Cost Avoidance Based Return on Investment (ROI)

The determination of the ROI allows managers to include quantitative, readily interpretable results in their decision-making.  While the formulation of an ROI associated with investing money in a financial instrument is straightforward, the calculation of an ROI associated with the generation of an increase in the customer base, cost savings, or a future cost avoidance is less straightforward. 

ROI is a common performance measure used to evaluate the efficiency of an investment or to compare the efficiency of a number of different investments. To calculate ROI, the benefit or gain associated with an investment is divided by the cost of the investment and the result is expressed as a percentage or a ratio:

                (1)

An ROI of 0 represents a break-even situation--that is, the value you get back exactly equals the value you invested.  If the ROI is > 0, then there is a gain; if the ROI is < 0, there is a loss.  Equation (1) is relative to the no-investment case (e.g., burying the cash in the ground).

Cost Avoidance ROI
Cost avoidance is a reduction in costs that have to be paid in the future.  Cost avoidance is commonly used as a metric by organizations that have to support and maintain systems to quantify the value of the services that they provide and the actions that they take.  See my May 31, 2017 Blog post for more about cost avoidance.

Cost avoidance ROIs are a bit more difficult to calculate than the financial ROIs.  As an illustration, consider the determination of an ROI for the addition of some sort of improvement to a system.  This improvement will result in a future cost avoidance (maybe it reduces the future maintenance costs).  Is the investment in the improvement worth it? 

To formulate the ROI for adding this improvement to a system, we first have to decide what we are measuring the ROI relative to.  For our example, we could measure the ROI relative to maintaining the system without the improvement.  The ROI from Equation (1) becomes, [1]:

                             (2)
where

C_wo = the life-cycle cost of the system managed without the improvement

C_w  = the life-cycle cost of the system managed with the improvement

I_w    = the investment in the improvement

If C_wo is larger than C_w then there is a positive ROI.  The nice thing about Equation (2) is that the numerator is the difference of life-cycle costs, i.e., one only has to be able to determine the difference between the two cases (the actual values of C_wo and C_w, which are much harder to determine, are not needed) – see my November 2016 blog post on absolute vs. relative costs.  Note that C_w is a life-cycle cost that therefore includes I_w within it.

Another challenge with this ROI calculation is determining the investment cost (the denominator of Equation (2)).  For cost avoidance cases it is not always clear what costs are the investment and what costs are the result of an investment.  For example, if my improvement converts corrective maintenance actions (due to system failures) to preventative maintenance actions (taken before failure), the improvement could result in more (but less expensive) maintenance actions and the need for more spare parts.   Is the cost of the extra spare parts accounted for in the investment (I_w)?  The extra spare part cost in this case would not be included in the investment cost because the extra spare parts are the result of the improvement (i.e., the result of the investment) and are reflected in the life-cycle cost C_w.

General Comments about Calculating ROIs

1. Constructing a business case for an activity does not necessarily require that the ROI be greater than zero; in many cases, value is not fully quantifiable in monetary terms, or the activity is necessary in order to meet a system requirement that could not otherwise be attained, such as satisfying a system availability requirement.  
2. The calculation of ROI can be modified to suit the situation depending on what you include as returns and investments.  This means that ROIs are easy to calculate but can be deceivingly difficult to get right.  Financial investment ROIs are straightforward, but when evaluating the ROI of a cost savings, market share increase, or cost avoidance, the difference between costs that are investments and those that are returns is blurred.
3. ROIs have to be relative to some clearly defined situation.  Most often ROI for cost avoidance is measured relative to “business as usual”, i.e., the management of the system if no investment was made.
4. ROI is not independent of the cost of money (discount rate).  The discount rate will impact the life-cycle costs in Equation (2).
5. ROI can fool you, be careful.  The largest ROI solution may not represent the best option for an organization – see my February 6, 2020 Blog post.

[1] Feldman, K., Jazouli, T. and Sandborn, P. (2009). A methodology for determining the return on investment associated with prognostics and health management, IEEE Transactions on Reliability, 58(2), pp. 305-316.

Should-Cost

Should-cost is the result of cost modeling done by a customer to determine what it should cost them to purchase a product, service or system support [1].  Should-costing is based on the customer’s accounting and their understanding of the product or service. When a customer knows a product or service’s should-cost, then they know what they should pay for it.

Why is should-cost a thing?  For many common products, market competition protects the customer from significant overpayments (assuming the customer shops around or allows the market compete for their business).  However, for unique products and services (e.g., military programs, contracted services, etc.), where there is no market competition that sets prices at fair levels, knowing the should-cost is critical when a customer wishes to guard against overpayment.

