8/12/2019 Syllabus 105

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Syllabus 105

Number of clips 3

Clip 1:

Slide 1-7 (show only slide 4) Contents are mainly Slide 6 & Slide 7

Key Message: The Benefits of learning Data

Analysis and the learning objective for today.

Story:

Definition of Data AnalysisSlide 6

Data analysis is the process of derivinginsights from gathered data

Modeling is the process of makingprojections about the organisations future

processes

BenefitsSlide 6

Extracts useful results from raw data toform conclusions

Discovers relationships and trends withinand between data to back up issues and

ideas

Amplifies points of interest in data forfuture use

Learning objective for the day - Slide 7 Data analysis in a clear, logical and creative

way

Different chart types to present trends andrelationships

Data models including market sizing,financial modeling, capacity modeling

Data modeling methodologyHow we can integrate it into our case analysis

Slide 7

Right types of model for the right type ofsituations

Slide 8-9 (show only slide 8,9) Key Message: How past lessons (103, 104) on

hypothesis checking, data gathering leads to today

lesson where we will now learn how to analyze

these data.

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Slide 10-13 (show only slide 10,11,13) Key Message: Explain the Data Analysis

Methodology

Story:

The 3 methodology of data analysis is model,

interpret and chart.

Modelexplain the 6 steps Model Methodology

slide 13 briefly.

First Determine the objectives behind datamodeling

Second Break down key issue into targetcomponents to be included in model

The 6 steps could be summarized to the keyword.

1. Determine Objective2. Breakdown key issue3. Select key component4. Research for Figures5. List Assumptions6. Build Best &Worst case Scenarios

Slide 14-18 (we will need 1 example which can be

used to explain the 6 steps Model Methodology)

while having the 6 steps keyword beside the

example to show guide the view how we are going

to dissect the problem, and different slide for the6

steps to showcase how we dissect the problem.

But remove the words and explanation from theslide, verbally explain it instead.)

Key Message: Explain the 6 steps Model

Methodology with an example.

Example to use.

Organisation ABC wants to estimate key cost

drivers for educational talks and programmes for

for the next 4 years.

1. Determine Objective Cost estimation Revenue projection Mapping capacity requirements

2. Breakdown key issue

3. Select key component-Determine where each key issues falls under

Key cost drivers

Manpower

Referencematerials

Programme

Logistics

Communications

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the Relevant vs Significant Axis.

-Explain the meaning & difference between

relevance & Significance

Relevant

- Components that are specifically related to our

clients key issue

Significant

-Components which are important in making up

our clients key issue

-Prioritise items which takes up the biggest

component in key issue

4. Research for Figures-Slide 17 right example, while verbally explain

using the flowchart on the left.

5. List Assumptions-Slide 18

6. Build Best &Worst case Scenariosslide 18

Clip 2:

Slide 19-24 (we will need 1 example which can be

used to explain the concept of logical, clear and

iterative data)

Key Message: Explain how to make a good

analysis.

Explain the two data types: Numerical andTextual

Numerical

Summarise using measures of centraltendency and dispersion Look at the common values in a list of data

items: the mean, median and mode

Measure the range of data Explore connections between factors Look for outliers

Textual

Group comments into themes orcategories

Identify themes and patterns Explain the concept of Logical, Clear, iterative

using an example

Logical - integrates quantitative and qualitative

knowledge and its characteristics are:

Uncover implicit assumptions andimplications rooted in the data

Assess the answer: does it clear sense ordoes it imply something ridiculous?

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Ensure that your key assumptions areexplicit and have been tested for

reasonableness and sensitivity (i.e. your

assumptions are reasonable and realistic.

Even if real figures are off the mark, it

won't change the answers drastically)

Clear - backs up recommendations and its

characteristics are:

Sees the big picture and provides insightinto "why" and "what does it mean" for

the problem

Design analyses that rely on accessibledata rather than aiming for the "perfect"

analysis

Avoid analysing confidential information,scattered data across too many different

players and obscured data/metric which

no one has recorded thus far Outputs should be simple to present and

understand, yet be a good approximation

of reality

Iterative and refines information breakdown

when there is new data

Try to triangulate answer with results viaother methods (e.g benchmarks, previous

estimates, top-down vs bottom-up

approaches ) if possible

Not just about a bunch of analytical tools(DCF, NPV, Process mapping, Scale curves,regressions, TSR, game theory, etc)

Avoid pure number crunching andcalculations

Avoid being "scientific" rigorousClip 3:

Slide 25-30 (show multiple types of charts but all

fall under the category of quantitative, conceptual,

textual)

Key Message: Showcase different kind of

presentation method to inspire the viewers.

Slide 34-45 (show only slide 34) Key Message: Briefly explain how to analyze the 3

common models: Market sizing, financial

projections, Capacity Requirements.

Slide 47 (show only slide 47) Key Message: Conclusion

Learned about

Data analysis in a clear, logical and creativeway

Different chart types to present trends andrelationships

Data models including market sizing,financial modeling, capacity modeling

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Data modeling methodologyIntegrated

Right types of model for the right type ofsituations