GROSS MARGIN MANAGEMENT FRAMEWORK FOR MERCHANDISING DECISIONS IN COMPANIES WITH LARGE ASSORTMENT OF PRODUCTS

Size: px
Start display at page:

Download "GROSS MARGIN MANAGEMENT FRAMEWORK FOR MERCHANDISING DECISIONS IN COMPANIES WITH LARGE ASSORTMENT OF PRODUCTS"

Transcription

1 ECONOMICS AND MANAGEMENT: (1) ISSN (ONLINE) FOR MERCHANDISING DECISIONS IN COMPANIES WITH LARGE ASSORTMENT OF PRODUCTS Gedimias Jagelavicius Kauas Uiversity of Techology, Lithuaia Abstract Gross margi maagemet is a complex task as gross margi ca t be too high or too low i order to deliver maximum sales ad profit. Objective of the article is to preset framework which allows uderstadig ad maagig gross margi ad i compaies with large assortmet of. The framework has defied basic margi variaces pricig, cost, volume ad mix. These variaces eable to uderstad ad iterpret strategic ad merchadisig decisios of the compay. Formulas are preseted which traslate specific merchadisig decisios impact o gross margi ad gross profit, formulas allow to simplify calculatios without the eed to recalculate all assortmet o product by product basis multiple times. Derivatios of algebraic formulas are used to obtai gross margi variaces impact o gross margi ad. Cause ad effect model is used as a method to itegrate gross margi variace ito the gross margi maagemet framework. Bosto Cosultig Group matrix priciple is used to establish ad aalyse typical gross margi maagemet situatios ad iterpret behavior of customers. Coclusios compaies with large assortmet of have to maage fiacial results ad through gross margi maagemet by evaluatig merchadisig decisios impact o both ad gross margi. Four ad margi variaces, cost, volume ad mix, eed to be used to uderstad busiess situatios related to gross margi maagemet ad these four variaces ca be used as buildig blocks to aalyse specific merchadisig offers ad strategic decisios. The type of the article: Methodological article Keywords: gross margi maagemet, maagemet, variace aalyses, merchadisig decisios. JEL Classificatio: G39, M Itroductio Gross Margi maagemet is oe of the most importat ad oe of the most complex areas i maagig fiacial results of the compaies. Compaies which have higher gross margi ted to be more profitable ad ted to have stroger free cash flow - high cash flow ca be retured to shareholders or re-ivested ito the busiess, allowig the busiess to expad, without havig to rely o debt. These compaies are more resiliet to exteral eviromet impact from chage i macroecoomics or actios of competitors. Gross margi maagemet is complex task especially because gross margi ca t be too high or too low i order to deliver maximum sales ad profit ad this is differet comparig to maagemet of operatig expeses or cash flow where i may cases miimisig expeses or ivetory, accouts receivable etc. meas maximisig profit ad cash flow. Gross margi maagemet is eve more complex i compaies with large assortmet of customers behaviour iflueced by merchadisig decisios of the compay impact product mix, product mix impacts actual cost of merchadisig decisios ad actual gross margi ad. Nowadays gross margi is quite widely discussed i busiess cotext it is preseted ad 6

