Management Is Science or an Art - PowerPoint

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Management Science Approach
       Problem Definition
  What is Management Science?
• Scientific approach applied to decision making
• “Mess management”-- Early developer of MS
• “The use of logic and mathematics in such a way
  as to not to interfere with common sense”
   – “The results should look, feel and taste like
     common sense” -- Prominent MS Consultant
• “The use of [mathematical and statistical]
  techniques, mathematical programming,
  modeling, and computer science [to solve
  complex operational and strategic issues]. -- US
       Definition of
    Management Science

• Art of mathematical modeling
• Science of the solution techniques
  for solving mathematical models
• Ability to communicate results
Management Science Objective
• Given a limited amount of personnel,
  resources and material, how do we use
  them most effectively to:
  – Maximize -- Profit, Efficiency
  – Minimize -- Cost, Time
• Management Science is about doing the
  best you can with what you’ve got --
        Management Science
• Linear Programming Models
  Using of scare resources to achieve maximum profits
   when there are constant returns to scale.
     • Steelcase scheduling monthly production desks, cabinets, and
       other office furniture to maximize profit by assigning workers
       and utilizing the steel, wood, and other resources that are
     • Texaco blending various grades of raw crudes to maximize
       profits while meeting production targets.

• Integer Linear Programming Models
  Determining integer quantities (such as people, machines,
   airplanes, etc.) that maximize profits.
     • American Airlines assigning planes, crews, and support
       personnel on a daily basis.
     • McDonald’s assigning workers throughout the day.
      Management Science
• Network Models
  Using specialized linear models to determine routes of
   shortest distance, connections that tie points together
   of minimum length or finding a maximum flow (through
   a series of pipes)
     • UPS scheduling deliveries in a fleet of trucks.
     • United Van Lines determining the least costly route between a
       pickup and delivery point.

• Project Scheduling Models
  Scheduling of the various tasks that make up a project in
    order to minimize the time or cost it takes to complete
    the entire project.
     • William Lyon Homes scheduling the construction of a new tract
       of homes in Orange County.
     • CalTrans supervising the reconstruction of the Golden State
       Freeway after the devastating earthquake in the 1990’s.
        Management Science
• Decision Models
  Making decisions about the best course of action when
   the future is not known with certainty.
     • Fidelity Investments making mutual fund decisions given the
       uncertainty of the company performance, and the markets.
     • The International Olympic Committee making site decisions
       given uncertain weather patterns and changing international

• Inventory Models
  Determining how much of a product to order and when
   to place the order to minimize overall total costs.
     • Macy’s making merchandising decisions for the season.
     • See’s Candies producing goods for their own stores.
           Management Science
•    Queuing Models
    Analyzing the behavior of customer waiting lines to
       determine optimal staffing policies.
       •   Disneyland designing waiting lines and policies for rides at
           the amusement park.
       •   United States Postal Service determining staffing levels
           and type of waiting line at different branch offices.

•    Simulation Models
    Analyzing a variety models whose forms do not meet
       the assumptions or are too complex to be solved by
       other specialized techniques.
       •   United States Army evaluating tactical combat situations.
       •   Conagra Foods evaluating “what-if” situations in their food
           production processes.
       Management Science
         Team Approach
• Most management science models,
  particularly in larger companies are
  developed by “teams” of professionals.
  – Expertise from various specialists is
    integrated into building a good mathematical
    • Engineers, accountants, economists, marketing
      analysts, production personnel, etc. are just some
      of the specialists that can be utilized in the model
      building process.
    Parts of a Management Science

•   Problem Definition
•   Building Mathematical Models
•   Solving/Refining Mathematical Models
•   Communication of Results
  Types of Management Science
      Problem Definitions
• How Do We Get Started?
  – Evaluation of new operations and/or
• Can We Do Better?
  – Ongoing operations may be performing well,
    but perhaps they could improve
• Help!
  – Situations where the company is clearly in
    trouble – “mess management”
           Problem Definition Approach
1.       Observe Operations
     •     Try to view problem from various points of view within the
2.       Ease into complexity
     •     Do a lot of listening; ask simple questions; initially build a simple,
           common sense model that can be made more complex later.
3.       Recognize political realities
     •     Managers will not usually supply evidence showing his/her
           failures – there can be a “blame game” for failures.
4.       Decide what is really wanted -- the goal/objective
     •     Managers can have a fuzzy or a definitive idea as to the objective;
           this can be at odds with the global objective.
5.       Identify constraints
     •     With input from various sources seek the factors that will limit the
           firm’s ultimate objective; include only relevant factors.
6.       Seek continuous feedback
     •     The management science team must solve the “right” problem;
           seek, share and document frequent input with decision makers.
 Updating The Problem Definition
• Once the problem has been defined it is
  time for the modeling/solution phase.
• But results from this phase may result in
  a re-evaluation of the problem definition.
  – The model may be “infeasible”
  – The model may not provide “good enough
  – The model may highlight heretofore
    unobserved or unanticipated constraints
  – The model may result in a set of optimal or at
    least “good” possible courses of action
    allowing the decision maker to look at
    secondary objectives.
• Management science seeks to do the best
  you can with what you’ve got.
• It involves modeling, solution
  approaches, and communication.
• The process consists of:
  – Problem definition
  – Mathematical modeling
  – Solving the mathematical model
  – Communication/implementation of results.
• Approaches/pitfalls associated with the
  problem definition step.

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