Inventory Forecasting Reminds Me of the Chicken and Egg

Scientific systems exist today to help manage both sides of the equation; demand and supply, build versus buy, etc. Let’s start with basic inventory management and keeping stock levels accurate. 
Here is where we go to Inventory Optimization, Forecasting and Families and Groupings systems.  Why were they developed and how do they work?  Why do they exist?

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Supply Chain: A supply chain is a linked set of resources and processes beginning with sourcing of raw material, extending through to the delivery of end items to the final customer. This isn't just chicken feed, it is the life source of your business. A supply chain is comprised of vendors, manufacturing facilities, logistics providers, internal distribution centers, distributors, wholesalers and all other entities that lead up to final customer acceptance.
Inventory Forecasting:
Forecasting is a process enabling businesses to estimate expected sales (demand) in the future. forecasting takes into consideration four main variables:

• Demand - the overall market demand for a product.
• Supply - the overall quantity of a product in the market.
• Product Characteristics - features and functions influencing the customer's demand for your product.
• Competitive Environment - the actions of all businesses striving to create demand and satisfy demand with a given product.

There are four basic types of forecasting methods, used in combination, for creating a forecast:

• Qualitative - speculative in nature, this method relies on a person's opinions of a market.
• Casual - assumptive in nature, this method assumes that demand is strong based on specific environmental and market factors.
• Quantitative - also known as "Time Series," scientific in nature, this method uses historical patterns as an indicator to forecast future demand.
• Simulation - a combination of casual and "Time Series," this method aims to imitate consumer behavior in a given set of circumstances.

Extending Optimization: Inventory Families & Groupings:
Families & Groupings allows classification and grouping stock items into "collections" for the purpose of optimizing your inventory through better analysis and forecasting. This enables you to forecast and analyze data at a higher level than the stock code level defined in Manual Forecasting. By combining products which have sales and procurement relationships, other than product categorical mix-based, to collate their data to product working forecasts
Families and Groupings not only allows you to analyze and forecast stock items at an individual level (as is possible using the Manual Forecasting, Batch Forecasting, Approve Draft Forecasts, Demand History Maintenance and Pareto Analysis programs), it also allows you to model forecasts at an aggregated level. This is achieved by creating collections (i.e. a group or a family) of stock codes or warehouses you classify in a way which is meaningful to your business. Once created, a collection is treated as a single item against which comparisons and forecasts can be made. Policy is set according to the collection defined which in turn defines how investment (stock holding) and service level are balanced for each item. A collection stipulates prerequisites to aggregated Families and Groupings forecasting.
Forecasting, apart from the stock code level, is advantageous particularly when considering product mixes do not, necessarily, always fall within definable data relationships. However Families and Groupings extend those relationships to include virtually any combination of item mixes into forecast collections.
Managing unpredictable demand with Optimized Inventory
Whitepaper: ERP Inventory Management
The next level, Inventory Optimization aggregates supply chain and service levels into a feature rich set of tools for managing and delivering goods at each level of demand and supply planning.

• Modeling of different ‘what-if’ policy scenarios to arrive at the best mix of service and inventory investment
• Clarity and objective measures of when stock is ‘right’ (supply and demand are in balance)
• Optimization at the SKU-Loc (stock keeping unit – location) level which can be aggregated up to higher levels
• Forecasts at regional or territory level by consolidating warehouses for logistical or supply chain purposes
• Improves stock turns and service levels
• Reduces waste in your supply chain
• Highlights where problems are – stock-outages, over- or under-stocking
• Improves your ability to manage demand

Summary:
On one hand you have demand for the eggs; on the other the factory capacity and chickens. When do we know how many eggs are needed and by when to satisfy demand through the supply chain? We don’t want to over buy (costs) or over produce (shelf-life) or overload the supply chain and pay more or lose the yield?
Some things to think about:

• If we keep the lights on, the chickens make more eggs. (XL, L, M and S)
• Can quality be maintained? (time to market, storage, shelf-life)
• How does the supplier/grower maintain chickens & feed (organic or other)?
• Downstream we have consumers and oops, Easter is coming.
• How many eggs can be produced by chickens per a day/week/month?
• How many hours does a chicken stay on the job before they are put out to pasture?

For example:
County Grocery Inc. inventory history shows they serve a neighborhood of about 1500 homes (names & addresses). Each home has on average six to twelve eggs on-hand (1/2 to 1 Dozen). They consume 2.5 dozen eggs each month average. So that is about 3500 dozen per month considering all sizes of eggs sold. Eggs have a shelf-life of between 15 and 60 days depending on storage and transportation.
The Farm Fresh Eggs Company sells eggs exclusively to this grocery store. The sales history for the “egg farm” shows there is an average in-store on-hand quantity for any week of about one hundred dozen or 1200 eggs in their refrigerated storage. Deliveries are once per week.
Predicting the average over the last 2-3 years, The Farm Fresh Eggs Company knows:

• How many chickens produce how many eggs
• How many are ship-able quality
• How many on average are of which size
• How many are scrap
• How many cartons and shipping containers
• Costs per-egg-produced
• Sales volume required to sustain…

Using history of sales and use we can see how many “were” sold, used and prior demands against prior stock levels. With this information we can also see “into the future” by using these same numbers to predict what we will need and when to order or produce.
Okay, I'm not sure about you, but my head is starting to swim. If you can't get your mind wrapped around sensible meanings you can manage, where can you go from here?