- The document describes a model of the deer population on Kaibab Plateau from 1920-1950 that was created by consultants to help the game manager test policies for controlling the growing deer herd.
- The base run of the model shows the deer population growing dramatically without natural predators, matching the actual behavior described in the appendix.
- Simulations were run testing policies of reintroducing predators by ending deer hunting. This slowed the deer population growth but did not fully solve the problem of overpopulation.
In Korean: Making Sense of Multichannel (in the pharma industry)Len Starnes
Presentation first given at the Digital Health Summit Turkey, Istanbul, 11 – 12 September 2012. This was the first event of its type in Turkey with representatives of all major healthcare stakeholders: HCPs, patients, pharma, payers, government, academia, regulators, digital agencies and the media. Some 200 delegates participated.
http://www.ptms.com.tr/
This translation was made possible by the kind and generous help of Jahee Lee, Dreamwiz, Korea. www.dreamwiz.com
비록 박정희와 육사 동기지만 5.16에 가담하지 않았고 유신체제에 대한 비판의식이 있었던 김재규. 그는 재판에서도 박정희에 대한 ‘각하' 호칭을 사용하는 등의 한계가 있었지만 민주주의에 대한 확고한 역사관 철학으로 네 번째 저격으로 뜻을 이뤘다. 혼란스러운 과도기에 전두환은 치밀하고 신속하게 정권을 찬탈했다. 박정희와 그 옹호 세력들이 일을 처리하는 방식은 큰 충격을 준다.
1 Mashing Up Data with PowerPivot When Filter, .docxkarisariddell
1
Mashing Up Data with PowerPivot*
When “Filter, Then Calculate” Does Not Work in DAX Measures
This time you need to open the file with the worksheet Sls and have it linked to the
PowerPivot window, using Add to Data Model as in the last hands-on assignment.
1. Please create a pivot table first showing the sum of sales by each representative
on each date. Now the task is made so easy. However, if you want to compare
the sales to the total sales for a month, you need to do some calculation. In DAX,
instead of using SUMIFS, you need to use Calculate. Calculate asks for an
expression and then one or more filters. For those filters, you are going to use a
special function called ALL. ALL says that you want it to look not just at one
representative’s sales for a particular date, but all the sales in the table.
2. Suppose you want to see % of Grand Total Sales. You need to create a new
measure (Hint: right click on Table1 to select Add Measure) by using
=SUM(Sls[Sales])/Calculate(SUM(Sls[Sales]), ALL(Sls)). The pivot table shows
that % of Grand Total for Bill’s sales of $851 on June 2, 2011 represents 0.9
percent of the grand total sales.
3. Now you want to calculate how Bill’s $851 sale on June 2 compared to all sales
on June 2. The numerator of the DAX measure is =SUM(Sls[Sales]). The
denominator is going to be hard. Instead of ALL(Sls), you need to ask for
AllExcept(Sls, Sls[Date]). It means go ahead and throw out all the filters except
for the Date filter. Keep filtering by date. Please create a new measure, % of
Daily Sales, by using the formula
2
=SUM(Sls[Sales])/Calculate(SUM(Sls[Sales]),AllExcept(Sls,Sls[Date])). Bill’s
$851 sales is now 25% of the daily sales on June 2, 2011.
4. You can also override the filters by specifying other filters in the Calculate
Function. The actual syntax of the Calculate function is Calculate (Expression,
[filter 1], [filter 2], [filter 3], ….). Please create a new measure, Amber Sales, to
calculate all Amber’s sales. The Calculated Field formula should be
=CALCULATE(SUM(Sls[Sales]),Sls[Rep]="Amber").
5. If Amber is the sales star in the store, perhaps you would want to show
everyone’s sales as a percentage of Amber’s Sales.
=SUM(Sls[Sales])/Calculate(SUM(Sls[Sales]), Sls[Rep]="Amber") shows sales as
a percentage of Amber’s total sales for that day. Please create such a new
measure
3
4
Mix in Time Intelligence Functions
You can apply many filters in the Calculate function. You can replace the first argument
in Calculate with MAX, MIN, AVERAGE, or any function. There are 34 Time Intelligence
functions. If you want to calculate a running month to date (MTD) total, you can use the
Calculate function and specify a filter of DatesMTD(Sls[Date]). But only for reps that
match, use AllExcept(Sls, Sls[Rep]).
1. To show MTD sales for each rep, create a new measure, MTDThisRep, using the
formula =Calculate(.
At its most elementary, the syntax of Manipulate is clone of that of.pdftemperaturejeans
At its most elementary, the syntax of Manipulate is clone of that of the standard operate Table.
take into account this Table command, that produces a listing of numbers from one to twenty.
In[1]:=
Click for copyable input
Out[1]=
Simply replace the word Table with the word Manipulate, Associate in Nursingd you get an
interactive application that allows you to explore values of n with a slider.
In[2]:=
Click for copyable input
Out[2]=
Play Animation
If you\'re reading this documentation within the atomic number 74 System, you\'ll click and drag
the slider to visualize the displayed price modification in real time (meaning that it changes
whereas you\'re dragging the slider, not simply after you unharness it). If you\'re reading a static
style of the documentation, you may see the slider captive to Associate in Nursing discretional
position. (By default, it starts out on the left facet, however within the following examples the
slider has generally been captive faraway from its initial position.)
In each Table and Manipulate, the shape is employed to specify Associate in Nursing \"iterator\",
giving the name of the variable and also the vary over that to vary it.
Of course the entire purpose of Manipulate (and Table for that matter) is that you just will place
any expression you wish within the 1st argument, not simply an easy variable name. Moving the
slider during this terribly easy output already starts to administer an inspiration of the ability of
Manipulate.
In[3]:=
Click for copyable input
Out[3]=
Play Animation
Again, if you\'re reading this in an exceedingly static kind you may got to trust that the graph
changes in real time once the slider is captive.
Note that the slider has an additional icon next to that that, once clicked, opens alittle panel of
further controls. Here, the panel from the previous example is opened.