2 Gedimias Jagelavicius explaied by compaies to shareholders ad aalysts, cosultig compaies are ready to propose gross margi icrease strategies as well exists quite extesive scietific research aalysig separate gross margi aspects or decisios which impact gross margi. The problem is that due to the reaso the subject is very wide therefore there is a lack of itegrated approach to gross margi where gross margi aalysis are liked to decisios ad compay strategy which should help select eeded decisios. Cost accoutig theory provides aalyses of cotributio or expressed i moey terms but does ot traslate it to margi impact expressed i percetage poits which is extremely importat for compaies with large product assortmet. As well cost accoutig is focusig o fiacial aspect i this way loosig lik to merchadisig ad sales promotio. O the other side merchadisig ad sales promotio researches are focusig o sales ad marketig side without the lik to fiace. The objective of this article is to preset framework which would allow uderstadig gross margi ad drivers, likig it to product merchadisig ad strategic decisios ad allowig usig it i compaies which have big assortmet of. Gross profit ad gross margi as performace idicators are chose i order to make the framework practically easy applicable. Classical cost accoutig (Horgre, Datar, Raja, 2010) proposes cotributio margi idicator which additioally takes ito accout expeses directly related to aalysed situatio or decisio. I this article ad i my proposed solutio I limit aalyses to the ad gross margi without takig ito accout operatig expeses for the simplicity purposes: Compaies with large assortmet is complex eough therefore busiess ad decisio aalyses should be split ito smaller steps. Gross profit ad gross margi aalyses should be oe of the first steps. Compaies which do ot have developed sophisticated performace aalyses system as a step 1 ca start with my proposed gross margi aalyses. Later o after the compay is used ad fully uderstad ad gross margi it ca add o operatig expeses to their aalyses ad move to cotributio margi idicator as a step 2. Oly those merchadisig decisios which directly impact fiacial result are i scope for this article, the impacts of these decisios ca be measured by the proposed framework. So impacts of pricig, offers ad promotios, up-sell, cross-sell, samplig ad similar decisios are measured by the proposed framework. Merchadisig elemets such as visualisatio, store desig etc. with o direct attributio to fiacial result is out of scope for the proposed gross margi maagemet framework. Research o differet aspects of Gross Margi or Merchadisig decisios impactig gross margi is quite extesive, I would like to metio those most related to this article Hurlbut (2005) states importat aspects of gross margi maagemet ad lists most commo mistakes related to gross margi i retail idustry; Cushma (2011) liks merchadisig decisios to fiacials mostly for small busiess; Shah & Kumar (2012) aalyse merchadisig decisios, specifically cross-sellig, impact o customers behaviour ad impact o compay profit; Goldratt, Eshkoli & Browleer (2009) preset a problem whe icorrect merchadisig ad sales promotio decisios dilute fiacial performace of large assortmet sellig busiess, solutio based o theory of costraits aligs merchadisig decisios to right strategy which allows cosiderably improve profit, margi ad retur. Cosultig compaies propose ready to implemet solutios directed to gross margi maagemet e.g. Boulder group s itegrated gross margi improvemet program focuses o gross margi maagemet process, strategic ad tactical decisios; Siburg Compay has a margi icrease solutio focusig o pricig, cost ad other gross margi drivers. 2. Theoretical backgroud - Gross profit, Gross Margi ad its variaces i the cotext of merchadisig decisios Gross profit is the differece betwee reveue ad cost of goods sold. Gross Margi is the ratio of to reveue. Depeds o situatio or decisio aalyzed both or oe of these two performace idicators ca be more suitable. For merchadisig decisios i compay with large 7

