Operation Data Analysis Hints and Guidelines EGN 5621 Enterprise Systems Collaboration (Professional MSEM) Fall, 2012

Tools to Analyze 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 2

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 3

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 4

Using Queries to Analyze Data Queries contain 2 basic elements: Key Figures, KPI Dimensions. Margins as a function of time Sales by country 5

An Example Dimensions Dimensions Measures At the heart of a 6

Elements of an Info Cube Key figures Dimensions 7

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 8

How 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) 9

Exploring Data

Plant A: An overview 11

Plant B : an Overview 12

Plant C an Overview 13

Trying to Maintain Stocks for All Products 14

Large Variations in Sales per Step 15

Manipulating Graphs

Key Figure or KPI Y-dimension 17

Graph type: Scattered Bars 18

Graph Type: Scattered Lines 19

Graph Type: Lines 20

Graph Type: 3D Bars 21 21

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 23 23

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 24 24

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 25 25

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. 26 26

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? 27 27

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 28 28