A common alternative to should-costing is strategic sourcing, which is the process of comparing price quotes from different sources.  Alternatively, should-costing would start from an analysis of labor, materials, overhead, profit margin, etc., to estimate what the price should be.  Strategic sourcing is used for commodity items (e.g., if you are going to buy a washing machine, you shop around), while should-costing is used for highly engineered systems and services where there are few suppliers (e.g., a new aircraft carrier).  A commonly used example is the purchase of a car.  A strategic car buyer goes to multiple dealers to see who will give them the best price.  A should-cost buyer researchers the dealer’s invoice price and how dealers determine their markups and then tells the dealer what price they will pay for the car.

The car buying example aside, in the real world should-cost should be thought of as leverage, not a prediction [2].  Any should-cost analysis you perform will be wrong – there are thing you simply don’t know.  Most people have the expectation that the predictive power of should-cost alone will have the strength to cause the negotiated price to equal the price determined from the should-cost estimate - this is a great goal, but it is not typically realistic.  The point of should-cost is that it gives you leverage to push a quoted price toward your should-cost estimate.

[1] Carter, A. B. and Mueller, J. (2011).  Should cost management: Why? How?, Defense AT&L: Better Buying Power, Sept-Oct, pp. 14-18.

[2] Hiller, E. A. (2012), “Your Should-Cost Number is Wrong, But it Doesn’t Matter,” Industry Week, October 21, http://www.industryweek.com/procurement/your-should-cost-number-wrong-it-doesnt-matter  Accessed July 17, 2017.

Cost Avoidance vs. Cost Savings

In the case of manufacturing processes, it is reasonable to characterize the value of process, equipment and yield changes as cost savings.  However, the value of life-cycle management activities (i.e., sustainment) is usually quantified as a cost avoidance.  “Cost avoidance is a cost reduction that results from a spend that is lower than the spend that would have otherwise been required if the cost avoidance exercise had not been undertaken” [1].  A simpler definition of cost avoidance is a reduction in costs that have to be paid in the future to sustain a system [2].  

Cost avoidance is commonly used as a metric by organizations that have to support and maintain systems to quantify the value of the services that they provide and the actions that they take.  These organizations do not like to use the term “cost savings” since a savings implies that there is unspent money, whereas in reality there is no unspent money, only less money that needs to be spent.  Another way to put it is, if you told a customer that you saved 100 dollars, the customer could ask you for the 100 dollars back; if you told a customer you avoided spending 100 dollars there is no 100 dollars to give back.

Unfortunately, making business cases based on a future cost avoidance argument is often more difficult than business cases that are based on cost savings, therefore, there is a greater need to be able to provide detailed quantification of sustainment costs.  Requesting resources to create a cost avoidance is not as persuasive as making a cost savings or a return on investment argument. 

[1] Ashenbaum, B. (2006). Defining Cost Reduction and Cost Avoidance, CAPS Research.

[2] Sandborn, P. (2017). Cost Analysis of Electronic Systems, 2nd edition, World Scientific.

Resilient Systems and Resilient Design

We hear the word "resilience" a lot these days.  It's a word that's ripe for misuse and vagueness.  

There is a general agreement that resilience is the intrinsic ability of a system to resist disturbances.  Another equivalent definition of resilience is the ability to provide required capability in the face of adversity (sometimes referred to as disaster recovery).  Resilient design is about managing the ubiquitous uncertainties that constrain current design practices as well as finding ways to overcome an imperfect understanding of system requirements that lead to fragile and ineffectual system designs.

The definitions above are fine, but the real question is what is the “scope” of the system – and this is where views vary.  In this blog we focus on electronic products and systems, however, the concepts of resilience and resilient design are more prevalent in the building construction, architecture, and communities design space.

When you talk about resilient systems, several disciplines think they have a handle on the problem.  The control systems folks think that this is their domain, the optimization folks, the PHM (system health management) folks, the reliability engineering folks, sustainability folks, the system engineering folks, machine learning, artificial intelligence, … In my experience, none of these disciplines (with the possible exception of some system engineers) really grasps the total scope of resilience.  Every discipline wants to gather resilience under their umbrella and grant themselves ownership of the problem space based on their narrowed definition of what a system is.