3 Gedimias Jagelavicius assortmet of expressed i moey terms eeds to be used whe measurig fiacial result o the level of all product assortmet or o the level of big product group. This allows to see what is the overall fiacial result without diggig ito details. Gross margi expressed i percetage is more useful whe we look at the details e.g. we ca t pla exactly the from particular product because we do t kow exact quatities we are goig to sell because customer has wide rage of similar to choose i compaies with large assortmet. Differetly to gross profit, gross margi ca be plaed quite exact o product level as compay itself sets, defies discout, promotioal offer etc. ad compay kows the cost to produce or buy. As well margis expressed i percetage are more suitable whe compariso betwee or product groups eeds to be doe as expressed i moey terms ca vary very much depedig o product is expesive or ot, is o promotio or sold at regular etc. Therefore both idicators gross profit ad margi are importat to track whe makig ad aalyzig merchadisig decisios. Cost accoutig theory has variace aalyses which ca split profit variace ito groups based o ature of variace. Bhimai, Horgre (2008) defie sellig, cost per uit ad quatities sold variaces. Sold quatities variace is further split ito sales-mix variace ad salesvolume variace. I am usig these classical cost accoutig variaces as a buildig blocks for the gross margi maagemet framework. Table 1 presets how the proposed framework simplifies (marked grey) ad ehaces (marked light blue) the variaces of cost accoutig. Table 1. Compariso of Variace aalyses the gross margi framework vs. classical cost accoutig Variaces: Variace expressed i Variace measures differece i Variaces of Actual vs. pla or last year are calculated at the level of Variace for aalysig potetial ivestmet or savig decisio i plaig stage is doe at the level of Classical Cost acc. Cost Quatity: - Mix - volume Absolute profit (moey) Cotributio by product ad summed up by product ad summed up Proposed framework Cost Quatity: - Mix - volume Absolute profit (moey) & Gross Margi poits Gross profit ad Gross Margi Oe of the compoet (e.g. Gross profit variaces) is calculated at product by product basis. Traslatio to other compoet (e.g. Gross margi) is doe with simple formula with o eed to recalculate at product by product level Assumptio ca be directly traslated ito variace by usig formula Commet No differece More coveiet to pla ad make assumptios for large assortmet of Classical cost acc. takes ito accout expeses; the framework proposes practical solutio for compaies with large assortmet ad does ot take i scope operatig expeses No differece i effort Less effort, o eed to recalculate o product by product basis 8

4 Gedimias Jagelavicius 3. Gross profit ad Gross margi variaces From (1) ad gross margi (2) formulas we ca see that variace ca occur due to chage i, Cost ad quatities or i other words differet mix sold. GP Reveue CostofGoods Q ( P C ) (1) GM GP Reveue Q ( P GP - ; GM - gross margi; P - of specific product excl. value added tax; C cost of specific product per uit; Q - quatity of specific product sold. Q P C ) To calculate variaces formulas (3-6) should be used, alteratively 4 scearios eed to be calculated ad differece of ad margi betwee scearios would show variace: quatity or variace ca be obtaied by proportioally reducig all the uits i base sceario i order to arrive at actual uits sold while s per product ad costs per uit eed to stay as i base sceario. Differece of Gross profit ad margi betwee this recalculated sceario (example i Table 4) ad base sceario (Table 2) would give variace. Mix variace ca be obtaied by keepig s per product ad cost per uit as i budget sceario but uits sold replacig with actual quatities. Differece of this sceario (Table 5) ad previously described volume variace sceario would give Mix variace. variace ca be calculated by keepig actual quatities sold ad actual s per product ad just cost are as i budget. Differece of this sceario (Table 6) versus Mix calculatio sceario would give variace. Cost variace is calculated by deductig Gross profit ad gross margi of Actual sceario from variace sceario. Graphical presetatio ad summary of example aalysed i Tables 2-7 is i Figure 1. Var Q ( P P ) (3) A A A A B CostVar Q ( C C ) (4) B Var ( Q Q ) M GP (5) A BT MixVar Q ( M M ) GP (6) QA B B - quatity i uits of product actually sold; Q - total quatity of all uits actually sold, from product 1 to product ; QBT B B - total quatity of uits projected to sell i base sceario, e.g. budget or last year; PA - Actual per uit of product ; PB - per uit of product i base sceario; CA - Actual cost per uit of product ; CB - uit of product i base sceario; M B - Mix percetage i base sceario of product, e.g. if pla is to sell 3 uits of specific product ad total uits sold pla is 100 the mix percetage of this product is 3%; (2) 9

