Lean Six Sigma Rick Orr, Finance Manager Public Works Reducing Street Light Inventory.

Lean Six Sigma Rick Orr, Finance Manager Public Works Reducing Street Light Inventory

Work Towards Achieving Mayor Richards City Goals -Safe City -Quality jobs -Improved customer service - B.E.S.T. Demonstrate how Lean Six Sigma Improves Customer Service and Saves Resources Improve Customer Service by Reducing Capital Investment in Street Light Inventory Project Objectives

Systematic approach to reducing process defects that produce undesired outcomes - in our case, improving the decision making regarding inventory purchases DMAIC Define, Measure, Analyze, Improve, Control Team focus to problem solving - each of us are experts in certain areas of the inventory process and each have specialized knowledge of portions of the process What Is Lean Six Sigma?

Street light inventory seems excessive relative to usage Project Description Reduce inventory to optimum level Problem Statement: Objective:

External Customers Citizens Carrying excessive inventory ties up capital that can be used elsewhere Lost capital opportunities cause unnecessary high tax rates Internal Customers City Staff Uncertain ordering schedules makes it difficult to anticipate ordering needs Inaccurate inventory records Inaccurate damage recoveries Inaccurate materials billing Cost of Poor Quality

Frees capital funds to be redirected towards other use and helps maintain low taxes Benefits

The Y: the total value of street light inventory, measured monthly Y = f(x 1,x 2,x 3,,x k ) The Y

Minimizing Inventory: Increases flexibility in asset management Makes it easier to control Reduces the need for space Makes it easier to count Reduces aged inventory Inventory is an asset, but it is a non-productive asset. It earns no interest but costs City in handling, shrinkage, and space. Why Minimize Inventory?

Y = f(x 1,x 2,x 3,,x k ) The Project Plan: examine the factors that drive inventory levels on various items and appropriately reduce the level of individual street light items The Goal: Reach optimal levels of inventory to reduce the invested capital The Defect: excessive street light inventory The Y: the total value of street light inventory, measured monthly Definition of the Y

Champion: Greg Meszaros Assisting: Michele Hill, Roger Hirt Team Members: Rick Orr, Project Leader/Black Belt Dave Pepper, St Light Warehouse Nate Parker, St Light Warehouse Lori Dekoninck, St Light Warehouse Phyllis Davis, St Light Engineering Admin Steve Davis, Assistant Traffic Engineer Tracy Neumeier, Internal Audit/Black Belt Project Team

DefineMarch April 2003 Measure May Sept 2003 AnalyzeOct March 2004 Improve Apr Jun 2004 ControlJun 2004 + Project Schedule

Number of Street Lights (Approx) 27,500 Number of Alley Lights (Approx) 3,100 Energy Expense, 2003 $453,367 Department Expense, 2003 $2,743,285 Estimated Value of Network $8,500,000 Street Lighting System

Material Needs Determined Materials Ordered Materials Delivered Materials Stored Materials Depleted Process Map

Cause and effect matrix: Important Factors: demand, lead time, order interval, level of safety stock Cause and Effect Matrix

How can our process fail? As ranked with FMEA, failures can result if: historical usage data is not maintained and monitored inventory usage is not recorded by maintenance crews material usage is not recorded on work order tickets expensive in-stock items are substituted for out of stock items vendor states inaccurate delivery time on bid poor analysis done in budgeting cycle How Can Our Processes Fail?

Budget vs actual: 2000 - 2003 In May of 2003, the inventory budget was reduced by $100,000 in anticipation of project success. Approximately $80k less was spent on materials than modified budget would have allowed for 03. Estimated savings to date (March 04), $180,000. Budget Vs. Actual Costs 2000-2003

Actual material expense 2001 $636,865 Actual material expense 2002 $584,287 Actual material expense 2003 thru 9-30 $320,199 Total $1,541,351 Historical usage captured Jan 01 Sept 03, valued at $966,547 Current inventory value as of Sept 30, 2003 $630,806 Has all data been captured? *Note that recorded usage does not total the amount expended Has All the Data Been Captured?

