Product Support Financial Value Drivers. 3/10 – Product Failure

Oct 11
2012

This post is the third of ten entries that will discuss product support financial value drivers for solutions supplied by a commercial or military focused capital good Product Support Enterprise [PSE]. The 10 topics that will be discussed are the following:

  1. # of products employed by end-users
  2. End-user product utilization rate
  3. Product failure
  4. Environment in which end users engage the product
  5. Preventive maintenance processes employed
  6. Volatility of product technology
  7. Regulatory requirements
  8. Chronological age of the product installed base
  9. Life cycle stage of the product
  10. Manufacturer’s warranty coverage

Product Support Value Drivers – Product Failure Physics Envy

This area is one of the most “abused” areas in Product Support life cycle financial planning. Operation Research [OR] analysts, design engineers and logistics professionals have what is affectionately called “physics envy” when it comes to estimating the product failure rates of end-items and their components. The elite group of professionals in the business of predicting product failures tend to have a universally low success rate…

The marketplace has defined the acceptable average level of unplanned failures for a capital good/end-item at about once every 5-7 years. This product failure rate is applicable primarily for Commercial Off The Shelf [COTS] items, with Developmental/Design-To-Order items incurring product failure rates anywhere from 50-100% higher than that of COTS items.

The source of the aforementioned failure data is the Security Exchange Commission [SEC] mandatory filings by OEMs detailing their actual expenses incurred to support their warranty programs. There is over 10 years of reliability/failure rate data sets. Note that product failure rates have dropped by almost 50% over this 10+ year period. Why the “failure analysis” community does not employ this treasure trove of data in all their cost calculations is always amazing to me.

Product Support Value Drivers – Product Failure

Recently Giuntini & Co. developed a scenario-based Product Support life cycle financial plan that included the target cost for the correct-failure process throughout the twenty life of a product. We employed a series of SEC filing data sets and estimated $10 million per year in costs associated with the correct-failure process for an installed base of $200 million end-items. We also employed another method to calculate the cost and it still resulted in approximately the same number.

Product Support Value Drivers – Product Failure

While we had been calculating the correct-failure process costs, a team of OR brains were also calculating the same cost; we were both aware that we were working to the same goal. We both agreed to compare our estimated costs and there was a 4-fold difference in our costs; the OR guys were the higher number. After I examined their methodology, which was quite eloquent, I must say (disclosure; I once was an OR geek myself), I found their results to be totally bogus.

If the higher product failure rates were to have occurred, the product would never have been acquired by any end-user. Our common client accepted the Giuntini & Co. cost estimate as the one to be included in his Total Ownership Cost [TOC] calculation. To this day the OR brains have remained convinced that their methodology was the right way to go, even after being proven decidedly inaccurate.

Lesson learned – be extremely careful of ”physics envy” professionals providing you with product failure rate estimates. There is a high probably that they are materially off from the real world and if you accept their costs without an alternative opinion, you have only yourself to blame when an estimated TOC is way, way off.

Hypatia©, a Giuntini & Company financial software tool, provides a highly automated means of calculating the above and other product support financial value drivers, as well as an effortless way of being able to change any utilization assumption and immediately understand its impact upon total ownership costs.

Product Support Business Case Analysis [BCA]: Fast, Accurate, Proven Results Employing The Hypatia© Scenario-Based Product Support Life Cycle Financial Planning Software Tool

Oct 01
2012

Product Support Business Case Analysis for MRAP

A Product Support Business Case Analysis [BCA] study is employed by the Program Manager [PM] Office of a Program Executive Office [PEO] of a Life Cycle Management Command [LCMC] in their Milestone Weapon System Acquisition review. The Product Support BCA study applies a disciplined methodology for recommending the best solutions for efficiently and effectively managing the processes employed by a Product Support Enterprise [PSE] during the in-service life and End-Of-Life [EOL] of a weapon system. The Product Support BCA output is a major input to the Life Cycle Sustainment Plan [LCSP] that is delivered by the Product Support Manager/Integrated Logistics Support Manager of the Program Office. Giuntini & Company, Inc. [GCI] has successfully performed five Product Support BCAs for the CECOM LCMC and the TACOM LCMC.