5 Gedimias Jagelavicius M A - Mix percetage of product i actual sceario; GPB - of 1 uit of product i base sceario. Table 2. Budget Sceario Budget Quatity uit Profit Margi A % B % Total % Table 3. Actual Sceario Actual Quatity uit Profit Margi A % B % Total % Table 4. variace Sceario Variace sceario Quatity uit Profit Margi variace A % % B % % Total % % Table 5. Mix variace Sceario Mix Variace sceario Quatity uit Profit Margi Mix variace A % % B % (210) 0.0% Total % % Table 6. variace Sceario Variace sceario Quatity uit Profit Margi variace A % (275) -5.0% B % % Total % (225) -3.9% Table 7. Cost variace Sceario Variace sceario Quatity uit Profit Margi Cost variace A % (165) -20.0% B % - 0.0% Total % (165) -17.8% 10

6 Gedimias Jagelavicius It is very importat to make calculatios i the order as described above first calculate volume the mix the ad lastly cost variace. Calculatio of scearios i differet order would give differet result ad would ot have ecoomic sese e.g. if by mistake we calculate variace by keepig budgeted uits ad costs, replacig s to actual ad comparig it to budget sceario the i case of icreases we would observe overestimated pricig impact as differece i we would multiply by budgeted volume which probably was higher whe icrease was ot plaed. I compaies with large assortmet of volume variace ca be meaigless if compay sells very differet especially whe poits are very differet. I such case decrease i volume of expesive product does ot have equal ecoomic meaig as decrease i volume of cheap product. Solutio would be to measure volume variace by comparable product categories ad after that to group volume variace together with mix variace whe comparig o the level of all assortmet. 385 (11,4%) +285 (-10.3%) 290 (72,5%) 290 (0,0%) 225 (3,9%) 165 (17,8%) 575 (62,2%) Budget Mix Cost Actual Figure 1. Presetatio ad summary of Gross profit ad margi variace for aalysed example Formulas 3-6 calculates variaces. To calculate gross margi variaces we ca do multiple recalculatios as preseted i tables 2-7, but for the large assortmet it would be resource cosumig therefore already havig variaces it is easy to traslate it to gross margi variaces. Formulas were derived by the author of this article usig algebraic formulas derivatio method. As we kow volume variace has o margi impact therefore i all cases gross margi impact due to volume will be equal to zero. Gross margi Mix,, Cost variaces ca be calculated usig formulas 7-9. Var ( C CostVar ) VarGM % (7) S ( S Var ) CostVar CostVarGM % (8) S Var MixVar GM GM Var CostVar (9) GM% % BT% GM% GM% Var GM% - Gross margi variace for all assortmet or part of the assortmet expressed i gross margi poits; CostVarGM% - Gross margi cost variace for all assortmet or part of the assortmet expressed i gross margi poits; MixVarGM% - Gross margi mix variace for all assortmet or part of the assortmet expressed i gross margi poits; Var - Gross profit variace expressed i moey terms; CostVar- Gross profit cost variace expressed i moey terms; C - Actual total cost of all assortmet or part of the assortmet, ca be take from P&L report; 11

7 Gedimias Jagelavicius S - Actual total sales of all assortmet or part of the assortmet, ca be take from P&L report; GM % - Gross margi of all assortmet or part of the assortmet i Actual sceario, ca be take from P&L report; GMBT% - Gross margi of all assortmet or part of the assortmet i Base sceario, ca be take from P&L report. Merchadisig decisios impact all 4 types of variaces. Usual logic of merchadisig is to ivest i gross margi i order to icrease sales ad. Table 8 presets examples of offers used ad its impact o ad gross margi through variaces i situatio whe compay icrease spedig i the offers versus base sceario. If compay decrease spedig i the offers the impacts o variaces are opposite to those metioed i the table. Table 8. Merchadisig promotio offers impact o profit ad margi variace whe compay icrease ivestmet i the offers Promotio example Discout e.g. 40% off for particular product. Coupos e.g. is lower with preseted coupo. - Loyalty reward programs e.g. collect miles/poits ad redeem it for additioal product or services. Kids eat free Buy 1 & get 1 free or 3 for the of 2 Mix Cost Discout should icrease volume therefore volume variace will be positive with o impact to gross margi due to ature of volume variace. should icrease as cliets ted to choose our compay vs. competitio to obtai beefits therefore volume variace goig to be positive, o impact o gross margi. Discouted volume will icrease ad it ca caibalize sales of other so their volumes ca decrease. Impact to margi & profit is positive if promoted product margi is above average vs. the margi of total assortmet ad egative if promoted product margi is below average No mix variace as usually loyalty rewards are give o full assortmet Gross profit ad gross margi will decrease as discout impacts No chage to therefore o variace No impact to ad margi due to cost Cost var. is egative for & margi. Negative gross profit var. equals to cost of which ca be redeemed from collected poits. Gross margi variace equals cost of redeemed divided by reveue. Overall impact to Gross profit & margi Promotio is overall gross profit variace is positive - gross profit var. is more tha offset by sum of volume ad mix variaces. Overall Gross margi variace will be egative uless discouted remai with higher tha average gross margi eve after discoutig Offer is egative cost variace is more tha off-set by positive volume variace. Overall Gross margi variace will stay egative due to this offer. 12