Has all data been captured? All recorded historical usage was collected Historical inventory values were not kept. It can not be determined if some usage was not recorded or if the differences shown on the previous slide are attributable to changes in the value of inventory on January 1, 2001 as compared to the value of inventory on September 30, 2003. What can be done to insure data integrity, going forward? Work orders Re-lamping lists Proactive maintenance files Capital project files Has All the Data Been Captured?

Low hanging fruit data source Implementation of an inventory tracking database Material usage recorded as it leaves warehouse Information readily available to all staff Facilitates data collection going forward Improves accuracy of recorded usage Accomplished without adding any additional tasks not already being performed by warehouse personnel Data base implementation should help address 2 factors identified in the C&E matrix: availability of historical data and reliance on staff experience Low Hanging Fruit-Data Source

Modified Microsoft Office Template:In-house expertise without added cost Key problem poor record keeping Key Problem-Poor Record Keeping

Inventory Turn: A common method of measuring inventory management Calculated by dividing the average inventory level ($) into the annual inventory usage ($) 2003 material usage $450,539 2003 average inventory value $682,441 *For 2003, Street light inventory turned only.66 times *For 2004, Street light inventory turned 1.124 times Inventory Turn-Annual Inventory Use

At the start of this project, 165 items were identified with specific item numbers Shortly after implementation of database, an additional 88 inventory numbers were assigned to materials not previously carried on the books *Value of items not previously accounted for totaled $26,581 or 4% of inventory on hand as of Oct 21, 2003 Inventory Records-Inventory Accuracy

Inventory accuracy - Accuracy Benefits Enhance Customer Service Reduce Stock Outs Production is not jeopardized Inventory Accuracy

Past: Historically, a physical inventory count was conducted once per year. Accuracy statistics were not maintained, and the existing stock record was over-written with updated counts. Effective 2004, implemented Cycle Counting Current: Inventory items are now differentiated and counted multiple times per year, depending on usage-value (inventory classification) Class A items, count 6 times/year 80% of $ spent over 33 months Class B items, count 2 times/year 15% of $ spent over 33 months Class C items, count 1 time /year 5% of $ spent over 33 months

Inventory accuracy rates After annual 2003 inventory count, error rates were established. An error occurs whenever an item count differs from the inventory record, while considering +/- 5% as an acceptable tolerance. Class A items 27.3% error rate Class B items 35.7% error rate Class C items 26.1% error rate All items 27.3% error rate, 12-31-03 Error rates will be tracked with control charts, going forward. If the use of the inventory data base and the implementation of cycle counting fail to improve this error rate, this problem could be investigated further as a Green Belt project. Inventory Accuracy Rates

3 yrs of expense, 165 item numbers Most of the project effort and analysis will be directed at the 22 items comprising 80% of the expenditures. These top 22 items are designated as class A items. Show Me the Money!

Ranked listing of high expense items (class A) Jan 01-Sept 03

Poles used: Jan 2001 Sept 2003 Poles Used: Jan 2001-Sept 2003

Fixtures used: Jan 2001 Sept 2003 Fixtures Used: Jan 2001-Sept 2003

Bulbs used: Jan 2001 Sept 2003 In early October 2003, 48 250w bulbs and 48 400w bulbs were ordered! Why? Because we need them! Bulbs Used: Jan 2001-Sept 2003

Differences in usage values and dollars spent each month could mean that not all material usage was recorded or more inventory is being purchased than is being used. Total $ value of materials used = $1,034,998 Total $ expended = $1,577,055 *34 months examined Purchase Decisions Made On Usage

* With monthly measurements, there does not appear to be a significant linear correlation between material usage and the amount of funds spent for inventory acquisition. If R-Sq > 80%, then correlation is significant R-Sq = 1.2% Correlation of Funds and Usage

Additional bidding expectations were requested of vendors bidding on poles, mast arms, and fixtures Informed all bidders of our goal to minimize inventory carrying costs Required bidders to list best price at minimum quantity levels, price at lesser quantity order levels, and worst price if only 1 unit ordered Required vendors to list the length of time between order placement and order delivery (lead time) *This information will be critical in determining optimal inventory levels and reorder points Changes to Bidding Specifications

Beginning in 2000, Street Light Engineering began testing the longevity of various bulb manufacturers Purchase Decision: What Bulb is the Most Cost Effective to Purchase?