Play Animation
The panel permits you to visualize the numerical price of the variable, furthermore as set it in
motion mistreatment the animation controls.
If you wish to visualize the worth of the variable while not having to open the subpanel, you\'ll
add the choice Appearance->\"Labeled\" to the variable specification. (Note the quantity
presented the correct of the sign, that is updated in real time because the slider is captive.)
In[4]:=
Click for copyable input
Out[4]=
Play Animation
This is conjointly the primary hint that Manipulate goes way on the far side the relative
simplicity of Table, each in its output and within the flexibility and vary of what will be laid out
in the list of variables.
Just like Table, Manipulate permits you to administer over one variable vary specification.
In[5]:=
Click for copyable input
Out[5]=
Play Animation
You can have as several variables as you wish, as well as numerous that {a similar|an
identical|an Associate in Nursingalogous|the same} Table command would try and enumerate an
immoderately sizable amount of entries.
In[6]:=
Click for copyable input
Out[6]=
Play Animation
Y.
In Korean: Making Sense of Multichannel (in the pharma industry)Len Starnes
Presentation first given at the Digital Health Summit Turkey, Istanbul, 11 – 12 September 2012. This was the first event of its type in Turkey with representatives of all major healthcare stakeholders: HCPs, patients, pharma, payers, government, academia, regulators, digital agencies and the media. Some 200 delegates participated.
http://www.ptms.com.tr/
This translation was made possible by the kind and generous help of Jahee Lee, Dreamwiz, Korea. www.dreamwiz.com
비록 박정희와 육사 동기지만 5.16에 가담하지 않았고 유신체제에 대한 비판의식이 있었던 김재규. 그는 재판에서도 박정희에 대한 ‘각하' 호칭을 사용하는 등의 한계가 있었지만 민주주의에 대한 확고한 역사관 철학으로 네 번째 저격으로 뜻을 이뤘다. 혼란스러운 과도기에 전두환은 치밀하고 신속하게 정권을 찬탈했다. 박정희와 그 옹호 세력들이 일을 처리하는 방식은 큰 충격을 준다.
1 Mashing Up Data with PowerPivot When Filter, .docxkarisariddell
1
Mashing Up Data with PowerPivot*
When “Filter, Then Calculate” Does Not Work in DAX Measures
This time you need to open the file with the worksheet Sls and have it linked to the
PowerPivot window, using Add to Data Model as in the last hands-on assignment.
1. Please create a pivot table first showing the sum of sales by each representative
on each date. Now the task is made so easy. However, if you want to compare
the sales to the total sales for a month, you need to do some calculation. In DAX,
instead of using SUMIFS, you need to use Calculate. Calculate asks for an
expression and then one or more filters. For those filters, you are going to use a
special function called ALL. ALL says that you want it to look not just at one
representative’s sales for a particular date, but all the sales in the table.
2. Suppose you want to see % of Grand Total Sales. You need to create a new
measure (Hint: right click on Table1 to select Add Measure) by using
=SUM(Sls[Sales])/Calculate(SUM(Sls[Sales]), ALL(Sls)). The pivot table shows
that % of Grand Total for Bill’s sales of $851 on June 2, 2011 represents 0.9
percent of the grand total sales.
3. Now you want to calculate how Bill’s $851 sale on June 2 compared to all sales
on June 2. The numerator of the DAX measure is =SUM(Sls[Sales]). The
denominator is going to be hard. Instead of ALL(Sls), you need to ask for
AllExcept(Sls, Sls[Date]). It means go ahead and throw out all the filters except
for the Date filter. Keep filtering by date. Please create a new measure, % of
Daily Sales, by using the formula
2
=SUM(Sls[Sales])/Calculate(SUM(Sls[Sales]),AllExcept(Sls,Sls[Date])). Bill’s
$851 sales is now 25% of the daily sales on June 2, 2011.
4. You can also override the filters by specifying other filters in the Calculate
Function. The actual syntax of the Calculate function is Calculate (Expression,
[filter 1], [filter 2], [filter 3], ….). Please create a new measure, Amber Sales, to
calculate all Amber’s sales. The Calculated Field formula should be
=CALCULATE(SUM(Sls[Sales]),Sls[Rep]="Amber").
5. If Amber is the sales star in the store, perhaps you would want to show
everyone’s sales as a percentage of Amber’s Sales.
=SUM(Sls[Sales])/Calculate(SUM(Sls[Sales]), Sls[Rep]="Amber") shows sales as
a percentage of Amber’s total sales for that day. Please create such a new
measure
3
4
Mix in Time Intelligence Functions
You can apply many filters in the Calculate function. You can replace the first argument
in Calculate with MAX, MIN, AVERAGE, or any function. There are 34 Time Intelligence
functions. If you want to calculate a running month to date (MTD) total, you can use the
Calculate function and specify a filter of DatesMTD(Sls[Date]). But only for reps that
match, use AllExcept(Sls, Sls[Rep]).
1. To show MTD sales for each rep, create a new measure, MTDThisRep, using the
formula =Calculate(.
At its most elementary, the syntax of Manipulate is clone of that of.pdftemperaturejeans
At its most elementary, the syntax of Manipulate is clone of that of the standard operate Table.
take into account this Table command, that produces a listing of numbers from one to twenty.
In[1]:=
Click for copyable input
Out[1]=
Simply replace the word Table with the word Manipulate, Associate in Nursingd you get an
interactive application that allows you to explore values of n with a slider.
In[2]:=
Click for copyable input
Out[2]=
Play Animation
If you\'re reading this documentation within the atomic number 74 System, you\'ll click and drag
the slider to visualize the displayed price modification in real time (meaning that it changes
whereas you\'re dragging the slider, not simply after you unharness it). If you\'re reading a static
style of the documentation, you may see the slider captive to Associate in Nursing discretional
position. (By default, it starts out on the left facet, however within the following examples the
slider has generally been captive faraway from its initial position.)
