Problem Statement
FISC Yokosuka manages 246 line items of 1Q Cog material. Of these items, 129 have limited shelf-life. Due to order and shipping time from stateside suppliers, shelf-life on many line-items frequently expires before issue to our customers. Result is approximately $500,000 in disposal and re-procurement costs per year. We buy products using BP21 dollars (NEXCOM); store them using BP91 dollars (NAVSUP); dispose of them using BP21 dollars (NEXCOM); then re-procure new products using BP21 dollars (NEXCOM). This entire process is managed by two FISC item managers and, although both are MLCs and paid for by the Government of Japan, we do incur some annual labor cost for both of them.

Results
Streamline and consolidated process steps to one FISC and reduce order and shipping time by 50%. $250,000 type 1 savings.

Problem Statement
NAVICP produces shore-based allowances that are expensive to support, and are ineffective for customers. 20 percent of the NSNs on CONUS shore allowances and 17% of the NSNs on Ex-CONUS shore allowances experience zero demand during the life of the allowance.

Results
Improved the efficiency and effectiveness of the Shore Allowance process by removing non-value added activity from the process. Reduce NAVICP labor costs by $75,000 and saved $2M in material cost.

Problem Statement
During October 2007 through March 2008 the Process Cycle Time (PCT) for the FISCPH Shipyard Purchasing Division ranged from 1 to 179 days. The average PCT was 37 days. 69% of Shipyard Purchase Requests (PR) were not awarded within the NAVSUP required Purchasing Acquisition Lead Time (PALT) of 20 days. 43% of PR’s did not meet the customers Required Delivery Date (RDD).

Results
Achieved a 50% reduction in the FISCPH Shipyard Purchasing Division average Processing Cycle Time from 37 days to 18.5 days. $32,926 Type 1 & 2 savings.

Problem Statement
DSCR Richmond, as the DLA lead for aviation, expects on-time completion of 339s as follows: 95% for the highest priority 339s; 85% for more routine requests. The Navy averages 80% on time of all 339s. There is considerable variation in the process, driven by significant NVA (mainly queue time).

Results
Reduced turn-around time by 57%.

Emergency Department - reduced wait time: using Lean principles to study ‘patient flow’, avg patient wait time was reduced 70%. By focusing on ‘reducing waste’ and improving information flow, Material flow and patient flow, numerous ‘wastes’ were identified throughout the process. (e.g. multiple steps to gather information, duplicate information gathered, unnecessary breaks in ‘flow,’ duplicate information on multiple forms, relocation of supplies, simplification of forms .. etc). In addition, patients were broken into A-B-C groups (easy –medium-hard). The A’s were handled with the goal of ‘letting the fast go fast.’ In doing so, not only did the overall average come down, but more importantly, when patients are not ‘waiting’ in exam rooms, those exam rooms are now open to ‘start and complete’ other patients …

Wait time in orthopedics: Orthopedics is one of the most predictable procedures in an entire hospital. Knees, hips, orthoscopic procedures are all very predictable in time, materials, and recovery. Instead of ‘planning’ on using patient’s “time” as their strategy for keeping everyone busy, procedures again were broken into A-B-C. The mix of A’s was very high. With these procedures, they could (without risk) plan procedures at a much tighter degree of scheduling. Obviously SMED was used for OR Turnaround Time, Kits were used for common procedures, Department meds were revisited to ‘right size’ type, size and qty of meds … etc. Another big piece of this was the ‘level’ schedules Mon-Fri.
Capacity through imaging: SMED and patient flow is the key. In this situation, Imaging was capacity constrained. Using a simple VSM to look for patient delays, CT ‘waiting’. The key here is that everyone waiting is consuming assets. You want it to flow like subway sandwiches .. not like Disney. When you focus on “Theory of Constraints” in a capacity constrained business, the game is easy.

OR inventory: Hospitals typically have very good processes for getting ‘materials/instruments/rental equipment in.’ However almost NO hospitals have good processes for getting these things OUT. You could approach this as 5s (I do not) or about “Inventory Reduction” (which is the right way). Inventory ties to the balance sheet. Inventory is measured by the CFO. A simple A-B-C analysis of inventory takes you to both A’s (fast runner) and C’s (slow runners). In the world of healthcare, you can get (almost) anything in 24-48 hrs. Why do we have 70+ days of inventory on hand (no including Pharmacy … this makes the number worse)? In Healthcare Inventory is both very liquid and very concentrated. i.e. when you identify excess, you can immediately convert it to cash. Also, inventory Dollars are very concentrated in OR, ER, ICU, Pharmacy. C’s are identified very quickly (and sent back for credit). A’s are recognized as being very slow runners (compared to what they could/should be). Savings: $400k

Backlog in sterilization: Count the instruments ‘waiting for sterilization’ before the event. There are always many. Often times, many instruments that are still ‘sterile’ are waiting in line for someone to determine whether they need to be re-sterilized. Developing a specific process (a la cleaning dishes at the cafeteria) to handle the ‘flow’ of instruments into sterilization is pretty easy. The goal being to ‘put more instruments in play’ ... often works like a ‘tool crib’ in a plant. They never realized how many tools they actually have. When you keep them all ‘clean’, they realize they don’t have to order more. Result … reduced ‘expenses’ for a solid 2-5 months.

Problem Statement
Variability of configuration changes and system upgrades introduces increased processing time (4-6 days) and potential file inaccuracies (23%). Timely and accurate processing of these changes and upgrades is required to produce a quality Allowance product.

Results
Reduce 08, Retail Operations, configuration management processing time by 47%, and 12% improvement in accuracy. $150,000 Type 1 savings.

