Career pathway and few proposed projects

My career pathway, roadmap for future and few research proposed projects

1. Work experience and
projects
SENIOR LEADER
NAVEEN VENKATESH

2. My Journey
Phase 5 (2021-)
Improved planning using advanced analytics
with PBI, Datalake, GenAI know-how to help
with data based valuable decision making
My IDP (+5yrs)
Deliver business value
Fond of Numbers
Phase 1 (-2008)
Bachelors in Elx & Comm
Projects on Quick ROI RFID project
Phase 2 (2013-15)
Phase 3 (2013-15)
Masters in Business Administration (NSW, Australia)
Interned with Woolworths, Australia(Qlik/Tableau);
CrimsonLogic, SEA (Single window)
Phase 4 (2015-2021)
Senior Business Analysis leader
Planned demand supply of high spend semicon, PCBs, Displays
etc. (>$1Bn)
Transformation projects cross-functions. Eg: Tariffs etc.
Customer facing revenue generation trials
Asst. Program manager (Saved Octroi/EXIM/SCOMET)
Way forward
GROW

3. Geography covered in my journey
Worked with various customers, suppliers, stakeholders spread across the globe
Team diversity
Customer, Supplier diversity

4. Two alternate ways of Demand
forecasting
2024

5. Alternative one: SFDC Sales opportunity data

6. Alternative two: Sales Revenue Forecasting using macro factors
Features
•Predictions are run for all the Product Line and Country/Region/Sub_Region combinations
•Dependent variable (Variable to be predicted at quarterly level)–Invoice_Value (Product_Line 6 nos,
Country, Region, upto Sub-region level) - This is converted to weekly/quarterly using divisions
•Independent variables – Product_Line,Country,Region, Sub_Region, Quarter_End_Date, Combinationof
macro-economic indicators like –
•Real GDP/Nominal GDP(Gross Domestic Product), US$
•Real NIA Imports/Exports of Goods & Non-Factor Services, US$
•Consumer Price Index
•Real Government/Private Consumption, US$
•Real Inventory Investment, US$
•Interest Rate: Long Term/Short Term
•Exchange Rate Index, Period Average (LCU per US$)
•Real Fixed Investment, US$
•Index - Retail Sales- Real (Volume)/Index - Retail Sales- Nominal (SA - Value)
•Wholesale-Producer Price Index, US$ basis
•Industrial Production Index

7. Business
Inventory planning
using data with different planning policies - Aself-analytical tool!
Optimization & Data Analytics
Input data
•Historical Data
•Suppliers Data
Safety Stock
(SS)Policy
•SS_Upper_Limit
•SS_Lower_Limit
•Service Level %
•…
Safety Stock - Analytics Engine OUTPUT:
NOTE: Only three steps, self-analytics tool
PBI views:
csv in Google storage:
Improve Policy Iteratively

8. Best Practices - Computation Optimization
Analysis Best Practice
Robustness
Scalability
Speed
Maintenance
Extension
Greener
Material Determination
Engine optimization
Computation Reduction up to
50%
+90 min => 45 min (TIME)
219 DBU => 109 DBU (Max Computation Power)
48.18 $ => 23.98 $
($ per single analysis)
2505.36 $ => 1246.96 $
($ per year – 52 weeks)
"FAST, Money Efficient, Robust, Easy
Maintenance, Easy to use" - solution

9. SI&OP idea shared via Lunch n Learn:
Data based Scenario planning
2024

10. Demand planning: Impact of Iran-Israel war study
Critical Oil route
Iran – Israel war
Posses risk on Persian Gulf Ware
routes
Oil supply could decrease
•Logistics delays
•Lesser containers needs proactive forecasting
•Risk build process could be frequently, data needed for
quick decisions should be sought with least turn-around
times
•Which Zebra products are sold more and are sold less
during War
•Impact:
•Missed Sales Opportunities
•Increased Operational costs
•Customer dissatisfactionMetric Explanation WeightFormulae
1Ending Inventory Start with the inventory you had at the beginning of the period, add any new purchases, and subtract the cost of goods sold16.7%
2Key constraint utilizationMeasure how much of the available capacity of the key constraint is actually being used, expressed as a percentage16.7%
3Margin % Indicates what portion of revenue is retained as profit after accounting for the cost of goods sold16.7%
4On time to requestThis percentage shows the reliability of the company’s delivery performance16.7%
5Revenue Simply multiply the number of units sold by the price at which they were sold16.7%
6Revenue at risk Estimate the potential revenue and multiply it by the probability of the risk event occurring. This provides a quantifiable measure of the revenue that could be at risk.16.7%












Here’s why each metric is important:
Ending Inventory
Key Constraint Utilization
Calculate the Impact for this
scenario quickly

11. Demand planning: Impact of Fed rate changes
Fed rate changes
Could mean:
CapEx might increase with few
Zebra customers
Large order opportunities with
possible customers
Opportunities
•Increase in CapEx could enable more Sales not
foreseen – simulations and impact studies
•Large Order Impact:
•Key constraint utilization
•Supply chain disruptions
•Labor shortagesMetric Explanation WeightFormulae
1Ending Inventory Start with the inventory you had at the beginning of the period, add any new purchases, and subtract the cost of goods sold16.7%
2Key constraint utilizationMeasure how much of the available capacity of the key constraint is actually being used, expressed as a percentage16.7%
3Margin % Indicates what portion of revenue is retained as profit after accounting for the cost of goods sold16.7%
4On time to requestThis percentage shows the reliability of the company’s delivery performance16.7%
5Revenue Simply multiply the number of units sold by the price at which they were sold16.7%
6Revenue at risk Estimate the potential revenue and multiply it by the probability of the risk event occurring. This provides a quantifiable measure of the revenue that could be at risk.16.7%












Here’s why each metric is important:
Ending Inventory
Key Constraint Utilization
Calculate the Impact for this
scenario quickly