This case study analyzed alternatives to reduce food waste sent to landfills. The researchers developed decision models including TOPSIS and SAW to evaluate alternatives. Based on the analysis, re-purposing/re-using food waste was identified as the best solution as it is flexible, meets stakeholder requirements, is cost-effective, and can be immediately implemented.

1. CASE STUDY FINAL PRESENTATION
Nouf Aljalal
Abdulaziz Almaarik
Matthew Mycroft
Rama Wusirika
SELP 552
Professor Rosalind Lewis
April 30th, 2012

2. Research Plan
• Case Study Objective: Reduce the Amount of Food Waste Sent to
Landfills
– Null Hypothesis: Food Waste Sent to Landfills Cannot Be Reduced
– Alternate Hypothesis: Food Waste Sent to Landfills Can Be Reduced
• Methodology
– Analysis of Alternatives
• What Technologies Are Out There ?
• Can These Technologies Reduce Waste ?
• Which Is The Most Effective ?
– Develop Selection Criteria
– Develop Screening Criteria
– Cost/Benefit Analysis
• What Are The Cost of These Technologies ?
• What Is the ROI of These Technologies ?
• Do The Savings Justify The Cost ?
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3. Research Plan
• Objective: Develop Requirement Analysis Plan
– Performance Requirements
• What Makes A Technology Effective or Ineffective?
– Functional Requirements
• How and Under What Conditions Must The Technology Perform Under
– Architectural Constraints
• What Are The Limitations That Make A Technology Effective or Ineffective
– Measures of Performance
• How Will We Measure The Effectiveness of the Technology?
– Verification Criteria
• How Will We Verify That A Technology Is Working?
• Resources:
– Written Articles, Textbooks
– Current Company Technology Review
– Applicable Laws and Regulations
• FAO
• USDA
– From Where
• Library
• LMU
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4. Research Plan- Risks
• Risks
– Technical Risks
• No Technology Can Be Found That Meets the Performance Criteria
– Cost Risk
• The Technology Is Too Expensive To Develop Or Implement
– Schedule Risk
• The Technology Cannot Be Implemented In A Practical Timeframe To Make A Difference
– Programmatic Risk
• Decisions At Higher Authorities Levels (Government or Industry) Could Render Technology
Useless
• Funding Issues
• Dealing with Setbacks/Hurdles
– Only Chose Selections Determined to Be Measurable
– Difficulty with Obtaining Quantitative Data: Took More Qualitative Look
– Evaluation of Multi-Criterion Solutions:
• TOPSIS and SAW
• Build Quantitative Scorecard for Qualitative Multi-Criterion Solution
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5. Research Plan- Schedule
DATE DELIVERABLE
Week of Mar 20 Complete Schedule
Week of Mar 27 Start WBS and Measures of Performance
Analysis
Week of Apr 3 Update Risk
Address All Notes from First Presentation
Hold Meeting Apr 2
Week of Apr 10 Alternative Task: Complete Interviews
with Restaurant Owner and Sodexo
Start Cost/Benefit Analysis
Start Modeling
Week of Apr 17 Start Draft Presentation
Finish Cost Benefit Analysis
Address All Notes from Second
Presentation
Week of Apr 24 Complete Presentation and Paper
Practice Presentation
Week of May 1 Give Presentation
Turn in Paper

6. METHODS / ANALYSIS
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7. THE DECISION PROCESS
STAKEHOLDER
STAKEHOLDER
Output MEASURES
MEASURES
REQUIREMENTS
REQUIREMENTS OF
OF
DEFINITION
DEFINITION EFFECTIVENESS
EFFECTIVENESS
PROCESS
PROCESS
Input REQUIREMENTS
REQUIREMENTS Output MEASURES OF
MEASURES OF
ANALYSIS
ANALYSIS PERFORMANCE
PERFORMANCE
PROCESS
PROCESS
ANALYSIS OF ALTERNATIVES – Decision Models,
ANALYSIS OF ALTERNATIVES – Decision Models,
Effectiveness Comparison, Cost/Benefit Review
Effectiveness Comparison, Cost/Benefit Review
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8. DECISION ANALYSIS METHODS
DECISION MATRIX MODELS
TOPSIS – “Technique for order preference using similarity to the ideal
solution [12].”
 Goal Based
 A Form of Multi-Criteria Decision Analysis
 Computes “Closeness” of an Alternate to the Performance Poles
SAW – “Simple Additive Weighting [13]”
 Goal Based
 A Form of Multi-Criteria Decision Analysis
 Based on Weighted Averages “Scoring”
 Perhaps One of the Most Simple Methods of Decision Analysis
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9. DECISION MATRIX MODELS
There are two types of inputs that can be applied to a decision matrix model:
Tangible – “Definite, not vague or illusive”
•Cost
•Time
•Numerical Measures of Performance
Intangible - “Indefinite, vague”
•Better Than / Worse Than
•Good / Better / Best
•Low / Average / High
In order to conduct mathematical analysis on the decision matrix, we must
convert the intangibles in the decision matrix to numbers.