Problem Statement
FISC Yokosuka manages 4800 line items of 9G COG material.  Of these, approximately 500 items, have excess inventory that is considered dead stock -- no demands for this material within the last 24 months.  NAVSUP continues to pay item management and other associated costs (i.e. storage, receipt, and disposal costs) on this dead stock.

Results
Reduce our internally generated 9G COG excess material by 50% in four months and eliminate the associated costs of storing and managing this excess material.  Established standard procedures and practice to prevent reoccurrence of excess inventory.  $227K type 1 savings.

Problem Statement
Material directed into VREP increases Transit Time and overall processing costs.   Of the 17,883 shipments processed by VREP facility at FISC Norfolk as FOB Destination, 13,148 of these requisitions are “mail” eligible. 

Results
Reduced total processing costs by $631,109 and reduce Transit Time by 2 days.  This equates to 90% reduction of mail eligible shipments (14,609 X 90% = 13,148).

Problem Statement
Understand variance (17 – 32 days) in customer ordering routines that drive manual or exception processes; understand and lean subsequent order sourcing processes; define and measure order processing. Order processing time is the process metric that will define improvement of the Order Sourcing process.

Results
Reduced cycle time between receiving (date of requisition establishment in U.S.N. files) order and subsequent sourcing decision by 50% while reducing labor cost. $276,000 Type 1 savings

Problem Statement
The Navy is forced to use ‘premium’ Strategic Air support in order to support GWOT required delivery dates with waterfront ammunition support services.  The use of ‘premium’ air support is done to expedite in order to meet delivery requirements; this is costing in excess of $1.4M.

Results
Streamlined the processes through elimination of waste of non-valued added tasks associated with rework, operational definitions, and submission process that drove the need to ship via Strategic Air.  Reduce items shipped via Strategic Air by 95%.  $1.211M in Type 1 savings.

Business Case
The overall goal of the health clinic is to reduce the prevalence of Sexual Transmitted Diseases (STD). In order to optimize that goal within the clinic, we need to see as many patients as possible within maximum defined wait times while maintaining best practices.

Opportunity Statement
Our current clinician process is capable of only seeing 1.1 pts per hour, with a Full Service Patient Length of Stay (LOS) that exceeds 120 minutes.

Performance Measurements

Metrics	Current	Std Dev	Goals
# of full service patients / hour	1.1 pts per hour	.3 pts per hour	2.5 pts per hour
Length of Stay at Clinic	< 120 minutes	23.4 minutes	< 60 minutes

Key Current Process Steps

A Lean Six Sigma team was formed utilizing the DMAIC (Define, Measure, Analyze, Improve, Control) methodology using both Lean and Six Sigma tools.

In the Measure phase, the team began by walking the process, then to map out the current process using both a Value Stream Mapping technique and a Spaghetti Map to better understand patient, clinician, information flows, and cycle / lead times. The team collected and validated cycle-time data, and both patient and clinician travel distance by number of steps for analysis. A Value Analysis was conducted by the team to determine and define activities that are customer value added, non-value added, and business value added; the results of this analysis were less than 2% of activities were considered to be customer value added. The customer was defined to be the patient.

Two quick-wins were identified by the value analysis that eliminated 18 minutes in the patient flow. (1) Patients with an appointment no longer went through triage, and (2) Patients forms were revised eliminating obsolete and redundant information.
By analyzing the remaining data, the team determined that the two areas impacting patient flow were in triage and the clinician diagnosis and treatment process. The actual cycle time for these two processes was 55 minutes, with a patient wait time of 82 minutes. The team’s primary focus is to identifying and validates the root cause for patient flow inefficiencies within these two primary areas.

In the Analyze phase a fishbone analysis was performed that identifying three main areas as potential root causes:

• Patient Turnaround Time
• Data Entry, and
• Lack of Clinician Teamwork/Skills

Data was gathered and used to validate these three areas by performing hypothesis testing through ANOVA.

Patient turnaround time – Clinicians that saw at least two patients in parallel, versus Clinicians only are seeing one patient at a time.

Results
Clinicians seeing patents in parallel had a significant time impact on reducing patient time and capacity.

Data Entry – Computer data entry, versus manual entry of data on form. Results: Manual data entry had a significant time impact on reducing patient time and capacity.

Clinician Teamwork/Skills – Developing an employee skills proficiency matrix the team analyzed clinicians who were more skilled / knowledgeable than other clinicians. Results: Clinicians who were more proficient had a significant time impact on reducing patient time and capacity.

Impressive Results
The clinician improvement team reduced significantly patients Length of Stay by 83 minutes. Having clinicians come up with the solutions and buy-in to seeing patients in parallel, utilizing a manual check list form (color coded for male and female), and establishing a skills proficiency matrix to improve teamwork and overall competence lead to positive outcome in identifying diseases.
The clinician’s patients per hours metric improved immediately to 2.0 pts per hour with the parallel patient flow, and progressively over time to meet the original goal of 2.5 pts per hour as clinician skills and teamwork improved. The clinicians meet for 10-15 minutes each morning to review their own dashboard, workload, and document and status issues. This Kaizen Event also establishes a meeting with the clinic leadership team and the clinicians once a month to review strategic goals and evaluate their efforts on identifying and reducing the prevalence of Sexual Transmitted Diseases (STD) in the community.

The STD clinic will be moving to a new facility in 2012 and the spaghetti mapping will be of significant support for the facility layout to reduce walking for both the clinicians and patients. In addition, the cumbersome and time consuming computer system is expected to be overhaul with input from the clinic personnel to eliminate paper forms.

Problem Statement
Tower sections were not meeting customer demand and being shipped short each month. The goal was to have 35 sections shipped each month. Baseline performance is at 27 sections.

Results