8 Gedimias Jagelavicius Promotio example Free samplig Bous pack e.g. of 1 liter is the same as 0.75 l Loss leader sellig oe or few at loss or little profit i order to attract customers to buy other Moey refud offer e.g. buy at regular but you ca retur if you do t like them Mix Cost variace positive as customers are goig to buy more of those which they tried through samplig of Bous pack product will icrease ad it will result i positive variace variace is positive variace is positive as cautious customers are goig to try Mix is goig to be positive if sampled have higher tha average gross margi ad egative if sampled have lower tha average gross margi Mix is positive if bous pack product has higher tha average gross margi ad opposite if bous pack has lower gross margi comparig to total assortmet Mix depeds o volume icrease of with higher tha average gross margi vs. volume icrease of with lower tha average gross margi Mix variace is positive if with higher gross margi will be drive by this offer No chage to therefore o variace No chage to therefore o variace variace egative for both gross profit ad gross margi No variace Cost variace is egative for & margi. Negative gross profit variace equals cost of samples. Gross margi variace equals cost of samples divided by reveue. Negative cost var. for profit ad margi equals to icrease i product costs bous package vs. regular package cost multiplied by actual quatity sold No cost variace Gross profit cost var. is egative ad equals to the cost of retured which ca t be resold. Gross margi variace is cost of retured usalable divided by reveue. Overall impact to Gross profit & margi Offer is egative cost var. is more tha off-set by sum of volume ad mix var. Overall Gross margi variace will stay egative due to this offer. Offer is egative cost var. is more tha off-set by sum of volume ad mix variaces. Overall Gross margi var. will stay egative due to this offer. Promotio is variace is more tha off-set by sum of volume ad mix variaces. Overall Gross margi variace will be egative. Offer is egative cost variace is more tha off-set by sum of volume ad mix variaces. 13

