Operations and Supply Chain Management (OSCM)

How to develop capabilities to design, produce and deliver products and services in a competitive market.

Start high level: Operating Model (goal) -> Tactically (small goal) -> Practical (what you do)

The Six Primary Processes of Supply Chain: 1) Plan 2) Source 3) Make 4) Deliver 5) Return 6) Engage

Really, it is boiled down to matching supply to demand well.

If you have a good supply chain, you are able to make good money. It is important! It is the heart of the business. If you have a poor supply chain, you lose productivity, you lose money, you gain customer complaints, you have to expedite in the future, and damage to your brand.

The biggest change supply chain faces are: 1) Flexibility and responsiveness to changes in demand or product 2) Supplier performance in terms of risk, reliability, and quality. 3) Ensuring the supplier has sufficient capacity 4) Effectively supporting new product launches 5) Lack of competitive cost structure

Usually there is a spectrum on how much it is costing versus how fast you are. The products you’re selling often determine what side of the spectrum you fall on. Functional products are stable; they are safe, low inventory, low profit, long shelf life and predictable. Innovative products have uncertainty, short product life, high inventory cost, high margins.

Efficient:

• Good for functional products (steady, low margins)
• Utilize as much capacity as possible
• Reorder often
• Reduce lead time as long as it doesn’t incur cost
• Interested in cost and quality provider
• Uses boat more

Responsive:

• Good for innovative products (don’t know demand)
• Deploy buffer capacity to have flexibility.
• Keeps a lot of extra inventory
• Will pay for faster lead time
• Interested in speed of supplier.
• Uses air more

Many products are just assemblies of other companies products: think iPhone, Boeing Airplane. They are all just dozens of parts stuck together from parts of other companies that have their very own supply chains.

Vendor Managed Inventory: When a company manages inventory at a store. Think how you see a coke guy refilling the local grocery store.

Decentralized or Centralized

How can you configure your supply chain network to optimize your process? There are two main types: centralized and decentralized. Many companies make their product in one location and then have warehouses in different markets. Sometimes you just are decentralized and source, make, and distribute in many different locations.

Centralized:

• Total inventory is less
• Lower cost (sometimes)
• Higher shipping costs (but can negotiate with a primary vendor)
• Standardize practices
• Longer shipping times
• Good for stable predictable products
• Good for when shipping speed isn’t important
• Good for higher available products
• Good for few points of sale
• Want to send a lot at a time.
• Not as complex

Decentralized:

• More extra inventory
• Faster, cheaper shipping
• When you have lots of points of sale

Outsourcing

Outsourcing is obtaining and resource or process external to the company.

Why should you resource?
• Reduce and control constraints
• Increase flexibility and speed
• Share risk with another company
• Increase innovation capability
What should you outsource?

Probably don’t outsource everything. You can identify all company activities and ask “Is this activity core to what we do as a company? Or at least important.” A core item would be strategic value, bread-and-butter, do it better than others, competitive advantage. You could make a 9x9 matrix of competitive advantage and risk of outsourcing. If the help is high, and risk is low, why not outsource!

Offshoring

Offshoring is obtaining any resource or process external company and across an ocean. You can offshore to yourself. A lot of companies have IT work in India for American companies.

Nearshoring would be moving something to Mexico or Canada (not across an ocean).

Usually this is done because of cost. You have to ensure the quality, speed, and innovation is satisfactory.

When you do this, there can be a lot of cost elements such as taxes, tariffs, exchange rates, ect.

Lean Manufacturing

Lean originated with Toyota Production System in Japan. The philosophy behind lean is the elimination of waste. No value = Waste. Customer’s define value.

Steps

1) Identify value 2) Map the value stream 3) Create flow 4) Establish pull 5) Seek perfection

Pull vs Push

Push

Take the raw material and make as much as we can with what we’ve got. Every worker will be busy as often as they can. Keep individuals and workstations busy. But no guarantee that what they’re making is going to get sold. You’ll see bottlenecks and piles of unfinished product. Hard to adjust to changes and last minute orders.