Sylvania bulbs are the most cost effective for the City Without the cost/lifespan analysis, former procedures would have directed us to purchase Phillips bulbs The addition of bulb replacement labor costs to the analysis, would further expand the cost differences Low Price Best Price

Material ordering procedures were tightened for all inventory purchases order form initiated by warehouse personnel or engineers order requires sign-off by department director order requires sign-off by finance manager Changes to Ordering Procedures First time the procedure was used, an order of photo cells was reduced from 500 (4-5 month supply) originally requested to 200 ordered

Purchase/Replenish Pull System Implemented a widely recognized inventory system, developed by Toyota Motor Corp, known as Kanban Kanban is an empirically driven method of both signaling the need for inventory and controlling inventory levels Kanban Japanese word for sign Purchase/Replenish Pull System

4 Variables for an Effective Purchase/Pull System Demand the average monthly usage amount Lead Time length of time expired between placing order and receiving goods, measured in monthly units Order Interval how often orders are anticipated, in monthly units Safety Stock amount of inventory to be held to compensate for demand variability and/or lead time variability Purchase/Replenish Pull System

Historical Demand Estimate Future Costs By Analyzing Past Material Usage 4 Uses of Materials Maintenance Repair to Damaged Facilities Re-lamping Activities Based on Light-Out Lists Proactive Replacement of Aged Facilities and/or Bulbs Capital Construction Project Capital projects are known prior to construction. By meeting minimum requirements, capital materials can be ordered on a project by project basis. On appropriate projects, capital needs will now be segregated from other material needs. Recall that some of the historical data might be suspect Historical Demand

Demand analysis Demand Analysis = Compare means, standard deviations, and medians for each item Pre data base implementation Post data base implementation Demand Analysis If similar, conclude historical usage was accurately collected use data collected since January 2001 for a specific item If different, conclude historical usage was not accurately collected use data collected since October 2003 for a specific item

21.41% of material expense 100 HPS Town & Country Fixture

Should all data be used to estimate monthly demand? Difference in means Difference in medians Similarity in Standard Deviations Inconclusive to not under estimate, use data since Oct 1, 2003 100 HPS Town & Country Fixture (Continued)

8.82% of material expense 150w Cobra Head Fixture

(Continued) Large difference in means Large difference in medians Similar standard deviations Conclusion Including data prior to Oct 03 might result in under estimation of usage 150w Cobra Head Fixture

Demand Analysis Lots of Variability 100w Alley Fixture

100w alley fixture (continued) Similar Means Similar Medians Similar Standard Deviations Conclusion Including data back to Jan 01 should not result in under estimated demand This methodology was used to analyze demand for all class A and class B items 100w Alley Fixture (Continued)

lead time Lead Time - Time Expired From Order Initiation to Receipt of Goods Lead Time stated in bid specifications for poles, fixtures, bulbs include City staff time for requisition preparation and sign-off

lead time analysis Lead Time Analysis

lead time analysis Conclusion: Lead Time Analysis must be done at the item level not the vendor level Lead Time Analysis Lead Time on Graybar Items There is too much variation in lead time between different items

Order Interval- Frequency of Placing Orders for Each part If ordering often, can order less quantities per order. But there are overhead and administrative costs for initiating order, processing requisition, purchase order contacting the vendor and placing the order receiving the goods, re-stocking the shelves processing the payable Order Interval Order class A items frequently, and order class C items infrequently Trade-off between the level of inventory quantities carried per item and the frequency of ordering the item. Pareto analysis used to establish order frequencies. Class A items are few but are 80% of the dollars in inventory. Class C items are numerous, but only a small part of total inventory value.