In each Table and Manipulate, the shape is employed to specify Associate in Nursing \"iterator\",
giving the name of the variable and also the vary over that to vary it.
Of course the entire purpose of Manipulate (and Table for that matter) is that you just will place
any expression you wish within the 1st argument, not simply an easy variable name. Moving the
slider during this terribly easy output already starts to administer an inspiration of the ability of
Manipulate.
In[3]:=
Click for copyable input
Out[3]=
Play Animation
Again, if you\'re reading this in an exceedingly static kind you may got to trust that the graph
changes in real time once the slider is captive.
Note that the slider has an additional icon next to that that, once clicked, opens alittle panel of
further controls. Here, the panel from the previous example is opened.
Play Animation
The panel permits you to visualize the numerical price of the variable, furthermore as set it in
motion mistreatment the animation controls.
If you wish to visualize the worth of the variable while not having to open the subpanel, you\'ll
add the choice Appearance->\"Labeled\" to the variable specification. (Note the quantity
presented the correct of the sign, that is updated in real time because the slider is captive.)
In[4]:=
Click for copyable input
Out[4]=
Play Animation
This is conjointly the primary hint that Manipulate goes way on the far side the relative
simplicity of Table, each in its output and within the flexibility and vary of what will be laid out
in the list of variables.
Just like Table, Manipulate permits you to administer over one variable vary specification.
In[5]:=
Click for copyable input
Out[5]=
Play Animation
You can have as several variables as you wish, as well as numerous that {a similar|an
identical|an Associate in Nursingalogous|the same} Table command would try and enumerate an
immoderately sizable amount of entries.
In[6]:=
Click for copyable input
Out[6]=
Play Animation
Y.
Instructions(1) Work through the pages below.(2) Use the us_demog.docxdirkrplav
Instructions:(1) Work through the pages below.(2) Use the us_demographics.jmp data table to: (a) select a continuous variable and generate a histogram
(b) select two continuous variables and determine the correlation coefficient(c) generate box plots using College Degrees as the Y, Response variable and Region as the X, Factor variable(3) Copy and paste the results for 2 (a, b, & c) in a Word document.
Histograms, Descriptive Statistics, and Stem and Leaf
Use to display and describe the distribution of continuous (numeric) variables. Histograms and stem and leaf plots allow you to quickly assess the shape, centering and spread of a distribution. For categorical (nominal or ordinal) variables, see the page on Bar Charts and Frequency Distributions.
Histograms and Descriptive Statistics
1. Open the JMP® data table us_demographics.jmp, select Analyze > Distribution.
2. Click on one of the continuous variables from Select Columns, and click Y, Columns (continuous variables have blue triangles).
3. Click OK to generate a histogram, outlier box plot and descriptive statistics.
· The percentiles, including quartiles and the median, are listed under Quantiles.
· The sample mean, standard deviation and other statistics are listed under Summary Statistics.
Example: Car Physical Data.jmp (Help > Sample Data)
Tips:
· To change the display from vertical to horizontal (as shown), click on the top red triangle and select Stack.
· To change the graphical display for a variable, or to select additional options, click on the red triangle for that variable.
· To display different summary statistics, use the red triangle next to Summary Statistics.
· To change all future output to horizontal, go to Preferences > Platforms > Distribution, click Stack and
Horizontal, then click OK.
Stem and Leaf Plot
To generate a stem and leaf plot, click on the red triangle for the variable and select Stem and Leaf.
Tips:
· A key to interpret the values is at the bottom of the plot. The top value in this example is 4300, the bottom value is 1700 (values have been rounded to the nearest 100).
· Click on values in the stem and leaf plot to select observations in both the histogram and the data table. Or, select bars in the histogram to select values in the stem and leaf plot and data table.
jmp.com/learn rev 07/2012
Use to display the distribution of continuous variables. They are also useful for comparing distributions.
Box Plots – One Variable
1. From the open JMP® data table, select Analyze > Distribution.
2. Click on another continuous variable from Select Columns, and Click Y, Columns (continuous variables have blue triangles).
3. Click OK. An outlier box plot is displayed by default next to the histogram (or above if horizontal layout). To display a quantile box plot, select the option from the red triangle for the variable.
jmp.com/learn rev 07/2012
Box Plots
The lines on the Quantile Box Plot correspond to the quantiles in the distribut.
해당 잡지사의 허락을 받고 공유합니다. 다운로드 가능합니다.
[이달의 신기술]에 '기후변화 시뮬레이션이 던지는 시사점'이라는 제목으로 원고를 부탁받아서 작성한 글입니다.
[이달의 신기술]은 <이달의 신기술>은 산업통상자원부가 후원하여 R&D 전담기관인 한국산업기술평가관리원, 한국에너지기술평가원, 한국산업기술진흥원 및 한국공학한림원 공동으로 발행되는 매거진입니다.
원고에서 저는 기후변화가 주는 위험 요인과 기회 요인을 언급했습니다. 관심있는 분은 읽고 공유해 주시면 고맙겠습니다.
정창권 드림
Benjamin@System-Leadership.org
기획재정부가 보내 준 공식자료(보도 자료)를 공유합니다.
이 자료가 필요하신 분에게 적절히 사용되기를 바랍니다.
(보도자료) 긴급 거시경제금융회의 개최결과
(보도자료) 2015회계연도 세입․세출 마감 결과 - 세계잉여금 4년만에 흑자로 전환 (2.8조원) -
(보도자료) 민생안정과 경제활력제고를 위한조속 처리 필요 법안 주요내용
(보도참고) 「증세는 없다?…작년 월급쟁이 세금 6.7%증가」제하 기사 관련
(보도참고) 「연금저축의 배신」제하 기사 관련
cf) 2015년 공공기관 경영평가 위원으로서 받은 자료입니다. 담당부서의 승인을 받아 원문을 공유합니다.