Pull

You have raw material, but that doesn’t mean you move it. As customers order from you, that becomes the signal to make more. And it starts from the end and pulls backwards. Preventing piles of unfinished product from collecting. Keep the material busy. If production stops in some place, you could run out of material. Throughput time decreases.

Kanban

Kanban was inspired by Piggly Wiggly’s use of cards to describe when to restock the shelf. Take a card down to show you took from the storage and give it to the other work center upstream. They then finish and put that card and the product into storage. Doesn’t make any more or any less than the cards.

Production Planning

Take sales forecasts and try to make production plans and schedules. How do you match demand and supply?

View the following:

• Raw Material Availability
• Market Demand
• Economic Conditions
• Competitors’ Behavior
• Capacity

In terms of personal, you have the following strategies:

• Temporary workers
• Subcontracting
• Large backlogs
• Hire and fire
• Excess Inventory
• Change production rates
• Overtime/reduced hours

External Strategies:

• Price changes
• Promotions
• “Bundled” or “Packaged” offerings
• Turn down orders
• Pre-Orders/Reservations

Bull-Whip Effect:

As you go upstream from the customer, the suppliers order more and more. So customer might want 5, and the party above them orders 10, the party above that orders 15, and the party above that, orders 20, and the party above that orders 40 and now you’re 35 over the demand.

What causes this? Fluctuations in prices. Things like sale could make demand go op artificially. The parties above don’t know about the sale so they can’t tell it is artificial demand.

Ordering Batching to keep storage and inventory, could be seen as demand where it doesn’t exits.

Shortage Gaming is when the suppliers are worried and order more than needed, often causing canceling

News Vendor Model

A boy buys a paper for $0.80 and sells for$1.00.

How many should the boy buy each morning?

Too few papers and he’ll lose customers because he won’t have anything for them.

Too many papers, he has to eat the price of the extra papers because no one wants one tomorow.

Your goal is to maximize profit. But the demand is unknown, but it can follow a distribution.

This is used for restaurants, perishable foods, short selling seasons (flowers, Christmas trees, )

• c the cost of each item from your distributor
• p the selling price for each item
• s salvage for unsold items
• x the number of items you buy
• P(x) the probability that the next item will sell (goes down as x goes up)
• $C_u$ is the cost of under supplying which is $p-c$
• $C_o$ is the cost of over supplying which is $c-s$

Solve for the P(x) until you reach the critical fractile $\frac{C_u}{C_u+C_o}$

You might have some normally distributed curve of what demand might be.

Forecasting Demand

Forecasting is the prediction of future events used for planning purposes.

One of the best forecasts is the weather. What is the weather going to be in the future? You use that information to determine what you do and what you wear.

Forecasts could come from qualitative in nature, an opinion or intuition. The other is quantitative that rely on data, math, and analytical techniques.

Forecasts are usually wrong, but they can still be helpful. Forecasts are usually more accurate for shorter period of times. Every forecast should have an error estimate. Forecasts are more accurate for groups of families of samples.

Patterns of Demands

1) Trends

2) Seasonality

3) Cyclical Elements

4) Autocorrelation

5) Random Variation

Time Series Forecasting

Simple Moving Average

The last n values within the last n periods, the average of the last n, is the prediction for the next n.

$F_{t+1}=\frac{\Sigma v_n}{n}$

Weighted Moving Average

The weighted moving average is very similar to the simple moving average, but instead you weight the pervious n data values. Usually the sum of the weights equal 1.

Usually the most recent value is weighted the highest.

Weights are chosen via trial and error.

Exponential Smoothing

The prediction depends on the most recent observation and the error of the latest forecast. You weight these two based on $\alpha$. Very common, easy to understand, fast to compute, low storage.

$F_{t+1}=F_t+\alpha \cdot (A_t-F_t)$

A higher alpha means that the method is more reactive and relies more on the last point/error.

Metrics

Bias: when a consistent mistake is made.

Random: errors that can’t be explained by the model.

Error

The error is just defined as: $$E_t=A_t-F_t$$

RSFE

Running sum of forecast error:

$\Sigma(A_i-F_i)$

MFE - Mean Forecast Error (bias)

$MFE=\frac{RSFE}{N}$

$TS=\frac{RSFE}{MAD}$