9 Gedimias Jagelavicius 4. Gross margi maagemet framework Now we kow that ad margi eeds to be aalyzed by calculatig variaces which helps to idetify the reaso or driver for icrease or decrease i profit ad margi. To apply this theory i practice ad make it meaigful i maagig the compay we eed to take ito accout compay strategy ad merchadisig decisios which are made to drive sales. Combiig strategy ad merchadisig decisios with gross margi/profit variaces aalyzes allows to measure where do we go i terms of directio defied by strategy ad esures merchadisig decisios are aliged with strategy. Strategy will give us a aswer to questio - how compay does wat to develop. Let s say compay has a strategy to grow through itroducig ew. I this case our ad margi aalysis eeds to split all assortmet ito groups depedig o time of itroductio. After calculatig ad gross margi ivestmet or di-ivestmet for each group we kow exactly how much ad where do we ivest i each product group. Similarly compay ca have a strategy to grow through few strategic categories of product ad fiace the growth through icreases i o-sesitive. I this case we split assortmet ito groups based o strategic priorities ad measure ivestmet (di-ivestmet) for each group separately. Figure 2 presets example where we ca see that compay was drivig ew by ivestig i cost (improvemet of product quality or stroger merchadisig offer of the ew product impactig cost variace) ad at the same time icreasig s ad growig volume i this product group. Last year s were icreasig volume due to decrease i s ad at the same time compay was savig o cost of last year s. Overall result was deteriorated by which fiish life cycle volume was decliig eve with decreases ad declie of from these were ot off-set by ewly itroduced therefore overall ad margi of the compay declied. +40 (10.0%) 330 (82,5%) +10 (+3.5%) (85,0%) (-13.7%) 290 (72,5%) 285 (71,3%) Last year total Mix Cost Most ew Mix Cost Last Mix Cost year itrod. Prod. Actual total New s Last year s Fiishig life-cycle Figure 2. Example of aalyzes of strategic product groups & margi Merchadisig decisios drive sales ad growth of. It is very importat to measure success ad impact of each decisio therefore to have good quality of iformatio we ca split all assortmet of by type of promotio ad measure success of each offer. If discoutig decisio with X poits of margi ad Y dollars ivestmet i pricig results i greater volume ad mix variace the the offer is successful ad i this way we ca measure retur of each type of offer. For example retur o ivestmet of samplig offer described i table 8 ca be calculated by dividig overall icrease drive by samplig by cost variace of samplig offer. The gross margi maagemet framework aalyses assortmet by splittig it ito groups 14

10 Gedimias Jagelavicius depedig o compay strategy ad each promotio type withi assortmet is aalysed separately. Ivestmet or divestmet is measured by calculatig ad gross margi variaces (Figure 3). Group A (e.g. ew ) split ito 4 variaces Group B (e.g. last year itroduced ) split ito 4 variaces.. Group N (e.g. ed of the lifecycle) split ito 4 variaces Strategic groupig of assortmet Mix Cost 4 Gross Profit & Margi variaces Offers type 1 (e.g. discoutig)split ito 4 var. Offers type 2 (e.g. samplig) split ito 4 var.. Offers type N (e.g. 2 for of 1) split ito 4 var. Merchadisig promotioal offers Figure 3. Gross margi maagemet framework 5. Why is ot eough to measure oly variace Classical cost accoutig measures profit or cotributio variaces where variace is expressed i moey terms. The framework proposed by this article additioally measures margi variace. It is importat to uderstad ot oly but as well gross margi variace as gross margi variace gives additioal dimesio to uderstad behavior of customers. Figure 4 presets top level two-dimesioal customer behavior aalysis whe both dimesios ad gross margi variace are aalyzed. Goig deeper ito variaces we still eed to look at both profit variace ad margi variace, e.g. Figure 5 presets example of coclusios which ca be made whe aalyzig iter-relatio of gross margi mix variace with volume variace. Similarly whe aalyzig particular offer, e.g. discoutig we ca see what has happeed to variace i relatioship to quatity ad together quatity ad mix variace. Gross margi variace is the iput to aalyze offers impactig s such as discoutig if variace was egative meas compay ivested i the offer more tha i base sceario (e.g. last year) ad if quatity variace was positive meas customers liked the offer, if quatity ad mix variace was positive this discoutig offer did t caibalize other offers. + - Total Gross Profit variace Gross Margi ivestmet pays back i gross profit icrease Ivestmet was ot eough to growth or ot attractive to customers There is a space to icrease gross margi further Gross margi icrease was too high ad fired back impactig decrease i profit - + Total Gross Margi variace Figure 4. Two-dimesioal aalysis of merchadisig decisios 15