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10. DECISION MATRIX MODEL
Intangibles Scale [12]
(Saaty’s Scale of Pairwise Comparisons)
Cost to
Time Cost Implement Spent Funds Impact Profit Feasibility
0
Very
10+ Very High Large Increase 1 Small/None Large Decrease Definitely No
5-10 High Increase 3 Small Decrease Probably No
1-5 Yr Average No Change 5 Average No Change Maybe
< 1 Yr Low Decrease 7 Large Increase Probably Yes
Now Very Low Large Decrease 9 Very Large Large Increase Definitely Yes
10
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11. The Food Waste Decision Matrix
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12. Conversion of Decision Matrix to Matrix of Numbers
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13. Normalization & Weighting of the TOPSIS Matrix
NORMALIZING THE DECISION MATRIX [12]
The matrix may contain incommensurate units. Thus, it is
normalized to create a dimensionless table of numbers:
Rij = Xij / Sq. Root (Sum, i = 1…n of Xij2)
WEIGHTING THE DECISION MATRIX
As different criteria may vary in importance (as determined by
the stakeholders), each criteria is given a weight and each
column of the decision matrix is multiplied by its
corresponding weight to obtain a weighted decision matrix.
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14. The Weighted and Normalized Matrix
The decision matrix has now been normalized and weighted. As part of the
TOPSIS analysis, it is important to determine the “Best” (Closest to Ideal) and
“Worst” (Furthest from Ideal) value in each column (note that the columns are
measures, and we are selecting the best and worst solutions for that independent
measure).
Vj* = BEST
Vj- = WORST
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15. TOPSIS ANALYSIS
The next step in TOPSIS analysis is to determine the separation measure from the
ideal and negative ideal solutions.
Separation Measure from Ideal Solution [12]:
S* = Ideal Sq Root (sum of squares for j = 1….m of (vij-vj*))
Separation Measure from Negative Ideal Solution [12]:
S- = Sq Root (sum of squares for j = 1….m of (vij-vj-))
Once the separation measures are determined, we can calculate the relative
closeness to the ideal solution: Ideal Solution
Closeness to the Ideal Solution [12] = Si - / (Si * + Si -)
Si*
Negative
Ideal
Solution
Si- Examined
Alternative
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16. TOPSIS RESULTS
TOPSIS DECISION
MATRIX RESULTS
Relative
S* S- Closeness Solution Rank
NO CHANGE 0.100 0.061 0.38 6
CONVERSION OF WASTE TO ENERGY 0.067 0.096 0.59 2
SMART FOOD PACKAGING 0.089 0.058 0.39 5
RADIO RF TAGS 0.094 0.048 0.34 8
EDUCATION 0.070 0.073 0.51 4
VARIABLE PRICE STRUCTURE 0.065 0.088 0.57 3
RE-PURPOSE/RE-USE 0.049 0.082 0.62 1
FARM GLEANING 0.101 0.060 0.37 7
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17. Normalization & Weighting of the SAW Matrix
NORMALIZING THE DECISION MATRIX
Rij = Xij / Xj* for Benefit Criteria [12]
Rij = Xj- / Xij for Cost Criteria [12]
WEIGHTING THE DECISION MATRIX
As different criteria may vary in importance (as determined by
the stakeholders), each criteria is given a weight and each
column of the decision matrix is multiplied by its
corresponding weight to obtain a weighted decision matrix.
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18. The SAW Decision Matrix
Dividing each column by value Xj*, the largest number in each column,** we obtain the
normalized SAW matrix [12]. We then multiple each column by it’s determined weight to obtain
the weighted, normalized SAW matrix. Adding each row (each alternative solution), we obtain
the simple additive weights solution.
**Remember that we setup our matrix to have maximum benefit from the largest number, otherwise we would have to
determine if each criteria was a benefit or a cost.
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19. Decision Model Comparison
Based on our various methods of analysis, we have determined that the
following solutions are worth further investigation:
 Variable Price Structure
 Re-Purpose / Re-Use
 Conversion of Waste to Energy
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20. Decision Model Review
Reviewing our model, we decided that our method for
weighting each category could be improved.
1.Initial weighting assumed stakeholders were prioritizing
criteria. Weight was applied with this assumed priority.
2.We were too heavily weighted toward profit criteria. We
decided to divide the weight for profit related columns to
combine to share a weight equivalent to that of a single
category.