As a result of the experience above, GCI has developed a listing below of the varied elements required as inputs to the BCA.

Item #

BCA elements

1

# of end-items to be fielded

2

# of end-users

3

Deployability status of end-users

4

Global location of end-users

5

Product Support processes employed during life cycle

6

Product Support process frequency

7

Product Support process duration

8

Business model of each Product Support solution delivered by the PSE

9

Volatility of product technology/DMSMS issues

10

Regulatory requirements

11

Aging of the fielded end-items

12

Life of the product in DoD inventory

13

Manufacturer’s warranty coverage

14

Item design source/IP ownership/TDP

15

Materiel Availability [Am] requirements of end-user

16

“Jointness” of solution with multiple end-users

17

Business model elements for each Product Support solution

18

BOM levels employed

19

BOM variations

20

BOM level capabilities

21

End-item on-site maintenance strategy

22

End-item off-site maintenance strategy

23

BOM item costs

24

LRU renewal cost

25

Current/constant $$

26

Continuous Process Improvement [CPI] initiatives

27

Level of BOM in which Government owns IP

28

Employment of PSM/PSI PSE construct

29

Employment of ARFORGEN reset/reconstitute Product Support process

30

Funding sources included in analysis

31

Reparable parts Beyond Economic Repair [BER]/washout rate

32

Others

Product Support Business Case Analysis using Hypatia Tool

With over 35 years of data collection and development, GCI has created a software tool that encompasses all the above elements to create the outputs of a BCA study; it is called “Hypatia: A Scenario-Based, Product Support Life Cycle Financial Planning Software Tool.” Hypatia has enabled GCI to reduce the time to complete a Product Support BCA by 30%, and in turn has been able to reduce the cost of the study by the same amount. Another benefit of Hypatia has been its ability to deliver target life cycle Product Support costs that have been considered reasonably accurate by the recipients of the study. Traditional Product Support cost estimating tools such as COMPASS  are often inadequate to be employed in a BCA.

If you are interested in discussing how our proven Hypatia tool can be employed in your Product Support BCA study initiative, both for new programs and legacy programs, call a Giuntini & Co. SME at 570-713-4795 or visit us at www.giuntinicompany.com.

Product Support Financial Value Drivers. 2/10 – End User Product Utilization Rate.

Sep 24
2012

This post is the second of ten entries that will discuss product support financial drivers for solutions supplied by a commercial or military focused capital good Product Support Enterprise [PSE]. The 10 topics that will be discussed are the following:

  1. # of products employed by end-users
  2. End-user product utilization rate
  3. Product failure
  4. Environment in which end users engage the product
  5. Preventive maintenance processes employed
  6. Volatility of product technology
  7. Regulatory requirements
  8. Chronological age of the product installed base
  9. Life cycle stage of the product
  10. Manufacturer’s warranty coverage

The utilization rate of a product materially drives the financial impact of Product Support upon Total Ownership Cost [TOC]; an aircraft end-user that flies 500 hours/year will spend less on Product Support solutions than that of an aircraft end-user that flies 3,000 hours/year. The Product Support processes most impacted are correct/prevent unplanned failures and conformance to safety/regulatory requirements.

There are three primary ways in which a product’s utilization can be measured:

Period of use (i.e. 3 hours), frequency of use (i.e. 8 trips, 20 cycles), and output from use (i.e. 500 miles travelled, 1,000 pieces produced).

End user utilization rate for aircraft. Product support financial value drivers.

Choosing the appropriate utilization measurement can significantly impact the understanding of this key Product Support financial value driver. For example, if mileage is the only utilization measurement for a truck, and if the truck spends many hours idling, Product Support estimated costs based upon only mileage utilization may result in inaccurate forecasts; utilization measurement may sometimes require a blend of several factors.

