 pounds. It travels at speeds of up to 15 miles per hour and can go about 12 miles on a single charge. The scooter can be recharged in about two hours from a standard electric outlet. The scooter is easy to ride and has simple controls — just an accelerator button and a brake.

Sketch

Rendering

Storyboard

3D Solid CAD Model

Appearance Model

Working Prototype

Beta Prototype

Survey Format PART 1, Qualification –How far do you live from campus? –How do you currently get to campus from home? –How do you currently get around campus? PART 2, Product Description –

Survey Format PART 3, Purchase Intent –If the product were priced according to your expectations, how likely would you be to purchase the scooter within the next year? I would definitely not purchase the scooter. I might or might not purchase the scooter. I would definitely purchase the scooter. I would probably not purchase the scooter. I would probably purchase the scooter. “top box”“second box”

Survey Format PART 4, Comments –What would you expect the price of the scooter to be? –What concerns do you have about the product concept? –Can you make any suggestions for improving the product concept?

Interpreting the Results: Forecasting Sales Q = N x A x P Q= sales (annual) N= number of (annual) purchases A= awareness x availability (fractions) P= probability of purchase (surveyed) = C def x F def + C prob x F prob “second box”“top box”

Forecasting Example: College Student Market N = off-campus grad students (200,000) A = 0.2 (realistic) to 0.8 (every bike shop) P = 0.4 x top-box x second-box Q = 200,000 x 0.20 x [0.4 x x 0.2] = 6400 units/yr Price point $795 Revenue = 5 million dollars

Forecasting Example: Factory Transport Market N = current bicycle and scooter sales to factories (150,000) A = 0.25 (single distributor’s share) P = 0.4 x top-box x second-box Q = 150,000 x 0.25 x [0.4 x x 0.2] = 6000 units/yr Price point $1500 Revenue = 9 million dollars

emPower’s Market Decision: Factory Transportation

Sources of Forecast Error Quality of Concept Description Quality of Testing Method –Concept testing v. conjoint analysis Pricing Level of Promotion Word-of-Mouth Effects Competition

Discussion Why do respondents typically overestimate purchase intent? Would they ever underestimate intent? How to use price in surveys? How much does the way the concept is communicated matter? –When shouldn’t a prototype model be shown? How does early (qualitative) concept testing differ from later (quantitative) testing?

How to get to the next stage Similar gate process but more detailed than stage 1 –Does it fit with the corporate strategy? –Does it offer a competitive advantage? –Is the market attractive? –Is it technically feasible? –Is it financially attractive? Critical evaluation before Stage 3 - the “money stage”

Sample Gate 3 Business Strategy Fit Congruence (fit with company strategy) Impact (financial and strategic impact) Product & Competitive Advantage Offers unique benefit to users Meets user needs better than competitive product Provides good value for money to customer Market Attractiveness Market size Market growth rate Competitive situation Weight Score

Sample Gate 3 Strategic Leverage Leverages marketing, distribution & selling resources Leverages technological expertise & resources Leverages operational capabilities & facilities Technical Feasibility Size of technical gap (small) Technical complexity of project (low) Technical uncertainty of outcome (low) Risk v. Return Expected profitability (NPV) Percent return (IRR% or ROI%) Payback period (years) Certainty of estimates Low cost and fast to do (low risk) Weight Score