ʱ (보도) 누리과정의 차질없는 시행 및 교육환경 개선을 위해 ‘16년 목적예비비 3,000억원 지원
ʲ (보도참고) 「2015 대한민국 정책평가」 기사 ‘공공기관 임금피크제’ 관련 (2015.11.30., 12.2 동아일보)
ʳ (보도참고) 위안화의 SDR 바스켓 편입의 영향 및 대응방향-
ʴ (보도) 2015년도 세법개정안 주요내용과 의미
※ 본 자료는 기획재정부가 운영하는 위원회 및 자문단 소속 위원님께 정책의 이해를 돕기 위하여 보내드리는 자료입니다. 주1회 현안이슈에 대한 기획재정부의 입장이 담긴 자료를 보내드립니다.
2015년 공공기관 경영평가 위원으로서 받은 자료입니다. 담당부서의 승인을 받아 원문을 공유합니다.
ʱ (보도참고) 최경환 부총리, 한중 FTA 등 조속한 비준처리 촉구 (제51회 국무회의 FTA비준 관련 발언, 한·중, 한·베, 한·뉴 FTA 영향평가 결과 및 보완대책)
ʲ (보도참고) 국민일보, 「서비스법 통과땐 일자리 69만개 생긴다는데...과연?」 제하 기사 관련
ʳ (보도참고) ‘15년 3/4분기 가계동향 분석 “가계소득 0.7% 증가, 소득분배 개선세 지속”
ʴ (보도) 「제13차 재정관리점검 회의」 - 2016년 예산을 연초부터 즉시 집행할 수 있도록 사전준비 완료
※ 본 자료는 기획재정부가 운영하는 위원회 및 자문단 소속 위원님께 정책의 이해를 돕기 위하여 보내드리는 자료입니다. 주1회 현안이슈에 대한 기획재정부의 입장이 담긴 자료를 보내드립니다.
내 인생의 소중한 가치 10가지를 쓰는 훈련을 위해 저의 소중한 가치를 소개합니다. 나의 소중한 가치는 중요한 의사결정을 할 때의 기준이 됩니다. 따라서 나에게 헌법과 같은 의미입니다.
하지만 완성된 것으로 보면 안됩니다. 내용도 바뀔 수 있습니다. 또한 이 가치를 현재 내가 잘 지키고 있다는 뜻이 아닙니다. 나의 지향점을 의미합니다. 그 이상도 그 이하도 아닙니다. 현재 이런 모습이 아닐지라도 그런 모습으로 이끌어 갈 수 있는 힘을 받을 수 있습니다.
편하게 작성해 보십시오. 그리고 계속 수정하십시오. 저는 이 내용을 3년 동안 수정하면서 완성한 것입니다.
정창권 드림
경영학 박사, cck@K-Bridge.org
2015년 9월 24일 기획재정부
ㅇ 기업·공공기관에서 사회적 가치를 실현하는 기관을 대상으로 지원하는 사회공헌사업 중 지속적으로 진행되고 있는 프로그램을 발췌하여 안내하오니 (사회적)협동조합에서는 지원자격, 지원내용 등을 확인하시어 향후 사회공헌프로그램 공모에 대비하시기 바랍니다.
ㅇ 특히 한국전력공사의 사회공헌 프로그램은 '15.9월 이후 진행되오니 금융지원 등이 필요한 협동조합은 적극 참가하시기 바랍니다.
※ 신청 요건 및 절차, 문의처 등 자세한 내용은 첨부의 자료를 참고하시기 바랍니다.
출처: 한국사회적기업진흥원 http://bit.ly/1NTYTeB
www.facebook.com/EcoSocialEconomy
Table of Contents for PNAS August 19, 2014 vol. 111 no. 33.
# JOURNAL NAME: Proceedings Of The National Academy Of Sciences Of The United States Of America
# ABBREVIATION: P NATL ACAD SCI USA
# 2013 JCR IMPACT FACTOR: 9.809
HBR 2014년 5월호 Cover Story가 Resilient Company 였습니다. 자연재해와 천연자원의 고갈이 기업이 관리해야 하는 원가 위협/수익 위협 요인이어서 속수무책으로 당하지 말자는 취지에서 resilience를 키워야 하는 관점을 보이고 있습니다.
기존의 efficiency와 원가 절감을 단기적인 관점으로 돌려버리고 장기적인 관점에서 기업의 경영에 도움이 되기 위해서라도 efficiency에 반대되는 diversity를 키워야 하고 원가 절감에 반대되는 것처럼 보이는 redundancy를 중요시 해야한다는 주장을 하고 있습니다. 이것이 HBR이 관심을 가지고 있는 새로운 자본주의/ 기업 경영 원리로 자리잡고 있습니다.
동영상 강의와 연결해서 보시면 도움이 되실겁니다
동영상 라이브 강의 : http://goo.gl/8QCAQV
동영상 강의 목차 :
1. 강의 점검 및 강의소개 : 5분 55초 - 6분 29초
2. hbr 활용법 : 6분 30초 - 14분 11초
3. resilience의 개념 : 14분 12초 - 23분 14초
4. 본론 :23분 15초 - 1시간 19분 29초
5. 토론 : 1시간 19분 30초- 1시간 49분 59초
6. 정리 : 1시간 50분 - 끝까지
본 과정은 석, 박사 과정입니다.
에코 컨텐츠를 세상과 소통시키는 것에 관심있는 여성 인재들을 환영합니다.
본 사업단을 위해 교과목으로 [에코 크리에이티브 협동과정]이라는 석, 박사 과정을 새로 개설하였으며, 이 협동과정에는 자연대, 미대(산업디자인), 언론홍보영상학과, 사범대가 함께 합니다.
21세기는 에코가 경쟁력입니다. 본 협동과정과 사업단의 다양한 활동을 통해 다양성(Diversity)가 왜 기업, 사회, 인류의 생존 대안이 될수밖에 없는지 확인하시고 새로운 길을 열어보기 바랍니다.
