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Operations Management: presentation

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Cindy LM

on 6 October 2015

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Transcript of Operations Management: presentation

Operations management
Case study

Company overview
Discussion Questions
3. Justify the use of the weighting system used for evaluating managers for annual bonuses.

Thank you for your attention!
Hard Rock
Concept of “experience economy”
The heart of the sales forecasting system -> POS (Point-of-sale)
Examination for variances between forecast and actual sales
Describe three
different forecasting
applications at
Hard Rock Cafe
Application of statistics -> menu planning

Multiple regression
(regression model with more than one variable): managers can compute the impact on demand of certain menu items if the price of one item is changed.

Event planning (group events and meetings)
Concerts (bands, dates)

Results of NGT
Bonuses are controlled by a system of weights varying depending on the sells averages in the last three years.
Weights give more emphasis in recent periods of time, making forecasting more accurate as they reflect the current situation of the company.
Sales variables
Competitors’ prices
Marketing and advertising investment
Seasonality periods (like holidays)
Events per period (for example: concerts)
Economic and legal variables, such as a recession or tax increases
Sales and promotions
Name three
other areas in which
you think Hard Rock could use
forecasting models.
ŷ= a + bx

ŷ = dependent variable (guest count)
a= y-axis intercept
b=slope of the regression line (rate of change in y for given changes in x)
x=independent variable (advertising expenses)
Excel graph
Cintya López
Andrea Herrera
Alberto Zorrilla
Marcelo Salinas

Forecasting at Hard Rock Cafe
Chain of theme restaurants founded in 1971
191 locations in 59 countries today -> Demand for better forecasting.

145 cafes
21 hotels
10 casinos

Long-term: capacity plan,
Intermediate-term: leather goods and some food items (beef, chicken, pork)
Short-term: monthly sales

Evaluation of managers through bonuses according to their 3 previous years.

y = dependent variable
a = constant
x1 & x2 = values of two independent variables
b1 & b2 = coefficients for the two independent variables
2. What is the role of
the POS system in
forecasting at Hard
Weights can be used to place more emphasis on recent values.
This makes forecasting techniques more responsive to changes because more recent periods may be more heavily weighted.

Weighted moving averages
4. Name some variables
besides those mentioned in the
case that could be used
as good
predictors of daily sales
in each cafe.
5. At Hard Rock’s Moscow
restaurant, the manager is trying
to evaluate how a new advertising
campaign affects guest counts.

Using data for
the past 10 months, develop a least
squares regression relationship
and then forecast the
expected guest count when
is $65,000
This method results in a straight line that minimizes the sum of the squares of the vertical differences or deviations from the line to each of the actual observations.
ŷ= a + bx

ŷ= 8.3363029 + 0.79955457 x

For an investment of $65,000 in advertising, the guest count would be of:
ŷ (65)= 8.3363029 + 0.79955457 (65) = 60.30735

Answer= 60,308 guest counts

System for managing the sales of
retail goods
Efficient business, low costs, better customer service.
Data is analyzed to understand past
performances (transactions).
Provides more stable and consistent patterns
Identify changes in trends over time
Historical data helps forecast
future needs

POS (Point-of-sale)
Full transcript