Manufacturing game
Pierre-Majorique LÉGER
Jacques ROBERT
Gilbert BABIN
Robert PELLERIN
Bret WAGNER
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Part 2 – Chapter 6
Reporting
Copyright © 2011 HEC Montréal
ERP Simulation Game
OLTP Reporting
with SAP
Procurement management
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Inventory management
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Production execution
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Sales order report
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Sales summary report
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Market report
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Financial statements
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Profit center analysis
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Raw material cost per PO
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Product cost planning
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Liquidity planning
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OLAP Reporting
with SAP and MS
Access
5 styles of business intelligence
Enterprise Reporting – Broadly deployed pixel-perfect report formats for operational reporting and
scorecards/dashboards targeted at information consumers and executives.
Cube Analysis – OLAP slice-and-dice analysis of limited data sets, targeted at managers and others
who need a safe and simple environment for basic data exploration within a limited range of data.
Ad Hoc Query and Analysis – Full investigative query into all data, as well as automated slice anddice OLAP analysis of the entire database – down to the transaction level of detail if necessary. Targeted
at information explorers and power users.
Statistical Analysis and Data Mining – Full mathematical, financial, and statistical treatment of
data for purposes of correlation analysis, trend analysis, financial analysis and projections. Targeted at
the professional information analysts.
Alerting and Report Delivery - Proactive report delivery and alerting to very large populations based
on schedules or event triggers in the database. Targeted at very large user populations of information
consumers, both internal and external to the enterprise.
Source: The 5 Styles of Business Intelligence: Industrial-Strength Business Intelligence, A White Paper Prepared by MicroStrategy, Inc.
Version : August 2011
5 styles of business intelligence
Source: The 5 Styles of Business Intelligence: Industrial-Strength Business Intelligence, A White Paper Prepared by MicroStrategy, Inc.
Version : August 2011
Building an organisation around
analytics
Decisi
ons
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Start with the right
business questions
•
Successful analytic organization must focus on the right
questions, those that help make the right decision and
provide a competitive edge:
•
•
•
•
•
•
•
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Who are the most profitable/desirable customers?
Which clients are we more likely to lose?
What has been sold and where?
What should be our pricing and advertising strategy?
How my markets have evolved through time?
Have we reduced in-process inventories ?
Were there major production disruptions? Why ?
Tools to analyse data
• Tools to analyze data range from simple to
complex
• Reports and graphs
• Advanced statistics forecasting models
• Advanced optimization models and tools
• Having the right people matters
• Having data modeling
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A large quantity of quality data
• All analytic methods feeds on data – in large
quantity and good quality
• Having good data can be turned into a competitive
advantage
• Integrated organizations have a lot of data
available, they must learn to exploit it
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Interpreting data
• Skills are required to create appropriate graphs,
reports, and statistical analysis
• Skills are required to interpret correctly graphs,
reports and statistics
• Skills are required to make the appropriate
decisions from the analytics
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Using queries to analyse the data
Queries contain 2 basic
elements:
(i)Key Figures, KPI
(ii) Dimensions.
Margins as a function of time
Sales by country
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An example
Dimensions
Measures
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Elements of a Info cube
• Key figures
• Dimensions
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Types of Measures
• Additive : it makes sense to sum the measures across all
dimensions
• Quantity sold across Region, Store, Salesperson, Date, Product
…
• semi additive : additive only across certain dimensions
• Quantity on hand is not additive over Date, but it is additive
across Store and Product
• non additive : cannot be summed across any dimensions
• A ratio, a percentage
• A measure that is non additive on one dimension may be
the object of other data aggregations
• Average, Min, Max of quantities on hand over time
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How the DW differs from a
transactional DB
Characteristic
DB
DW
Operation
Real-time, transactional
Decision support, strategic analysis
Model
Entity-Relationship
Star Schema
Redundant data
Designed to avoid
Permitted
Data
Raw data, current
Aggregated, Historical data,
# of users
Many
Few
Update
Immediate
Deferred
Calculated fields
None stored
Many stored
Mental model
Tabular
Hypercube
Queries
Simple, some saved
Complex, many saved
Operations
Read / Write
Read Only
Size
Go (Gigabytes)
To(Terabytes)
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Doing BI with
ERPsim data in
MS Access
How to use
ERPsimData.accdb
• Step 1:
• Download the ACCESS
file ERPsimData.accdb
from the site provided
by your instructor
• Save the file
ERPsimData.accdb on
your hard drive
• You may open it to
check its content
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How to use
ERPsimData.accdb
• Step 2:
• Use Pivot Table in Excel
to analyze data
• Open an Excel file
• In the Excel file, on the
“Data” tab,
click on the “From
Access” button.
• Look for
ERPsimData.accdb on
your hard drive
• Select the query or table
you want to analyze
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How to use
ERPsimData.accdb
• Step 2 (cont’d):
• Select Pivot Table
report
• Select the fields you
want to use in your
report
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Exploring data
Plant A: An overview
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Plant B : an overview
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Plant C an overview
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Trying to maintain stocks for all
products
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Large variations in
sales per step
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Small production runs
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Long production runs
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Manipulating
graphs
Key Figure or KPI Y-dimension
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X (Row) dimension
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Multiple series: Column dimension
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Graph type: scattered bars
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Graph type: scattered lines
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Graph type: lines
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Graph type: 3D bars
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An example
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BI Questions
BI Question 1
• Current assets include
(i) cash
(ii) receivables
(iii) raw material inventory
(iv) finished product inventory
• How well have the teams performed in managing
the current assets over time?
• Hint: Use the financial data
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BI Question 2
• Did the winning team bring their highest margin
product to market first?
• Did they charge a price premium while they were
first to market?
• Can you see the impact of a competitor entering
the market?
• Hint: Use the operational data
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BI Question 3
• One objective of materials management is to make
sure that raw materials are available for production
when needed
• Which company has managed this process well as
shown by having the largest variety of products in
stock?
• Hint: Use inventory data by products over time
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BI Question 4
• Companies may have different strategies for
production management
• Some may prefer long productions to minimize setup
losses, while others may prefer shorter runs to respond
more quickly to market opportunities
• Can you determine what strategies were used by each
team?
• Where there any production disruptions?
• Hint: Use production data over time and products.
Filter for each individual company.
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BI Question 5
• Companies want to maximize sales
• If sales are too high, the price may be too low, and vice
versa
• Can you tell sales is affected by prices?
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BI Question 6
• Who owns the market (as measured by market
share) for each product?
• Hint: Use sales data filtered by product with
drilldown across plant
• Use a stacked area chart
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