관련 문의 : 민주영 (이화여자대학교 에코과학 창조아카데미 사업단)
T. 3277-3868 e600118@ewha.ac.kr
Company Valuation webinar series - Tuesday, 4 June 2024FelixPerez547899
This session provided an update as to the latest valuation data in the UK and then delved into a discussion on the upcoming election and the impacts on valuation. We finished, as always with a Q&A
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
RMD24 | Retail media: hoe zet je dit in als je geen AH of Unilever bent? Heid...BBPMedia1
Grote partijen zijn al een tijdje onderweg met retail media. Ondertussen worden in dit domein ook de kansen zichtbaar voor andere spelers in de markt. Maar met die kansen ontstaan ook vragen: Zelf retail media worden of erop adverteren? In welke fase van de funnel past het en hoe integreer je het in een mediaplan? Wat is nu precies het verschil met marketplaces en Programmatic ads? In dit half uur beslechten we de dilemma's en krijg je antwoorden op wanneer het voor jou tijd is om de volgende stap te zetten.
Enterprise Excellence is Inclusive Excellence.pdfKaiNexus
Enterprise excellence and inclusive excellence are closely linked, and real-world challenges have shown that both are essential to the success of any organization. To achieve enterprise excellence, organizations must focus on improving their operations and processes while creating an inclusive environment that engages everyone. In this interactive session, the facilitator will highlight commonly established business practices and how they limit our ability to engage everyone every day. More importantly, though, participants will likely gain increased awareness of what we can do differently to maximize enterprise excellence through deliberate inclusion.
What is Enterprise Excellence?
Enterprise Excellence is a holistic approach that's aimed at achieving world-class performance across all aspects of the organization.
What might I learn?
A way to engage all in creating Inclusive Excellence. Lessons from the US military and their parallels to the story of Harry Potter. How belt systems and CI teams can destroy inclusive practices. How leadership language invites people to the party. There are three things leaders can do to engage everyone every day: maximizing psychological safety to create environments where folks learn, contribute, and challenge the status quo.
Who might benefit? Anyone and everyone leading folks from the shop floor to top floor.
Dr. William Harvey is a seasoned Operations Leader with extensive experience in chemical processing, manufacturing, and operations management. At Michelman, he currently oversees multiple sites, leading teams in strategic planning and coaching/practicing continuous improvement. William is set to start his eighth year of teaching at the University of Cincinnati where he teaches marketing, finance, and management. William holds various certifications in change management, quality, leadership, operational excellence, team building, and DiSC, among others.
Premium MEAN Stack Development Solutions for Modern BusinessesSynapseIndia
Stay ahead of the curve with our premium MEAN Stack Development Solutions. Our expert developers utilize MongoDB, Express.js, AngularJS, and Node.js to create modern and responsive web applications. Trust us for cutting-edge solutions that drive your business growth and success.
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Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
Putting the SPARK into Virtual Training.pptxCynthia Clay
This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
Business Valuation Principles for EntrepreneursBen Wann
This insightful presentation is designed to equip entrepreneurs with the essential knowledge and tools needed to accurately value their businesses. Understanding business valuation is crucial for making informed decisions, whether you're seeking investment, planning to sell, or simply want to gauge your company's worth.
Policy analysis for the kaibab plateau (and introduction to vensim)
1. PAD 624, Kaibab Exercise
Page 1
Policy Analysis for the Kaibab Plateau (and Introduction to Vensim)
The year is 1920.
You are the game manager of the Kaibab Plateau, a region of about 800,000 acres on the
north side of the Grand Canyon. You are charged with maintaining the environmental balance of
the region. In particular, you must take steps to control the deer population, which has grown
alarmingly since the elimination of predators began around 1900.
Pressure groups and lobbyists have been calling your office daily with pet policies they
want you to adopt.
•
The Sierra Club argues that the elimination of the predators caused the problem, so
reintroduction of the mountain lions, coyotes, and other predators will solve it.
•
The ranchers, worried about their herds, are dead set against any reintroduction of
predators.
•
The local hunters want free access to the plateau.
Worse, the governor has let it be known that unless you come up with an effective policy to
control the deer, you'll be looking for a new job.
Since there has never been a deer population explosion like this before, experience cannot
guide you in your quest for effective policies. Fortunately, you have retained some expensive
consultants from the University at Albany (paid for with government money, of course). The
consultants have built some sort of model of the plateau. They claim you can use the model to
test the impact of different policy proposals on the herd. You are skeptical, but have little choice.
The consultants' model is contained on your class files disk as KAIBAB. A description of what
actually happened on the plateau appears in the Appendix.
(0) Call up Vensim PLE, and open the KAIBAB.MDL model on the disk handed out in class.
[In the "Open" dialog box, type *.mdl and press return (or click OK) to see all the files
labeled ".mdl", or just type KAIBAB.MDL as the file to open.]
You should see a screen like the one on the next page.
2. PAD 624, Kaibab Exercise
Page 2
Causes tree
Effects tree
Loops
Document
Causes
graSpinhgsle graph
Numbers
Run comparison
3. PAD 624, Kaibab Exercise
Page 3
Scroll around to look at the whole model. To see the entire model at once, use the View
menu to Zoom to a different magnification -- 50% will let you see almost all at once here.
Investigate the pull-down menus. Note in particular the entries in the Model menu. Look at
the Time Bounds. Over what years will the simulation run? How much simulated time
elapses between successive computations?
(1)
a) Print the Vensim diagram of the KAIBAB model. It should print nicely in "landscape"
mode, with one sector to a page. If the page break lines on the screen do not look like
landscape mode, go to Print Options in the File menu, and click on Best Choice or Landscape
Always; click OK, you should be back at the model diagram.
b) Draw a single, connected causal-loop diagram of the KAIBAB model. Identify the stocks
(levels) by drawing rectangles around them, but leave the rest in simple words and arrows.
Read the following before you begin.
You can begin the connected causal-loop diagram by drawing the variables as they appear on
the screen, substituting words and arrows for the flow symbols and their labels. But
the model is divided into sectors and some variables (the ones that look like <Food>)
are brought in from other sectors. That might make it hard to see all the loops. But
Vensim can help create the causal-loop diagram.