3.We decided to reduce the weight of the green-fuel category
as not all stakeholders would consider this a priority.
4.We increased the weight of our main category, reduction of
food waste to landfills.
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21. Final Decision Model Results
Based on our various methods of analysis, we have determined that the
following solutions are worth further investigation:
 Variable Price Structure
 Re-Purpose / Re-Use
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22. Decision Matrix Model Results
Through the decision matrix model, alternatives that are less favorable
toward our stakeholder’s criteria have been eliminated. We selected the top
two options for further analysis.
Variable Price Structure – Consumers would pay on a variable scale for
food products. As food life decreased or produce quality decreased, so
would the price on that product. Consumers looking for lower food prices
would benefit from the price reduction, while retailers such as markets would
be able to sell additional goods that would normally be thrown away.
Re-Use & Re-Purpose – Unsellable food (blemished, etc) would be used to
create products such as perfume fragrance, freeze dried foods, food
flavorings and additives. Food waste would be turned into compost,
fertilizers, bio-fuels, etc.
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23. Potential Solution – PROS & CONS Review
Variable Price Structure
PROS CONS
• Reduces the amount of food going to
• Lowers quality standards for produce and
landfills. other grocery goods.
• Beneficial to both consumers and sellers.
Consumers get a lower price & can save • May fail due to social standards. (For
money. Sellers gain benefit by selling example, some consumers may want to
hide the fact that they can’t afford the higher
produce or goods that may normally be quality produce.)
thrown away.
• Helps keep food on the table for those that • May result in a profit trade-off for retail
may be struggling financially. stores. They will sell more product, but the
profit on the product may be smaller. Can
• May help people to realize that there is they share the lost with food producers?
nothing wrong with slightly discolored or
blemished produce. People will be
educated by the experience.
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24. Potential Solution – PROS & CONS Review
Re-Use & Re-Purpose
PROS CONS
• Reduces the amount of food waste going • It can be very difficult to collect and sort
to landfills. waste for re-purposing. This can require lots
• Helps reduce costs associated with trash of time, money, and resources.
collection and transport. • Requires that people put in effort to make
• Helps to create products such as the solution effective. Individuals would have
compost, fertilizer, & other tangible to complete extra work to keep compost
goods. piles going or to sort food waste for
recycling.
• Reduces the amount of land needed for
landfills. This land can now be used for • There may be a stigma associated with
other activities. using food waste that has been converted
into usable products.
• Anyone can participate. Something as
simple as a compost pile can be created
with little or no startup cost.
• Can potentially create alternate forms of
fuel such as bio-diesel or bio-methane.
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25. Effectiveness Analysis (Risk of Not Performing)
Effectiveness Matrix
•Indicates each MOE and provides a pictorial representation of where a solution may or may not
perform favorably.
•In our analysis here, we are mainly looking at the likeliness of a solution being able to perform
well in terms of the MOE criteria.
 Green – Low Risk, Probably Will Perform Well
 Yellow – Medium Risk, Some Risk of Not Performing Well
 Red – High Risk, Most Likely Will Not Perform Well
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26. Cost / Benefit Considerations
Variable Price Structure
• Complex price structure interactions exist. Food prices are controlled by market
demand. Would variable price structuring cause farmers to allow land to lie fallow
or unharvested crops to spoil due to less favorable ROI?
• Will retailers end up losing money from variable price structures? One would have
to review the amount of money lost due to throwing away food versus the reduced
profits from selling items at low cost (while the same consumer would be currently
purchasing the item at full cost).
• What would be the labor required to sort foods by quality? What would be the
criteria to apply to the variable price structure? Would there still be undesirable
items in each of the “quality level bins?”
Re-Use / Re-Purpose
• Implementation can be very low cost or expensive
– Compost Piles (Low Cost)
– Bio-Fuel Production (Expensive)
• Current infrastructure makes it difficult to make a profit from food waste. Bio-fuel
plants may be expensive to implement. Food has to be collected and sorted to
provide fertilizer on a large scale.
• The products of this process have a lot of competition. Would chemical fertilizers
be more effective than compost based fertilizers? What would be the cost
difference between the two options?
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27. Qualitative Cost/Benefit Review
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28. Case Study Result
 Best Solution: Repurpose/ Reuse
 Does the Result of the Study Align of the Objective?
