For knight transportation interview

1. Mitigating Demand Volatility Impact
on Long-Term Material Availability
Teradyne - ASU Analytics
Capstone Collaboration

2. 3/1/22 2
Data Description
Summary

3. 3
1. LTF Data – Provides actual and forecasted yearly demand of Instruments for UltraFlex.
Timeline:
Actuals – 2015 to 2021
Forecast – 2015 to 2028
1. Historical Actual Raw (MISC)– per Site, System Type, System or Miscellaneous, Instrument, Part,
Category, Quantity, Date, TeraWK, TeraQTR, Request Date, Demand Source, Sales Order, Line,
Customer Id, Unit Cost, Unit Price, Extended Shipping Cost
Timeline:
Actuals – 2015 to 2022 (till 2022 Q1)
1. Historical Demand Actuals per Site, System Type, System or Miscellaneous, Instrument, Simple
Instrument Name, Category, Quantity, Date, TeraWK, TeraQTR, Year, Sales Order, Segment, End Market
Timeline:
Actuals – 2015 to 2021
1. Marketing Forecast - Utah, DCPM, HexVS, Tomahawk, Mohegan, HSD200, Pool2, DC90, IFLEX,
DC90XP, IFLEX, DC90, MFLEX, DC90XP, MFLEX
Timeline:
Forecast - 2021 to 2032
Data Description

4. 4
Goals &
Limitations
Summary

5. Goals & Limitations
Goals
1. Have a better understanding of orders for parts. For example, what are those parts used for?
Who and where is the most valuable costumers? Are there any seasonality feature can be
found in the order history?
2. How much off the forecast is? How can we make a better forecast?
Limitations
1. Even though we signed the NDA, but they weren’t welling to give us data that might be helpful
2. They didn’t want to share the details of how they did the forecast

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Descriptive
Descriptive Analysis

7. 7
Quantity for each Instrument by Year
Historical Actuals Raw Y2015 - 2022
Most of the
instruments are follow
the same shipment
pattern, except for
DC90 IFLEX and Utah.

8. 8
Quantity for each Instrument by Quarter
Historical Actuals Raw Y2015 - 2022
The second quarter always
has the highest shipment

9. 9
Percentage of Systems Usage by Instrument,
Quarter & Year
Historical Actuals Raw Y2015 - 2021
For all years and
quarters, most of the
Instruments number
contribute to System
usage followed by
MISC and Partial.

10. 10
Quantity for each Demand Source
Historical Actuals Raw Y2015 - 2022
ML is the largest shipment
source for all the years
ML is the largest shipment
source for all the years

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Ratios
Descriptive Analysis

12. 12
Ratio between Quantity and Customers
Historical Actuals Raw Y2015 - 2022
Overall Ratio:
Utah : 4.35
DCPM : 4.58
HexVS : 8.48

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LTF - Long Term
Forecast
Descriptive Analysis

14. 14
Actual Demand Vs Forecast
LTF - Y2015 - 21

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Season Index
Predictive Analysis

16. 16
Season Index
Historical Demand Actuals Data Y2015 - 2021
Let’s say we sell 100 DCPM in Q1. Now we can forecast for Q2 by
doing the following:
100*156% = 156
So we can expect to sell 156 DCPM in Q2

17. 17
Season Index
Historical Demand Actuals Data Y2015 - 2021
The marketing forecast for DCPM in the year 2022 we can
forecasted to sell 2022 Q1 2022 Q2 2022 Q3 2022 Q4
DCPM 279 353 274 217
Sum 1123
Average 281
So our Baseline average is 281
so for Q2 we will sell 281*156% = 438 DCPM

18. 18
Season Index
Historical Demand Actuals Data Y2015 - 2021

19. 19
Quarter Wise Comparison
Historical Demand Actuals Data Y2015 - 2021