Decision Management in Product Development Dr David Ullman

Decision Management in Product Development Dr. David Ullman President Robust Decisions, Inc. www. robustdecisions. com Copyright Robust Decisions Inc. 2003

“Concern for decision support is in its preinfancy and that the commercial world is just beginning to realize the importance of decision support in business and product development” Wayne Collier, analyst for D. H. Brown and Associates Copyright Robust Decisions Inc. 2003

What do these processes have in common? • Acquisition planning • Portfolio management • Product development • Proposal evaluation • Strategic planning • Homeland security • Bad actor identification • Target identification • Courses of Action (COA) decisions • Analysis of Alternatives • Business strategy development Copyright Robust Decisions Inc. 2003

They all require choosing a course of action and committing resources based on information that is: • Incomplete • Uncertain • Evolving from stakeholders or agents who: • Know part of the information • Are distributed in time and location • Represent many different viewpoints, areas of expertise, and organizational functions Copyright Robust Decisions Inc. 2003

The Value of Information DECISION Judgment KNOWLEDGE Behavior MODELS Relationships DATA Copyright Robust Decisions Inc. 2003 Increasing value

Historical View Product Process Decision 1970 s 1980 -90 s 2000 s Product development and business processes are the evolution of information punctuated by decisions. Copyright Robust Decisions Inc. 2003

The goal is to make decisions with: • • • Confidence Stakeholder buy-in Measured expectations Risk awareness Efficient processes Reports, documentation, and reuse Copyright Robust Decisions Inc. 2003

Meeting this goal requires decision management Decision management is a process that ensures stakeholders’ perspectives and their uncertain knowledge and information are effectively used in determining what to do next to make the best possible decisions with measured satisfaction and risk Copyright Robust Decisions Inc. 2003

Symptoms of poor decision management • Projects are late or over budget • “Final” decisions are later revisited • Poor stakeholder buy-in • Decisions made by edict or the most forceful • Expertise is underutilized • Low confidence in decisions • Decisions are not justified, recorded, reused Copyright Robust Decisions Inc. 2003

QFD, other requirements development, and concept generation tools Many decision support systems (dss) really only evaluate Copyright Robust Decisions Inc. 2003

Accord – single window application that TM supports Decision Management Incorporates • Uncertain Info. • Incomplete Info. • Evolving Info. • Distributed teams • Info. fusion • Stakeholder viewpoints • Graphical interface Useful results • Satisfaction • Risk • What to do next Copyright Robust Decisions Inc. 2003

Underlying model • Utility Theory augmented by Bayesian Model • Manages uncertain information from multiple stakeholders • Fuses distributed team information: • Satisfaction from multiple viewpoints • The value of information (risk and what to do next) • Patented algorithms • Easily imbedded in existing information management systems Copyright Robust Decisions Inc. 2003

Criterion 1 Criterion 2 C Best Estimate, Pessimistic, and Optimistic C K Criterion 3 K Belief W 1 Belief W 2 W 3 Weighted Values Sum Individual Satisfaction Copyright Robust Decisions Inc. 2003

Belief Map for qualitative evaluation 1 Criterion Satisfaction 0. 9 . 5 . 8 0. 8 . 9 . 7 0. 7 . 6 0. 6. 5 0. 4 Belief 0. 3 . 4 0. 2 . 3. 2 0. 1 0 0. 5 0. 6 0. 7 0. 8 Knowledge or certainty Copyright Robust Decisions Inc. 2003 0. 9 . 1 1

For qualitative evaluation Delighted Expand/ Contract Scale Lower Limit Disgusted Most Likely Upper Limit Copyright Robust Decisions Inc. 2003

Results (partial display) Satisfaction (expectation)for each alternative from various viewpoints Downside risk displayed as a potential reduction in expectation Copyright Robust Decisions Inc. 2003

Case study, HP Ink. Jet BACKGROUND • An interdepartmental team, developing the next generation color inkjet printer cartridge GOAL • Produce the best quality print and graphics, quickly and inexpensively TASKS • Design the ink delivery system • Select the inks • Revisit the process as the delivery system matures Copyright Robust Decisions Inc. 2003

Case study, HP Ink. Jet (cont. ) CHALLENGES • 15 people on the team, a variety of departments • The best ink must be selected early in the process- a poor decision might result in additional project cycles, or in unacceptable product performance • System design requires optimization of numerous interacting and evolving properties of the ink and delivery components • The nature, meaning, and relative importance of these interactions is not well understood or represented Copyright Robust Decisions Inc. 2003

Case study, HP Ink. Jet (cont. ) PREVIOUS DECISION MAKING METHOD • A series of meetings among the different representative groups • Sometimes are unstructured, and sometimes not NEW APPROACH • Robust Decisions’ training and companion software, Accord, were introduced to the group • Training is based on the book “ 12 Steps to Robust Decisions” • Accord is uniquely suited to teams managing uncertain, incomplete, and conflicting information Copyright Robust Decisions Inc. 2003

Case study, HP Ink. Jet (cont. ) RESULTS • Potential elimination of an ink testing iteration later in the project. Time savings: as much as five months • An estimated 30 -50% increase in decision confidence TEAMS ALSO REPORTED • Increased participant accountability, and process buy-in • Awareness of important issues and areas of disagreement • Consensus, with more certainty and rapidity • Decisions based on shared knowledge, rather than decisions made by a few experts • Better team visualization of individual and group thought processes • Improved alternative and criteria development Copyright Robust Decisions Inc. 2003

Customer results • Decreased time to market through lower risk of design cycle repetition • Increased probability of market success through: • • • Increased decision confidence Managed risk and uncertainty Identified areas for risk mitigation Facilitated team consensus Increased team accountability Captured decisions for reuse • Large organizations behaving like small teams Copyright Robust Decisions Inc. 2003

A free license is available to educational institutions in trade for use feedback. Contact Dr. David Ullman President Robust Decisions, Inc. Corvallis Oregon 541. 758. 5088 www. robustdecisions. com ullman@robustdecisions. com Copyright Robust Decisions Inc. 2003