Preferred Products: Poles, Mast Arms, Transformer Bases Poles/Mast Arms: charged a 13 14 % premium for orders totaling less than $11,000 / order, effective 2004. Various types of poles/mast arms can be mixed per minimum $11,000 purchase. Preferred Products purchases, October 2003 - February 2004 averaged $7,429 per month. To avoid paying an average premium of $1,003 per month (if the interval is 1), the order interval should be at least 2 months. This results in an inventory that is larger than would be necessary otherwise, for items that are relatively expensive. But in effect, the excess inventory carried is returning approximately 13.5% in avoided expense. Recall the Cause & Effect Matrix the process output cost effective purchases was ranked at 8 out of 10 in importance to the customer. Order Interval

GE Supply Fixtures & Power Doors Order Requirements: Lots of 25 Orders less than the per fixture price increases by 10%, or on average, $9 more per item. Again, the result is inventory that is larger than would be necessary otherwise if cost effective purchasing is to be achieved. But some fixtures used infrequently, anticipate paying premium charge. Order Interval

Safety Stock Safety Stock: inventory stock required to guard against process variability demand variability lead time variability quality variability Safety Stock Quantity: dependent on desired service level service level 1, on average no stock outs 84% of the time service level 2, on average no stock outs 98% of the time service level 1, 1 standard deviation of safety stock carried service level 2, 2 standard deviations of safety stock carried Safety Stock High Service Levels Need More Inventory/Safety Stock

Materials for capital projects are known in advance and ordered on a project by project basis. Capital projects are not impacted by the service level choice. For the cause & effect matrix, process outcomes were ranked by the Division Director minimizing total inventory carried ranked at 10 (high) responsiveness to calls, light outs ranked at 6 (medium) Street lights are not a critical service, so a service level of 1 will be used to establish inventory re-ordering points and optimal inventory levels. Safety Stock= Standard Deviation * Service Level * (Lead Time ^.7) Safety Stock-Level of Service

Kanban System Establish inventory levels and calculate reorder points for each carried stock item. Inventory Level/Order Triggering Formulas Kmax = Max on-hand quantity for an item (lead time * demand) + (order interval * demand) + safety stock Kmin = Re-ordering trigger point for an item (lead time * demand) + safety stock Order more stock when (balance on hand + items on order) is less than the trigger point Order Quantity = Kmax (balance on hand + items on order)

Inventory fills demand (after considering the acceptable level of risk of running out, i.e., safety stock). Demand is monitored not controlled. Demand affects inventory level, inventory level does not affect demand. Modified data base- demand transactions and values are monthly calculated and updated with changes. Materials for capital projects are bid and supplied by the successful bidder, not by the Citys inventoried stock Controlling the Xs (Demand)

The database was modified to better capture lead time changes. As orders are filled and the database updated, the received date is recorded and compared to other order dates. The difference in dates is converted to monthly units. The database prints lead time reports that list the average lead time value by item and by vendor to update lead time fields. Controlling the Xs (Lead Time)

Control Plan Summary

Control Plan Summary (cont) Control Plan Summary (Continued)

1.Prior to this project, procedures were not standardized or documented. As part of the control plan, inventory procedures were spelled out, documented and distributed. 2.The Street Light Inventory Procedures manual will facilitate implementation of the control plan, project understanding for all personnel and staff training in inventory control. 3.Inventory control still needs more work. Cycle counting will be examined in detail and order intervals will be further analyzed. Controlling the Process

Methodology is Working! To date, $400,000 of funds released can be redirected towards better use Methodology is Working

Inventory Levels, March 2005

Methodology is Working! Methodology is Working Since project inception, $400,000 of funds have been made available for use elsewhere. Without this project, inventory values would likely be at the level they were in early 2003.

ACTUAL VS 3% ANNUAL INCREASE Annual Budget $1,341,000 of Accumulated Savings BID YEAR Street Light Maintenance Contract BID YEAR

Lean Six Sigma Rick Orr, Finance Manager Public Works Reducing Street Light Inventory.

Documents

street light inventory

aged inventory inventory

inventory process

excessive inventory

inventory levels

excessive street light

project schedule slide

optimal levels of inventory