Product Support Financial Value Drivers. 6/10 – Volatility of Product Technology

Nov 04
2012

This post is the sixth 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 Financial Value Drivers

The current business model for OEMs is to seek a problem being encountered by an organization and to configure a hardware/software solution that affordably and effectively addresses a resolution to the problem. For example, a warfighter requires, within a 6-month period, a communication system that can access satellite transmissions on-the-move for a period of 20 years. The OEM awarded the contract chooses to employ a suite of bleeding-edge Commercial Off The Shelf [COTS] items and integrates all the pieces into a Design-To-Order solution. Great; the warfighter gets their solution quickly and the OEM can “call it a day.” But now comes the fun part. The Product Support Strategy [PSS] for this COTS-based solution must employ a process that modifies the configuration of the solution based upon future Diminishing Manufacturing Sources Material Shortages [DMSMS] challenges; what is currently bleeding-edge, will most probably have a cold commercial supply chain within 3-4 years.

Understanding how the source-of-design impacts Total Ownership Cost [TOC] is often not fully understood. An OEM’s employment of COTS items enables access to a hot supply chain in which development costs have been amortized by the manufacturer; item acquisition costs can often be 30-50% less than that of a developmental item with the same capabilities. Also note that the reliability of a COTS item can be 3-4 fold higher than that of a developmental item. All-in-all the production costs of a COTS-centric solution is financially attractive, but Product Support life cycle costs can be significant enough to offset the production savings.

For example, if a COTS item is to be modified, due to DMSMS issues every 4 years and there is a planned 20 year product life, that indicates that 4 to 5 modifications will have be performed during the period that the solution is in inventory. Note that upon the insertion of these modifications, capabilities enhancements may occur, but that is strictly a by-product of the activity.

From personal financial analytics experience working on many systems, I have in almost all situations observed that DMSMS-driven modification costs can constitute the number one or two ranked Product Support cost driver. Remember that Product Support constitutes a plurality of TOC, thus modifications to COTS-centric solutions are often within the top ten cost drivers of TOC.

Product Support Financial Value Drivers

Other issues to be considered that will impact financial performance due to technology volatility, is how the modification process will be performed. There are several alternatives (this is not an all inclusive listing), each with their own cost drivers:

  • Block-mod in which all end-items are inducted into the modification process at a depot within a short period of time
  • Block-mod in which all end-items are inducted into the modification process in the field via an exchange program, within a short period of time
  • Modify-as-failed in which reparable items, when inducted in a repair process, will also be modified
  • Modify-bundled-with-other in which an end-item when inducted into a process such as reset, overhaul or other end-item process, the modification will be employed when the end-item has been disassembled; logic is that as long as the end-item is apart, there is no additional labor required for installing the modification.

Each of the above impacts technician labor costs to remove and replace, transportation costs, facility costs, indirect personnel costs and many other costs. Also note that each alternative will impact Materiel Availability [Am].

Any financial analytics of the Product Support life cycle must include a rigorous review of modification expenditures regardless of the “color of money.” Technology volatility provides many challenges, but with insightful life cycle planning unfavorable performance risks can be mitigated.

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. Hypatia is also a proven, trusted and highly effective tool for assisting in the development of product support business case analysis.

Product Support Financial Value Drivers. 5/10 – Preventive Maintenance Processes Employed

Oct 25
2012

This post is the fifth 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 Business Case Analysis – Product Support Financial Value Drivers

Preventive Maintenance [PM] is a Product Support process that attempts to avoid an unplanned failure event; it is typically described and recommended to be employed by an end-item maintainer in the maintenance manual generated by an OEM.

There are three key flavors of PM:

  1. Use-based (i.e. after every 1,000 cycle remove reparable item to be overhauled and re-installed)
  2. Period-based (i.e. every 6 months remove/dispose non-reparable part and replace with a new condition part)
  3. Condition-based (i.e. when consumable brake pad wears down to 1 inch thickness, remove/dispose and replace)

All the above actions lend themselves to dependent demand financial planning; all you need to know is the forecast of each of the PM drivers and you develop a lock on the financial impact of a PM schedule.

For example;

  1. A reparable item has a PM schedule of a removal every 1,000 hours of end-item use; the item is to be overhauled and re-installed
  2. The end-item’s utilization is forecasted to be 4,000 hours per year or a planned removal event every 3 months/4 times per year
  3. The estimated cost of an overhaul is $2,000; the annual cost of the PM schedule is $8,000 (4 removals*$2,000).