Try this procedure: Double click on the Deer level to select it (it should appear in the
window bar as the variable on Vensim's "workbench.") Then click on the loop
symbol in the vertical bar of tools on the left of your screen (see "Loops" on the
Vensim screen picture on page 2). You will see a list of loops increasing in
"length" (number of other variables around the loop). Start with the loop of length 1
and draw it: In the middle of a sheet of paper write Deer and Deer Net Increase and
connect them with arrows in a loop. Draw a box around Deer to show it's a stock or
level variable. Then add to your picture the words and arrows of the next loop that
Vensim lists. Proceed until you have all the loops that involve Deer. Then double
click on Predators to select it on the workbench, click on loops, and add those (very
few) new loops to your diagram. Finally, do the same for the remaining level Food.
If you diagram is messy, you could redraw it for clarity, but don't spend a lot of time on this.
Identify the polarities of links and loops in your diagram. There are two loops that switch
between positive and negative polarity -- which are those? There is only one other positive
loop -- what is it?
(2)
a) Base Run. Next to the "runner" button in the menu bar of buttons across the top, there is
a window in which you can name each simulation.
4. PAD 624, Kaibab Exercise
Page 4
Erase the name that is in
there and type the word
BASE (upper or lower
case, it doesn't matter), to
be the name of the base
run of the KAIBAB
model. Then click on the
"runner" button (not the
SET button) to simulate
the model.
You will see Time go by,
and you will see a
window with some
warnings about being
"above" or "in" some of the graphical variables in the model. You can ignore these warnings
at this point -- click on the "close" box in the upper left
corner of this warnings window to close it.
Click on the "dial" button at the right-end of the menu
bar of buttons (shown above) to bring up the Control
Panel. Click on the word "Graphs" if it is not selected.
In the list of saved graphs, double click on KAIBAB
POPULATIONS to show a graph of Deer, Predators,
and Food. Click on KAIBAB RATIOS to see some
other information in the system. (Or click once and
select Display.)
Other Graphs
Looking at the model diagram, you can show graphs of
anything in the model by double clicking on the
variable you are interested in (to put it on the Vensim's
"workbench") and selecting any of the Graph tools in
the tool bar at the left of the screen. Try it: double
click on a variable such as Food Per Deer Ratio and
then select the Causes Graph tool, and then the Single
Graph tool. The Causes Graph should look like the
figure at the right.
Base
Food per deer ratio
200
150
100
50
0
Deer
100,000
75,000
50,000
25,000
0
Food
600 M
450 M
300 M
150 M
0
1900 1925 1950
If you see a variable in the strip graph that you'd like to
investigate, double click on its name in the strip graph
Time (year)
and select the same strip graph tool to see that variable
and its causes or effects displayed. Note that the
Food per deer normal
Causes Graph tool shows you a graph of the variable on
Base: 1,000
the Workbench, followed by all the variables that
directly influence that variable. You can thus trace causal effects graphically. So investigate.
5. PAD 624, Kaibab Exercise
Page 5
In the written report you hand in discuss briefly the following: Compare the plots to the
actual behavior of the system described and shown in the Appendix. Can we use this model
to test policies to avoid a collapse of the deer herd?
You can print a custom graph or strip graph to hand in by clicking on the little printer symbol
in the window bar of the graph window. You can also, or instead, copy a custom graph or a
strip graph to paste into a word processing document: click on the little clipboard symbol in
the window bar of the graph you want to copy. Move to the window of your word processor
and paste in the graph as you wish. Before you print or copy you can resize any of the
graphs by clicking and dragging a corner.
For what you hand in, I would suggest that you copy graphs and paste them into a word
processing document (as I have have done here) so that you can talk about them as well as
show them.
(3)
Policy analysis: Reintroduction of predators. The Predator harvest fraction in Predator
Sector of the model represents the fraction of the predator population that ranchers and
hunters are eliminating every year. The fraction is given as a function of time, with points
marked every five years from 1900 to 1950:
The graph represents the idea the bounty offered in 1905 led within five years to enough
hunting activity to eliminate 20% of the predator population every year from 1910 on.
(a) We will simulate the policy of removing the bounty in 1920 and bringing hunting on the
Plateau to a halt by 1925.
6. PAD 624, Kaibab Exercise
Page 6
Scroll around in the model to view the entire Predator Sector. Then in the top menu bar,
click on the SET button (a runner getting ready to run). Some of the word phrases will
become blue, indicating you can select them to change their values. Click on "Fraction
harvest p yr f"; you will see the window shown above containing a graph over time of
the fraction of predators we're assuming are being harvested each year because of the
bounty placed upon predators.
In the table of values at the left, change the 1925 value from 0.2 to 0. Continue for 1930,
1935 and so on to 1950. You should see the graph change accordingly. [You can also
change these points in the graph itself by moving points with the mouse, but it's hard to
be precise.] When you are done, click OK. Then name the run ReintroA or some other
suitable name (in the menu bar) and click on the Run (runner) button.
Click on the Dial button to see the Custom Graphs, but before viewing them we have to make
the new graphs the active ones. Click on Datasets, and then click once on ReintroA to bring
it to the top of the list. Then click on Graphs and select the graph(s) you want to see.
Looking at the model diagram you can select variables to view in comparative graphs.
Double click on Deer, for example, and then click on the Single Graph button (on the left).
You should see a graph that shows the deer population in both the Base and ReintroA
simulations. You might do this for each of the stocks in the model, and anything else you
think might be interesting to look at in this comparative way.
The Causes Graph tool works the same way here, showing you the two simulation runs
together.
In your written report discuss what happens in this policy. Why does it happen?
(b) Suppose the ranchers delay the implementation of this policy five years. Try the same
kind of simulation with the zero harvest fraction starting five years later (1930). Be sure to
rename your new simulation, say ReintroB.