 Reduce Food Waste Sent to Landfills: Yes
 Meets Stakeholders Requirements: Yes
 This solution is the most flexible of all the alternative
 Each stakeholder can implement the solution in their own fashion
 Cost Effective: Yes
 Each stakeholder can determine how much to invest in the solution
 Cost benefits can exceed investment for each stakeholder
 Implementable: Yes
 Reuse can be implemented immediately
 Repurpose can be implemented later but steps can be taken later
 Technologically Feasible: Yes
 Solution can involve no technology(grind up food) to a lot of technology (bio-
reactor)
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29. Case Study Result
• Solution Mix of Non-technological and Technological
– Addresses Issues of Stakeholder Behavior To Reduce Waste
– Addresses Issues of Using Technology In Concert
• Adverse Consequences
– Our solution minimizes adverse consequences to stakeholders
– Each stakeholder can determine best solution
– Flexibility Can Minimize Risks
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30. Lessons Learned
• The systems engineer process works
– Many parts of the process are recursive. It is important to analyze
and re-analyze.
– Plan for risk: Try to identify and quantify all risks. Put prevention
and mitigation plans in place. Monitor risks throughout the
process.
• Do not define the problem by a solution
– Full understanding of a problem is key
– Don’t form an opinion on the solution until the SE process is
applied. This will blind you from potential solutions.
• Models can show you how wrong you are in your assumptions
– It can be difficult to obtain good model inputs. Avoiding
questionable inputs is important.
– Weighting criteria can be quite challenging
• It is important to define stakeholder requirements
– It is critical to understand the stakeholders
– Understanding of CONOPS is crucial to system development
• Communication is key
– Open discussion and collaboration is required between all parties
to reach a viable solution
• There is no one right answer: consider the whole range of options
– Be open to out of the box ideas. They may not be realistic, but
they open your eyes to different ways of thinking.
• The ability to measure effects is important
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31. References
[1] Mather, Tina et Al. “Food waste remains persistent problem at farms, grocery stores and restaurants,” californiawatch.org, 31 March
2010. Web. 1 February 2012. http://californiawatch.org/health-and-welfare/food-waste-remains-persistent-problem-farms-grocery-stores-
and-restaurants
[2] Daniels, Kim. “Food to Waste”, USC Annenburg, 5 April 2010. Web. 1 February 2012. http://hungerincal.uscannenberg.org/?p=112
[3] Walsh, Dylan. “A War Against Food Waste,” New York Times, 15 September 2011. Web. 1 February 2012. <
http://green.blogs.nytimes.com/2011/09/15/a-war-against-food-waste/>
[4] Hall, Kevin et Al. “The progressive Increase of Food Waste in America and Its Environmental Impact,” plosone.org, 25 November 2009,
Web. 1 February 2012. <http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0007940>
[5] Kaye, Leon. “Swipe card technology introduced for food waste bins,” The Guardian, 26 January 2012, Web. 1 February 2012.
<http://www.guardian.co.uk/sustainable-business/south-korea-swipe-card-food-waste?newsfeed=true>
[6] Mather, Tina. “How the Top 5 Supermarkets Waste Food,” alternet.org, 18 April 2010, Web 1 February 2012.
<http://www.alternet.org/investigations/146487/how_the_top_5_supermarkets_waste_food?page=entire>
[7] Martin, Andrew. “One Country’s Table Scraps, Another Country’s Meal”, The New York Times, 18 May 2008, Web. 1 February 2012
<http://www.nytimes.com/2008/05/18/weekinreview/18martin.html?scp=1&sq=One%20Country%92s%20Table%20Scraps,%20Another
%20Country%92s%20Meal&st=cse>
[8] Ruitenberg, Rudy. “Food Waste Denounced as Almost 1 Billion People Go Hungry”, Bloomberg Businessweek, 23 January 2012, Web.
1 February 2012
<http://www.businessweek.com/news/2012-01-23/food-waste-denounced-as-almost-1-billion-people-go-hungry.html>
[9] Katsman, Hannah. “Three Reasons we Throw Away Food,” cookingmanager.com, 3 January 2010. Web. 1 February 2012.
< http://www.cookingmanager.com/reasons-for-throwing-away-food/>
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32. References
[10] Various. “The Incose Systems Engineering Handbook”,Incose , Incose Working Group, 2012
[11] Roedler, Garry et Al. “Technical Measurement,” Incose.org, 27 Dec. 2005. Web. March 11, 2012.
http://www.incose.org/ProductsPubs/pdf/TechMeasurementGuide_2005-1227.pdf
[12] Kanda, Arun. “Lecture Series on Project and Production Management,” Indian Institute of Technology
[13] Afshari et Al. “Simple Additive Weighting approach to Personnel Selection Problem.” International Journal of Innovation, Management
and Technology, Vol. 1, No. 5, December 2010. Web April 14, 2012
www.ijimt.org/papers/89-M474.pdf
[14] Ullman, Dr. David G. “Decisions Based on Analysis of Alternatives.” January 2009. Web. April 29, 2012.
www.robustdecisions.com/AOA.pdf
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33. Any Questions?
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