Introduction Of Decision Science

1. Decision Science
Sem-III (302)

2. HELLO!
I am Dr. Dhananjay Mandlik
I am here because I love
to do new experiment with new
technology
You can find me at 100djay@gmail.com
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3. Unit – I :
1.2 Assignment Models:
Concept, Flood’s Technique/
Hungarian Method,
applications including
restricted & multiple
assignments.
1.1 Introduction:
Importance of Decision
Sciences
Role of quantitative
techniques in decision
making.
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1.3 Transportation Models:
Concept, Formulation,
Problem types: Balanced,
unbalanced, Minimization,
Maximization, Basic initial
solution using North West
Corner, Least Cost & VAM,
Optimal Solution using MODI.

4. “ Now a day Data Management is
very important features of
every organization. Data
Management helps business
leaders to make decisions
based on facts, statistical
numbers and trends.
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5. What is Decision Making?
▸ Decision Making is nothing an integrated application
of mathematics and technology to solve real life
business problems. It involves systematic and
scientific analysis, visualization of extract insights
based on the calculation of clearly defined business
problems.
▸ Decision analysis provide the help to make decision
under the conditions of uncertainty. It trends the
decision maker in the area of costs optimization,
probabilities, quality, values and customer interest,
based on scientific calculation and experience
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6. What is Decision Making?
▸ Decision making is related to planning, organizing,
directing and controlling the functions of decision
maker. Decision making is very much important to
achieve the organizational goals/objectives within
given time and budget.
▸ Decision analyst can easily solve the
multidimensional complex business problem very
easily using various mathematical and probability
techniques
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7. What is Decision Making?
▸ decision Analysists are truly rare than data
scientists. Because decision Analyst artfully play
with business using math, technology and
behavioral science. Decision analysist must be good
communicator
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8. Decision Science is the collection of verious quantitative techniques used for decision-
making at the various levels in the organization. There are verious application of decision
science in the area of linear programming problem, cost optimization, transpotation
problem, assignment problem, graph theory and probability.
Decision Science includes decision analysis, risk analysis, cost-benefit, cost-
effectiveness analysis, simulation modelling and behavioural decision theory. It also
provide a unique framework to make decision at various circumstances.
It is a collaborative approach which involve mathematical formulae, business tactics,
technological applications and behavioral approach which help senior management to
make data driven decisions.
Decision Science is
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