The great tragedy of PM is that once established, there is often little adjustment to its frequency; comparing real-world failure experience and that of the PM schedule. The exception is when there is a major reliability issue which requires an immediate PM schedule adjustment. This lack of proactive adjustment, either up or down, can have a major impact upon Product Support financial value drivers.

Note that there are some PM schedules that are safety related and are required by Governmental regulations to be performed, but in almost all cases the PM schedule can be changed upon Governmental approval.

The following is an example of a project I designed and managed which was able to ultimately reduce the frequency of PM events by 50% over a 5-year period. There were about 100 non-reparable items that were selected that had PM scheduled removals every year. A slow frequency adjustment was employed in order to mitigate any unfavorable Materiel Availability performance risks; if actual unplanned failures increased, then we could quickly recover by going back to the original PM schedule frequency.

Product Support Business Case Analysis – Product Support Financial Value Drivers

In the project’s first year, the PM schedule of all 100 items was changed from 12 months to 13 months; an 8% reduction in removal frequency. The project team then waited 1 year to review failure analysis and end-user issues regarding these parts; there was no impact on the end-user community. In year two, the team stretched the PM schedule to 15 months; a 15% frequency reduction. Year three the PM schedule was moved to 18 months, with year four to 21 months and finally year five to 24 months; with a total decrease in PM schedule frequency of 50% ((24-12)/24). These 100 items drove 10% of the Total Ownership Cost [TOC]; the reduction in PM frequency resulted in a weighted 5% (50% reduction * 10% of cost) reduction in TOC.

The use of scenario based Product Support financial planning tools enables “what if” calculations on the changing of the frequency of PM schedules. There are big reductions in TOC to be harvested, but it has to be slow and methodical in its execution.

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. Hypatia is also a proven, trusted and highly effective tool for assisting in the development of product support business case analysis.

Product Support Financial Value Drivers. 4/10 – Operating Environment in Which End-Users Engage the End-Item

Oct 19
2012

This post is the fourth 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 Financial Value Drivers

There are many attributes of an operating environment that can have an impact upon Product Support financial drivers and performance. For some end-items, the impact is quite material, and for others not as much. OEMs, when designing their products, are quite aware of the operating environment of their end-items, and in turn adapt their design to minimize the operating environment’s impact Total Ownership Cost [TOC]. The OEM still will acknowledge that there will be financial implications, that can be material, especially if the instructions in their maintenance manuals are not followed.

There are 6 factors impacting Product Support financial driver performance:

1. Temperature
The majority of products are designed to meet their performance attributes within a range of temperatures. For example, aircraft, during the certification process, are tested in extreme cold temperatures, as well as in extreme hot temperatures. This assures end-users that all subsystems can function within a wide range of operating environments.

Where Product Support financials are impacted is when the end-user employs the end-item outside the temperature design range for any extended period of time. One example is a Class 8 truck designed for the North American market is exported to sub-Sahara Africa where temperatures can exceed that of the design threshold. Reliability issues can surface quickly resulting in much downtime.

Another example is an electronic device requiring cool external temperatures in order to offset the high temperatures generated by the device. Without the proper conditioning of air, reliability can materially decline.

2. Humidity
This is a major product support financial driver for the Product Support processes engaged in the repair of structural items. Again OEMs design attributes that attempt to minimize the impact of humidity. For example, Boeing in their new 787, reduced the impact of humidity on the corrosion of aluminum, by replacing large sections of the aluminum airframe with non-corroding fiber composites. Vehicle OEMs have dramatically reduced the impact of humidity through higher tech paints and their application.

The employment of preventive measures to assure that humidity does not corrode an end-item is the preferred solution for this area.

3. Particles
Sand, dust, dirt and other particles can cause the employment of multiple Product Support processes; from reliability issues related to mechanical parts becoming impeded, to cosmetic issues of a “dirty” end-item, and to items wear and tear being accelerated as a result of grinding caused by sand. Again OEMs are quite aware of these issues and indicate courses of action in their maintenance manuals, but it doesn’t preclude the end-user from being financially impacted by the presence of these particles due to the preventive maintenance activities that are performed on a periodic basis.