In my opinion, designing resilient hardware and software (which is the focus of most resilient system design activities) is necessary but not sufficient for creating resilient systems.  For a system to be resilient requires:

• reliable (or self-managing) hardware and software
• a resilient logistics plan (including supply chain and workforce management)
• a resilient contract structure
• resilient legislation or governance (rules, laws, policy)
• a resilient business model

One might also include within all of the above aspects, a resilience to changes in the end-of-support for the system.  For many systems, the end-of-support is a moving target that is extended ("life extensions") during the use of the system.

This represents a somewhat broader scope than what is generally articulated in the engineering literature, however, in practice, neglecting any of these elements potentially creates a legacy system with substantial (and potentially untenable) life-cycle support costs.

Although the discussion in this blog has an electronic product/system focus (our "scope").  Resilient design can certainly be applied to other things, e.g., buildings, communities, furniture, information technology, websites, health care, etc.  In this broader world one could consider adding the following to the bullets above:

• culturally resilient (does the system transcend cultures and culture changes)
• environmental resilience (sustainability)
• resilience to climate change

Obsolescence Definition

Obsolescence isn’t an uncommon word – a Google search finds more than 5.7 million entries.  However, in the engineering design and product support context it has several different meanings.  First, the dictionary definition of obsolescence is the condition of no longer being used or useful. This definition is not inconsistent with the definitions that follow, but it is also not specific enough to provide much value in a product support context.

Planned Obsolescence – we hear this a lot.  Planned obsolescence refers to products (usually consumer products) that are designed to be rendered obsolete by the introduction of another product that has more functionality, higher performance, smaller size, and/or costs less.  Planned obsolescence is a strategy sometimes followed by companies that design and manufacture consumer electronics.  Planned obsolescence is often confused with “made-to-break” products [1].  Made-to-break products are products that are intentionally designed or manufactured to fail at some point in the future (nominally after the warranty has ended) forcing the customer to purchase a new product.

Sudden or Inventory Obsolescence - Sudden or inventory obsolescence occurs when the product design or system part specifications changes such that existing inventories of components (e.g., spare parts) are no longer required.  This type of obsolescence has been studied in the operations research literature.

  

DMSMS or Procurement Obsolescence – DMSMS (Diminishing Manufacturing Sources and Material Shortages) obsolescence is the loss or impending loss of original manufacturers of items or suppliers of items or raw materials [2].  This type of obsolescence is caused by the unavailability of technologies or parts that are needed to manufacture or sustain a product.  DMSMS means that due to the length of the system’s manufacturing and support life and possibly unforeseen life extensions to the support of the system, the necessary parts and other resources become unavailable (or at least unavailable from their original manufacturer) before the system’s demand for them is exhausted.  DMSMS obsolescence is the opposite of sudden or inventory obsolescence.

Planned obsolescence is a strategy followed by product manufacturers, DMSMS obsolescence is a situation forced upon system sustainers (these two types of obsolescence are not the same).  DMSMS obsolescence may be the result of the planned obsolescence of products that drive the market for specific types of parts, e.g., if your long field life system depends on the same parts that cell phones depend on, then planned obsolescence strategies for cell phones drive the DMSMS obsolescence of the parts you depend on.  The “poster child” for DMSMS type obsolescence is electronic parts.  For some electronic parts the planned obsolescence of particular products is the primary driver behind the part’s obsolescence, but the discontinuance of parts is also simply the result of falling demand that makes it more profitable to dedicate manufacturing resources to other products, or changes in ownership of product lines or companies.

All of the types of obsolescence defined above are relevant for real product and system segments.  While it is easiest to think of these as impacting hardware, obsolescence also has a significant impact on software [3], materials, and even the human workforce [4]. 

[1] Slade, G. (2006). Made to break: Technology and obsolescence in America, Harvard University Press.

[2] Sandborn, P. (2008). Trapped on technology's trailing edge, IEEE Spectrum, 45(1), pp. 42-45, April.

[3] Sandborn, P. (2007).  Software obsolescence - Complicating the part and technology obsolescence management problem, IEEE Transactions on Components and Packaging Technologies, 30(4), pp. 886-888, December.

[4] Sandborn, P. and Prabhakar, V.J. (2015).  Forecasting and impact of the loss of the critical skills necessary for supporting legacy systems, IEEE Transactions on Engineering Management, 62(3), pp. 361-371, August.

2nd Edition of Cost Modeling Book Published

This book provides an introduction to cost modeling for electronic systems that is suitable for professionals involved with electronic systems development, management and sustainment, and advanced undergraduate and graduate students in electrical, mechanical and industrial engineering.

