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Can you make another video to find the Max total cost?

thank youu fo the video!

thanks! this helps a lot :)

thank you so much! this helps me a lot for my course - prescriptive analytics

thank you for this!

Hi Sir. How did you arrive in the all points of the graph?

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This playlist is really helpful. Thank you!

Thank you, I did my homework thanks to your video.

Can you make a video about this policy: A single buyer single vendor supply chain system faces lumpy demand that follows normal distribution with (µ,δ)= (150,30). Holding cost in the buyer and vendor is IDR 7000 /unit/month and IDR 5000/unit/month respectively. Retailing profit in buyer per unit is IDR 30000, while profit per unit in the vendor is IDR 20000. Ordering cost in the buyer when place an order to the vendor is IDR 100000/order. Based on that description, develop a spread sheet-based simulation based on periodic review order(or production) up to R policy in order to minimize the total supply chain cost (total cost of the buyer and vendor).

Can you upload a video about Inventory simulation using Excel (Up to R policy)? A single buyer single vendor supply chain system faces lumpy demand that follows normal distribution with (µ,δ)= (150,30). Holding cost in the buyer and vendor is IDR 7000 /unit/month and IDR 5000/unit/month respectively. Retailing profit in buyer per unit is IDR 30000, while profit per unit in the vendor is IDR 20000. Ordering cost in the buyer when place an order to the vendor is IDR 100000/order. Based on that description, develop a spread sheet-based simulation based on periodic review order(or production) up to R policy in order to minimize the total supply chain cost (total cost of the buyer and vendor).

Thank you for this! 🥳

Thanks for yout video.

Owesome thank you for sharing

Could we download that Excel template?

HOW DO WE COMBINE TREND AND SEASONAL COMPONENTS GRAPHS

Thanks sir for sharing this knowledge, it helps me a lot with my linear optimization problems on college. Greetings from Croatia!

Thank you!

this content is really helpful

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Whats up, Furkan ÖZTANRISEVEN. extremely charming video. thanks. :)

This is what should have been taught in school

0:21 SoftwareDevelopmentServices mediabrand.live

I LOVE IT PLEASE KEEP IT (if people hate on it just keep it they dont boss you around (❤ ω ❤))

Every one has a bad display but.. your display is so fabulous :-P

entertaining display, lets goo =D

I really enjoy playing this game 😁

0:21 SoftwareDevelopmentServices mediabrand.live

MAPE shows how much the model is off by

Risk - Probability of an undesired outcome 1:04 Events and Probabilities Ex. Coin Toss, Rolling a die

1:30 Buying whole and partial shares 2:18 Cumulative # Shares 4:36 Convert into today’s dollars, Time Value of Money 7:47 Using the Discount Rate 8:43 What the difference means

0:00 CountIf 1:08 Cost Per Unit (Pay for supplier, transportation, logistics) 1:45 Fixed Cost per Order Objective + Minimize Total Cost 3:30 Calculating for variable cost (COGS) 4:15 Order Quantity 5:00 IF(B20>=50,$4.50*.90*B20,$4.50*B20) B20= Order Quantity (How much a company orders)

0:28 Cost per unit Limited Supply for the current Demand 1:35 What is the objective of the model? *+ Minimize Costs* 2:05 What are my decision variables? 3:33 Constraints 3 Supply Constraints 4 Demand Constraints 5:08 SumProduct 7:59 Solve for Optimal Solution

Spreadsheet Model is also known as “What-if Models” 1:18 Fixed Cost - Cost not depending on production Variable Cost - Cost depending on production

0:25 Sample Dataset • 5 types of coke means 5 bins

0:48 Percent Change (% change) (2011Sales - 2010 Sales) 2:48 Sorting Data Highlight the data Hit "Sort and Filter" 6:45 Filter 8:57 Conditional Formatting 11:20 Data Bars

*Types of Data* 0:23 Population = All the elements of interest (All companies in the USA) Sample = A subset of the population (Ex. Energy Sector) 1:56 Quantitative Data = You can do + or - or x or / on it Categorical Data = Qualitative data = No Arithmetic 2:50 Cross-Sectional Data Time-Series Data Ex. Dow Jones value over time _in years_

Descriptive Data utilizes *Past Data* 0:55 Data = Facts and Figures 1:17 Variable = quantity of interest that can take on different values 1:42 Random Variable cannot be known 100% certain Dow Jones Industrial Index ex. (1:51) 3:00 Variables (change with time) 3:30 Observation

12:22 *Big Data* (1) Volume (Terabites or Gigabites) (2) Velocity (speed, capture in real time. Ex. Tweets on Twitter) (3) Variety (PDF's, Videos, Images, etc.) (4) Veracity (Encryption, cybersecurity) * Big Data requires large storage, processing, working format, and security 14:42 *Business Analytics in practice* 15:01 Complexity vs Competitive Advantage 16:00 *Advanced Analytics* includes Predictive and Prescriptive analytics 17:00 Human Resources- Finding the right people to hire 17:28 Marketing- Consumer Behavior, Communicating value to customers 18:28 Healthcare- Organizing patients, schedules, layout of hospital 19:32 Supply Chain Management- Transportation, Waiting Periods, 19:52 Government- Outliers, Focus Groups, Parameters 20:45 Sports Analytics *Better Allocate Resources* *Cultivate Success*

0:16 *Three Developments have led to the growth in the use of analytical methods* 2:07 *The most important thing is making better decisions* (1) Strategic Decisions are made by business owners about higher level, overall goals (2) Tactical Decisions are made by midlevel management (3) Operational Decisions are made by managers regarding day-to-day operations *The Decision Making Process* (4:06) 1. Identify and define the Problem (we love solving problems) 2. Determine the criteria to evaluate the solutions (to avoid bias) 3. Determine the set of alternatives 4. Evaluate the alternatives 5. Choose an alternative *Business Analytics Defined* (5:48) - The Scientific process of transforming data into insight for making better decisions - Used for data-driven, fact based, more objective decisions + Create insight --> + Forecast the future --> +Help quantify/predict risk *A Categorization of Analytical Models* (7:04) (1) Descriptive Analytics (2) Predictive Analytics (3) Prescriptive Analytics *Descriptive Analytics* (7:54) *Data Dashbords* (8:47) KPI = Key Performance Indicator (Check your car engine for oil warning or fuel tank fill) *Prescriptive Analytics* (10:48) - Relies on *rule-based models* to indicate the *best* course of action to take