Square Root Law – inventory in multiple locations

Got asked what would happen to inventory when the number of stocking locations change.  I thought for a minute and remembered a quick estimate.  The Square Root Law states that total safety stock can be approximated by multiplying the total inventory by the square root of the number of future warehouse locations divided by the current number.

X2 = (X1) * √ (n2/n1)

n1 = number of existing facilities
n2 = number of future facilities
X1 = existing inventory
X2 = future inventory

Here’s an example:

Current inventory is 4000 units, 2 facilities grow to 8.  Using the square root law the future inventory = (4000) * √ (8/2) = 8000 units.

 

 

 

By Lawrence Loucka | 2 comments

Demand Profile

Maslow’s hammer, or a golden hammer is an over-reliance on a familiar tool; as Abraham Maslow said in 1966 in A Psychology of Science, “It is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.”  So, must every product in every business segment be set up in a one piece flow cell? Or put on kanban with an heijunka to smooth demand? Or run on a rate-based assembly line? Certainly not!  One size rarely fits all.  But how to know which techniques make sense?

One place to start is to look at customer demand. All lean practitioners know about Takt Time, or the customer drum beat, and is used to match the pace of an operation with customer demand.  Takt Time is calculated at Available Time/Demand, and is by definition an average.  Customer demand is anything but average, and so we need to understand the variation or range of demand placed on our process.

Here’s an example …

To build a demand profile take the following steps:

  1. Pick the product or product family or business unit of interest.
  2. Determine an appropriate time unit – hourly, daily, monthly.
  3. Gather the true customer demand as best you can.  Be careful about using promise dates instead of requested dates, and be doubly cautious of schedules which are often smoothed, filtered, or otherwise manipulated.
  4. Create the graph or time series plot as above.
  5. Now calculate some simple descriptive statistics.  In this example the average is 17 with a range of 49 and a standard deviation of 11.

What can we conclude?  Should we design our operations control around a demand rate of 17 a day?  Is the variation in demand something we can deal with?  How?

 

By Lawrence Loucka | One comment

ABC Analysis: how to

 

  1. Make a list of part numbers
  2. Determine total quantity used over some period of time
  3. Obtaining the cost for each part
  4. Calculate usage $ value for each part by multiplying the quantity and the cost
  5. Sort the list from high to low $
  6. Calculate the total usage $ value for all items
  7. Calculate each item’s percent of total usage $ value
  8. Select percentage cut offs for each ABC group, for example:

 

Here’s an example …

Example of ABC Analysis

 

Next steps

Once you have classified your parts you can use this data to drive key materials management activities. For example, coordinating your perpetual inventory cycle counting program – you might routinely verify your Category A parts on a monthly basis but only review your category C parts twice a year.

You might use flow orders, kanban, or VMI for your C parts but require detailed negotiated purchase orders for your A parts.

In a warehouse you might want to be sure the A items are near the shipping dock and the C items are toward the back.

You might even want to take a close look at the C items and purge a few.

The main point is – one size doesn’t fit all parts, choose the materials management approach that best serves each inventory category.

By Lawrence Loucka | Leave a comment

Bullwhip Effect

The bullwhip effect is the result of uncertainty caused from distorted information flowing up and down the supply chain.  The bullwhip effect is caused by fluctuations in information supplied to firms further up the supply chain. Distorted information causes firms to forecast demand incorrectly.  Thereby, many unnecessary costs are put upon each of the firms along the supply chain.  Nearly all industries are affected!  Firms that experience large variations in demand are at risk.  Firms that depend on suppliers upstream or distributors and retailers downstream may be at risk.   Most firms are affected by the bullwhip effect.  The bullwhip effect used to be considered a normal phenomenon.  However, recently, many firms have been trying to focus on how to improve communication along the supply chain.  The bullwhip effect can inflict many unnecessary costs on business firms.  Inventory costs from stored inventory, problems with quality caused from rapid production, overtime expenses for increased employee labor, and increased units being shipped create costs far and beyond normal levels of production.  Customers can also lose faith in a firms ability to deliver products.  This is because firms are having trouble meeting demand.  Likewise, firms often must lengthen lead time for finished goods, which also may discourage customers, which in turn leads to lost sales.  In a worst case, incorrect forecasts may entice a company to adjust capacity which could be detrimental to the overall success of the company.  To reduce stocked product, retailers may offer sales promotions to customers.  If retailers fail to notify firms upstream in the supply chain, these firms may forecast increased sales as legitimate demand.  Thereby producing product that was not wanted by the customer in the first place.  Furthermore, salesforce incentives may entice selling products to firms to meet targets.  This may cause large inventories for the firm, or the firm may cancel the orders, which causes demand fluctuations in the supply chain.   Firms upstream in the supply chain may feel that the increased demand may be legitimate and increase production and inventory levels to produce more.  However, in reality, the product hardly moved and required a drop in price to be moved off of retailer’s shelves.  Each firm upstream in the supply chain will feel the whip effect.

Here’s the classic illustration from The Bullwhip Effect in Supply Chains by Hau L. Lee • V. Padmanabhan • Seungjin Whang, SLOAN MANAGEMENT REVIEW/SPRING 1997.

 

By Lawrence Loucka | Leave a comment

Time Value Chart

 

 

 

  1. Determine Total Cycle Time
  2. Determine Queue Times between steps
  3. Create Step segments proportional to the task times
  4. Place steps, queue’s along the line segment in the order that they happen
    > Place Value Adding steps above the line
    > Place Non-value Adding steps below the line
  5. Draw in feedback loops & label Yield percentages
  6. Sum Activity / Non-activity times
  7. Sum Value / Non-value Times
By Lawrence Loucka | Leave a comment
 
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