This book melds elements of traditional engineering economics with manufacturing process and life-cycle cost management concepts to form a practical foundation for predicting the cost of electronic products and systems. Various manufacturing cost analysis methods are addressed including: process-flow, parametric, cost of ownership, and activity based costing. The effects of learning curves, data uncertainty, test and rework processes, and defects are considered. Aspects of system sustainment and life-cycle cost modeling including: reliability (warranty, burn-in), maintenance (sparing and availability), and obsolescence are treated. Finally, the total cost of ownership of systems, return on investment, cost-benefit analysis, and real options analysis are addressed.

The book includes a large number of  quantitative examples solved in the text, over 230 problems (detailed solutions to over 90% of the problems are available to practitioners, researchers and instructors using the book in classes), and over 300 references.

http://www.worldscientific.com/worldscibooks/10.1142/10241

Table of Contents (571 pages)

Chapter 1 Introduction

Part I Manufacturing Cost Modeling
Chapter 2 Process-Flow Analysis
Chapter 3 Yield
Chapter 4 Equipment/Facilities Cost of Ownership (COO)
Chapter 5 Activity-Based Costing (ABC)
Chapter 6 Parametric Cost Modeling
Chapter 7 Test Economics
Chapter 8 Diagnosis and Rework
Chapter 9 Uncertainty Modeling - Monte Carlo Analysis
Chapter 10 Learning Curves

Part II Life-Cycle Cost Modeling
Chapter 11 Reliability
Chapter 12 Sparing
Chapter 13 Warranty Cost Analysis
Chapter 14 Burn-In Cost Modeling
Chapter 15 Availability
Chapter 16 The Cost Ramifications of Obsolescence
Chapter 17 Return on Investment (ROI)
Chapter 18 The Cost of Service
Chapter 19 Software Development and Support Costs
Chapter 20 Total Cost of Ownership Examples
Chapter 21 Cost, Benefit and Risk Tradeoffs
Chapter 22 Real Options Analysis

Appendices
Appendix A Notation
Appendix B Weighted Average Cost of Capital (WACC)
Appendix C Discrete-Event Simulation (DES)

Index (over 900 entries)

More Than Acquisition Cost – F-35

Aircraft are “sustainment-dominated” systems.  These are systems for which the lifetime footprint significantly exceeds the footprint associated with making it [1].  In the case of aircraft, the footprint we are talking about includes cost.   Lockheed Martin’s official response to President-elect Trump’s recent tweet about out-of-control costs for the F-35 included the following statement [2]:

“The cost doesn't just include the acquisition price. Lockheed Martin and its industry partners are also investing in reducing the sustainment costs of the aircraft recognizing that much of the cost of owning and operating an aircraft is after it's delivered. We're investing hundreds of millions of dollars to reduce the cost of sustaining the airplane over its 30-40 year lifespan. We understand the importance of affordability and that's what the F-35 has been about.”

It is not uncommon for 70% of more of the life-cycle cost of a sustainment-dominated system (e.g., commercial and military aircraft, ships, power plants, and other high-cost, long-life items), to be incurred after the design, development, and procurement of the system.  These life-cycle costs can include: operation, maintenance, upgrade, spare parts, testing, training, documentation, unplanned life extensions, obsolescence management, and many more things that contribute to the logistics footprint of a complex system.  As an example, consider obsolescence management [3].  The majority of the electronic systems in the aircraft are not constructed from “custom” parts, but rather from the same parts that are in consumer products (phones, computers, etc.).  Most of these parts have a procurement life of a few years at best, but an airplane has to be supported for 30+ years.  Sourcing these parts after they are discontinued (obsoleted) by their original manufacturer can be expensive and risky.  The problem is that aircraft are safety-critical systems that are highly qualified and certified, replacing obsolete parts with newer versions of parts may be a very expensive proposition (may require re-qualification of critical subsystems or even the entire aircraft); alternatively using aftermarket suppliers exposes systems to the risk of counterfeit parts [4]. Obsolescence is only one example of how high procurement cost systems can become even more (much more) expensive to sustain.

[1] Sandborn, P. and Myers, J. (2008). Designing engineering systems for sustainability, in Handbook of Performability Engineering, K.B. Misra, Editor, pp. 81-103 (Springer, London).
[2] http://www.zerohedge.com/news/2016-12-12/lockheed-responds-trump-tweet
[3] Sandborn, P. (2008). Trapped on technology’s trailing edge. IEEE Spectrum, 45(1), pp. 42-45.
[4] Pecht, M. and Tiku, S. (2006). Electronic manufacturing and consumers confront a rising tide of counterfeit electronics. IEEE Spectrum 43(5), pp. 37-46.