The following four deployability types that can be employed to segment the planned utilization of a product, as well as be compared to a baseline utilization level:

  1. Preparing for deployment (i.e. garrison training); 1.00=baseline
  2. Non-deployable (i.e. schoolhouse training); ~1.25 of baseline
  3. Deployed (i.e. combat, humanitarian); ~2.00 of baseline
  4. Stored for future deployment (i.e. advanced deployed); ~.05 of baseline

Recently I delivered a weapons system Product Support Business Case Analysis [BCA] to a TACOM lifecycle management command program office in which the products were to be employed in all of the four above deployability types. The product studied was to be fielded over a 6 year period, but the distribution of the product’s deployability types had yet to be decided, but regardless, I had to estimate the impact of Product Support upon TOC in order to deliver my Business Case Analysis.

EOD team and product support

Given several known and unknown factors, I applied the following distribution of the products to be fielded for each period that a product was in-service: 70% preparing for deployment, 10% non-deployable, 15% deployed and 5% stored for future deployment. Using the variance factors from the baseline, the utilization of all the fielded products from the baseline was calculated as 1.15= [(70%*1.00) + (10%*1.25) + (15%*2.00) + (5%*.05)]. This weighted cost factor was applied to all processes that were driven by product utilization. For example, if the utilization baseline was 1,000 hours year, then a 1.15 weight factor would drive the annual utilization rate for each fielded product to be 1,150 hours.

Knowing that the Mean Time Between Failure [MTBF] was 2,000 hours and the weighted utilization was 1,150 hours/year and that the average cost of a repair was $2,000, I could estimate that the annual Product Support cost for the correct-failure Product Support process per fielded product was $2,875= [(1,150hrs/2,000hrs)*$5,000]. This was a simplified calculation, but it provides an overview of how utilization impacts Product Support costs.

Hypatia©, a Giuntini & Company financial software tool, provides a highly automated means of calculating the above and other product support financial value drivers, as well as an effortless way of being able to change any utilization assumption and immediately understand its impact upon total ownership costs.

 

Product Support Financial Value Drivers. 1/10 – Number of Products Employed by End-Users.

Sep 23
2012

This post is the first of ten entries that will discuss product support financial drivers for solutions supplied by a commercial or military focused capital good Product Support Enterprise [PSE]. The 10 topics that will be discussed are the following:

  1. # of products employed by end-users
  2. End-user product utilization rate
  3. Product failure
  4. Environment in which end users engage the product
  5. Preventive maintenance processes employed
  6. Volatility of product technology
  7. Regulatory requirements
  8. Chronological age of the product installed base
  9. Life cycle stage of the product
  10. Manufacturer’s warranty coverage

The first financial value driver – the number of products that are in the hands of the end-user – is THE biggest driver of all. Put simply, the more products delivered to end-users, the more Product Support required. It is always surprising to me that OEMs often do not know the quantity of their products that are in the hands of end-users. Almost all OEMs are focused upon production, but few are focused upon Product Support solutions.

number of products employed is the most important part of a product support enterprise

Working recently with one construction equipment OEM, I sat down with their leadership to discuss areas of revenue/profit opportunities in Product Support. Leadership was gloating that Product Support revenue had been increasing at 15%/year for the last 4 years. I asked them how much was their installed base changing for their products, but they couldn’t answer my question. So, I asked them to give me their warranty files and I did a quick and dirty analysis and I found that their installed base was growing at a 25%/year rate. When I plotted the results and told them that they had foregone 40% of the potential Product Support revenue, they were crushed…but I got them to be angry at themselves for not seeing all the money that were leaving on the table, and the OEM became much more proactive in assuring that they got “their fair share” of revenues generated from solutions delivered by a PSE.

To give some OEMs slack, they often employ authorized distributors to sell their products directly or indirectly to end-user; the OEMs don’t know when their products are actually sold and to whom.

Lesson learned: OEMs must know the current and future size of their installed base in order to develop a Product Support life cycle financial plan…and as a result of not knowing the size of their installed product based, especially for out-of-production product lines, the typical OEM captures only an estimated 15% of the value of all the solutions supplied by a PSE.

The next product support financial value driver entry coming in a few days.

Learn how to maximize your profits using Hypatia financial cost analysis forecasting software from Giuntini & Co. 

info@giuntinicompany.com

Tel: 570-713-4795