4. Fluids
The effective management of the impact of salt water, chemicals, oils and other fluids can improve Product Support financial performance. For example end-items employed in the transportation field, trucks, aircraft, ships and trains all have extensive Product Support programs to minimize the financial impact of salt water; from fresh water washing to periodic disassembly/clean/reassembly. Manufacturing equipment is often subjected to chemical and oil exposure requiring the employment of preventive Product Support processes.

5. Hours of Operation
For certain end-users they can only operate their end-items during specific times of the day; could be safety related, pollution related or noise related. For example trucks cannot idle in an urban area after 2200, or aircraft cannot depart after 2100, or building construction activities cannot occur during the week-end. Whatever the situation, a Product Support Enterprise must deliver solutions that adapt to these constraints. Often Product Support processes will be performed during the hours that the end-user cannot employ its end-items; for labor this can result in higher costs related to shift differentials, or requiring more Product Support parts safety stock, due to parts suppliers not being available to delivery items during off-hours.

6. End-Item Operator
Challenges in adopting to a new technology, loss of experience due to high operator turnover, employee malfeasants (i.e. union “thuggery”) and other elements related to an end-item operator’s unfavorable impact Product Support financial performance is a continuing occurrence to be dealt with in developing solutions for a Product Support Enterprise. Improved operator training programs, user-friendly operator manuals, electronic monitors identifying end-user abuse and other resources can be employed to mitigate the additional financial impact of these challenges.

Product support financial value drivers

Understanding how an end-item is operated in developing a scenario-based Product Support life cycle financial plan or product support business case analysis is just one more element to consider. My recommendation is to have an “operating environment” weight in your Cost Estimating Relationship [CER] input; you might not know exactly how changing operating environments may impact you, but you can take a guess and once real data sets can be captured, you will have a place holder to make those changes.

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. Hypatia is also a proven, trusted and highly effective tool for assisting in the development of product support business case analysis.

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 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.

 

OEM PSE Profits -The Secret The Industry Doesn’t Know About

Jul 06
2010

Commercial OEMs create from 15% to 40% of their profits as a result of the revenues generated from each Product Support Enterprise (PSE) that employs their product. A PSE engages all the processes employed by a product end-user to: meet materiel availability levels, increase maintainability, assure capability, grow reliability, improve deployability and decrease costs. The remainder of an OEM’s profits is primarily derived from the sale of new-condition products, with the exception being those OEMs that have a financial arm.

When I have had nothing to do at 0400 on a Sunday morning, I have used that time “wisely” to dig into the Quarterly (10Q) or Annual (10K) Security and Exchange Commission (SEC) financial reports of capital goods OEMs in order to better understand the financial impact of PSEs upon their balance sheet….but I have been highly “disappointed” when virtually no information could be found to satisfy this longing of mine! I have reviewed close to 200 OEMs and I have developed a list below of only 13 OEMs who are willing to acknowledge, in even a minor detail, the existence of investments employed in PSEs.

When an OEM truly believes that being proactively engaged in PSEs is material to their financial health they often segment their balance sheet investments employed for PSEs. Note that for some OEMs, creating opaqueness in being engaged with PSEs is by design; they often do not want to indicate to their competitors that their business model is more like the razor-and-razorblade then one that focuses on the sale of the razor…but that is another story.

# OEM or Key Supplier Sector Financial Statement Description
1 AGCO Farm Balance Sheet: Current Assets Repair and Replacement Parts
2 NCR Office Balance Sheet: Current Assets Service Parts
3 Pitney Bowes Office Balance Sheet: Current Assets Supplies and Service Parts
4 Cognex Mfg. Automation Balance sheet: Long-term Assets Service Inventory
5 Ciena Data/Voice/Network Balance sheet: Long-term Assets Maintenance Spares Inventories
6 Diebold Specialty Balance Sheet: Current Assets Service Parts
Balance sheet: Long-term Assets Rotable Parts
7 KLA-Telcor Mfg. Semiconductor Balance Sheet: Current Assets Customer Service Parts
8 Rofin-Sinar Technologies Mfg. Automation Balance Sheet: Current Assets Service Parts
9 Faro Technologies Mfg. Automation Balance sheet: Long-term Assets Service Inventory
10 PAR Technologies Transactions Balance Sheet: Current Assets Service Parts
11 Terex Construction Balance Sheet: Current Assets Replacement Parts
12 Applied Materials Mfg. Semiconductor Balance Sheet: Current Assets Customer Service Spares
13 Wabash National Transportation: Trucks/Engines Balance Sheet: Current Assets Aftermarket Parts

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