Are the results predictable?
(c) Try another hunting policy of your own devising. Note that the first five numbers in the
Predator hunting fraction table must be 0/0/.2/.2/.2 because these are the history that you are
dealing with up to 1920, after which you can take some different action.
Hand in a graph of your run [ReintroC? ReintroC1, ReintroC2?], and comment on it (see the
comments above about printing or cutting and pasting a graph).
What can you say about policies for reintroducing predators? Do they solve the problem?
To get ready for more simulation runs, it would probably be a good idea to remove the
Reintro datasets so they don't show up in future graphs. Click on the Dial button to see the
Control Panel, and click on the Datasets tab. Click once on the name of a dataset you want to
7. PAD 624, Kaibab Exercise
Page 7
remove (say ReintroA) and then click on the button marked <<. That will "unload" that
dataset -- it will still be available (in the list on the left), but only the "loaded" graphs show
up in graphs. Leave the Base run loaded so you can use it for comparative purposes. Of
course, as you go on you can control the datasets that are loaded so you can show any
comparisons you'd like.
(4)
Policy analysis: Harvesting deer. Hunters have urged the hunting of deer to maintain a
healthy herd and prevent the collapse. We will test three "harvesting" policies: a constant
number of deer per year; a constant fraction of the deer per year; and a harvest whenever
the deer population exceeds a chosen target.
To test these we have to edit the model. Click anywhere on the model diagram to make it the
active window. Add a new outflow rate from the deer population called the Deer harvest rate.
(Click on the flow tool, ,click once inside the Deer level, move the mouse up out of
the level about an inch (where you want the end of the flow pipe to be) and click the
mouse button again. You'll be given a box to name the flow: call it Deer Harvest Rate. If
you don't like what you have you can adjust it somewhat by clicking and dragging the
cloud or the circle "handles" that appear, or you can erase it with the Pac Man tool (eat it
up) and try again.)
The sequence should look like
Click inside the Deer box, then move the mouse about an inch above. It should look like this:
Click the mouse at that point and you get:
8. PAD 624, Kaibab Exercise
Page 8
Fill in the name for the flow -- the Deer Harvest Rate -- and press Return and you should see:
This next step is important: Hold down the Ctrl key and the Shift key simultaneously and
click on the Deer level -- you will see and equation-writing screen for the initial value of
Deer and the flows into and out of the Deer level. Add (that is, subtract) the new outflow
Deer Harvest Rate, then click OK.
We will set the Deer Harvest Rate equal to the sum of three new auxiliary variables: DHR1,
DHR2, and DHR3. There's not enough room for them in the Deer Sector diagram, however,
so we will put them in a new sector, labeled the Deer Harvest Sector, which will be a fourth
page of your model diagram, and link them to the Deer Sector.
The picture you are about to add looks like this:
9. PAD 624, Kaibab Exercise
Page 9
Here's how to create it:
Click on the auxiliary variable tool , and click somewhere in the Deer Harvest Sector
page of your model. Name the new variable DHR. Then click three more times nearby to
create the variables DHR1, DHR2, and DHR3. To set DHR equal to these, click on the
information link tool and click on DHR1 and DHR in succession to make a link from
DHR1 to DHR. Similarly make links from DHR2 and DHR3 to DHR.
To write the equation for DHR, hold down the Shift key and the Ctrl key simultaneously and
click on DHR. You will see the equation writing screen for DHR. Set it equal to DHR1 +
DHR2 + DHR3 (you can just click on the names and put plus signs in between -- you don't
have to retype the variables here). Make the units deer/year and click OK.
Use these techniques to set DHR1 equal to
(Constant deer harvest)*(STEP(1, Deer harvest year)).
[First create in the diagram the variables for Constant Deer Harvest and Deer Harvest Year. Then Ctrl-Shift
click DHR1 to write the equation. The STEP is a built-in function; you can enter it by just typing its name.
Make sure the parentheses match.]
To set DHR2 equal to (Deer harvest frac)*(Deer)*(STEP(1, Deer harvest year)) we must add
the Deer level to the Deer Harvest Sector as a "shadow" variable, a copy of the variable
defined in the Deer Sector. Select the Shadow variable tool and click near DHR2 and
DHR3; from the list of variables that appears select Deer and click OK. You will have added
<Deer> to your diagram.
Following the procedures above, set DHR2 equal to
(Deer harvest frac)*(Deer)*(STEP(1, Deer harvest year))
and DHR3 equal to
MAX(0, (Deer - Desired deer pop)/(Time to correct DP))*STEP(1,Deer harvest year).
In the process, you'll need to add some more auxiliary variables to your diagram for the
various constants in these equations. Use Ctrl-Shift-click to set the values of those constants
initially as follows:
10. PAD 624, Kaibab Exercise
Page 10
Deer harvest year = 1920 [units = year]
Constant deer harvest = 0 [units = deer/year]
Deer harvest frac = 0 [units = 1/year]
Desired deer pop = 1e6 [units = deer]
Time to correct DP = 1 [units = year]
When you are done the Deer Harvest Sector will look something like the following (the
geometry may be very different in your picture, but the connections and variables should be
the same):
11. PAD 624, Kaibab Exercise
Page 11
One last important step: We need to link your DHR variable to the Deer Harvest Rate you
created in the Deer Sector. Go back to the Deer Sector. Click on the "shadow variable"
button to select it, and then click somewhere near the Deer Harvest Rate (about an
inch away would be good). Up will come a window asking you which variable you want to
place there as a shadow variable. Find DHR, select it, and click OK. You should see
<DHR> placed on the screen. Select the arrow tool and link DHR to the Deer Harvest Rate.
Then control-shift click on the Deer Harvest Rate and set it equal to DHR.
You have now created all the necessary changes and the model should run with the new
sector present.
To be sure every equation has been specified, you can click on the equations tool at the
top of your screen. Any unspecified variables will show up black. Click on these (you don't
need to Ctrl-Shift click since the equation writing tool is selected) and fix them. You can also
go to the Model menu and select Check Model. You hope it comes up "Model is A.O.K." If
not, fix the error(s) that Check Model identifies.
When you are done, you might want to look at all the equations in the model --click on the
Document Model tool at the left of the screen (see page 3). You should see your new
equations, just as you want them. Save your model!
Note that the parameters are set so that the policies are all initially inactive. You will change
these constants in reruns to test the policies. If you run the model in this condition, it should
behave exactly as before, since the new deer harvesting structures are not active. Try it: Run
your model, giving the run the name DHR0. The strip graphs or the single graph tool will
show both runs, so you can easily compare. If DHR0 behaves differently from the Base run,
go back over your changes to fix them until the model behaves just as before. Don't continue
unless it does. Call if necessary.
Save your model. Print out a model diagram (click in the diagram to make it the active
window and select Print from the File menu). Print out an equation listing by clicking on the
Document Model tool in the tool bar on the left of your screen and clicking on the little
printer icon in the window bar of the model listing. [Alternatively, click on the Clipboard
symbol (which copies all the equations onto the clipboard, and go to a word processor
document and Paste.] Hand in a model diagram and an equation listing with your new
equations highlighted somehow.
(5)
Deer harvest policy 1.
(a) Sketch a word and arrow diagram of the deer population and the deer harvesting rate
given by policy DHR1. (Leave out the rest of the model; note there is no feedback loop in
this policy, as you should see if you double click on DHR1 and select the loops tool.)
12. PAD 624, Kaibab Exercise
Page 12
(b) Simulate the deer harvesting policy 1 by clicking on the SET button and clicking on the
Constant Deer Harvest parameter. Set its new value to 1000. Name the run DHR1, and
click on the Run (runner button) to simulate.
Check the resulting predefined custom graph1 (and any strip graphs you like), and print any
you decide you want to include in what you hand in.
Then try enough other values for the constant number of deer harvested per year, to get a
good idea of what this policy is likely to do. [Always change the constant using the SET
button rather than by editing the model itself! Changes made like this always revert back to
the original model after the run.] Judge whether DHR1 is a good or bad policy.
Summarize your results (please include an illustrative plot for this exercise and the remaining
exercises).
(6)
Deer harvest policy 2.
(a) Draw a word and arrow diagram of the deer population and the structure of the deer
harvesting policy 2. (Note that there is a feedback loop here, as you should see if you double
click on DHR2 and select the loops tool. Is it positive or negative?)
(b) Simulate policy 2 by changing the fraction of deer harvested per year from zero to 0.1.
[Change the constant by clicking on the SET button and on the constant, as before.]
Try other values of the fraction of deer harvested per year until you are satisfied you
understand the effects of this policy. Summarize your results.
(7)
Deer harvest policy 3.
(a) Draw a word and arrow diagram of the deer population and the structure of the third deer
harvesting policy. (The loops tool may help. Note there is a feedback loop here. Is it
positive or negative?)
(b) The article in the Appendix suggests that 30000 would be a sustainable size for the deer
herd. Simulate policy 3, trying a Desired deer population equal to 30000.
Then try 35000. What happens? Why? Try other values of the Desired deer population if
you wish.
1 Remember: If you want to look at or print strip graphs that show only some of the runs, you can remove the
datasets you do not want to see by clicking on the Dial button and going to the Control Panel. If you click on a
loaded dataset you want to remove, it will become selected and move to the top of the list; clicking on the >>
symbol will remove that dataset from the active list. Now call up a graph, and it should display only the datasets
you want.
13. PAD 624, Kaibab Exercise
Page 13
Then try Desired deer population = 30000 with the Deer harvest year to 1926, simulating
implementation of the 30000 deer limit in 1926 instead of 1920. [You will have to change
two constants in SET mode.] What happens? What do you learn about the real world from
this simulation?
Summarize your findings about this third policy.
(8)
Policy recommendations.
What policy would you recommend to the governor? Why?
A serious question, to be answered as thoughtfully as time and energy permit: How would
you actually implement your policy recommendation?
14. PAD 624, Kaibab Exercise
Page 14
DESCRIPTION --KAIBAB PLATEAU
Prior to 1907, the deer herd on the Kaibab Plateau, which consists of some 727,000
acres and is on the north side of the Grand Canyon in Arizona, numbered about 4,000.
In 1907, a bounty was placed on cougars, wolves, and coyotes--all natural predators of
deer. Within 15 to 20 years, there was a substantial extirpation of these predators (over
8,000) and a consequent and immediate irruption of the deer population. By 1918, the
deer population had increased more than tenfold; the evident overbrowsing of the area
brought the first of a series of warnings by competent investigators, none of which
produced a much needed quick change in either the bounty policy or that deal with deer
removal. In the absence of predation by its natural predators (cougars, wolves, coyotes)
or by man as a hunter, the herd reached 100,000 in 1924; in the absence of sufficient
food, 60 percent of the herd died off in two successive winters. By then, the girdling of
so much of the vegetation through browsing precluded recovery of the food reserve to
such an extent that subsequent die-off and reduced natality yielded a population about
half that which could theoretically have been previously maintained. Perhaps the most
pertinent statement relative to the matter of the interregulatory effect of predator and
prey is the following by Aldo Leopold, one of the most significant of recent figures on
the conservation scene:
We have found no record of a deer irruption in North America antedating the
removal of deer predators. Those parts of the continent which still retain the
native predators have reported no irruptions. This circumstantial evidence
supports the surmise that removal of predators predisposes a deer herd to
irruptive behavior.
Source: E.J. Kormondy, Concepts of Ecology
(Englewood Cliffs, NJ: Prentice-Hall, 1966), p. 96.
100000
75000
50000
25000
60% of herd starved
in two winters
40,000
30,000
20,000
Probable capacity if
herd reduced in 1918
Seven successive warnings
First fawns starved
Damage seen:
first warning given
0
1905 1910 1915 1920 1925 1930 1935 1940 1945