11 Gedimias Jagelavicius This article is limited with descriptio of few situatios whe aalyzig ad margi variace as it is impossible to list all the situatios ad preset big variety of coclusios which are possible to make by usig the proposed framework ad aalyzig big assortmet by busiess usig two dimesios ad gross margi combied with classical 4 variaces, cost, volume, mix. 6. Coclusios Both gross margi ad eed to be aalyzed whe evaluatig strategic ad merchadisig decisios of the compay. Compaies with large assortmet of have to rely o gross margi maagemet vs. maagemet whe plaig at a detailed level. Classical, cost, mix, volume variace is a tool to aalyze ad margi drivers. Profit ad margi variace formulas allow to make calculatios i shorter way without the eed of multiple recalculatios. Gross margi maagemet framework preseted i the article allows to evaluate strategic decisios ad calculate retur of differet merchadisig offers. + - Gross Profit ($) variace Customers geerally like offers but choose cheaper Customers pick cheaper offers ad overall customer propositio is ot attractive or too expesive Customers like our offers ad customer propositio is likely to pay-back Offers with higher tha average gross margi were supported but other offers lack support - + Gross Margi (%) Mix variace Figure 5. Customer behavior aalysis from volume ad mix variaces Refereces Bhimai, A., Horgre, Ch., Datar, S.M., Foster, G. (2008). Maagemet ad Cost accoutig, 4th editio. Pearso Educatio Limited. Cushma, L.M. (2011). A Practical Approach to Merchadisig Mathematics. Fairchild Books. Goldtratt, E.M., Eshkoli, I., Browleer, J. (2009). Is't It Obvious? North River Press Publishig Corp. Horgre, Ch., Datar, S.M., Raja, M. (2010). Cost Accoutig, 14th editio. Pretice Hall. Hurlbut, T. (2005). Gross Margi the Overlooked Metric. Ic Magazie, September. Shah, D. & Kumar, V. (2012). The Dark Side of Cross-Sellig. Harvard Busiess Review, December,

*The most important feature of MRP as compared with ordinary inventory control analysis is its time phasing feature.

*The most important feature of MRP as compared with ordinary inventory control analysis is its time phasing feature. Itegrated Productio ad Ivetory Cotrol System MRP ad MRP II Framework of Maufacturig System Ivetory cotrol, productio schedulig, capacity plaig ad fiacial ad busiess decisios i a productio system are iterrelated.

More information

Page 1. Real Options for Engineering Systems. What are we up to? Today s agenda. J1: Real Options for Engineering Systems. Richard de Neufville

Page 1. Real Options for Engineering Systems. What are we up to? Today s agenda. J1: Real Options for Engineering Systems. Richard de Neufville Real Optios for Egieerig Systems J: Real Optios for Egieerig Systems By (MIT) Stefa Scholtes (CU) Course website: http://msl.mit.edu/cmi/ardet_2002 Stefa Scholtes Judge Istitute of Maagemet, CU Slide What

More information

Institute of Actuaries of India Subject CT1 Financial Mathematics

Institute of Actuaries of India Subject CT1 Financial Mathematics Istitute of Actuaries of Idia Subject CT1 Fiacial Mathematics For 2014 Examiatios Subject CT1 Fiacial Mathematics Core Techical Aim The aim of the Fiacial Mathematics subject is to provide a groudig i

More information

Supply Chain Management

Supply Chain Management Supply Chai Maagemet LOA Uiversity October 9, 205 Distributio D Distributio Authorized to Departmet of Defese ad U.S. DoD Cotractors Oly Aim High Fly - Fight - Wi Who am I? Dr. William A Cuigham PhD Ecoomics

More information

INVESTMENT PERFORMANCE COUNCIL (IPC) Guidance Statement on Calculation Methodology

INVESTMENT PERFORMANCE COUNCIL (IPC) Guidance Statement on Calculation Methodology Adoptio Date: 4 March 2004 Effective Date: 1 Jue 2004 Retroactive Applicatio: No Public Commet Period: Aug Nov 2002 INVESTMENT PERFORMANCE COUNCIL (IPC) Preface Guidace Statemet o Calculatio Methodology

More information

where: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return

where: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return EVALUATING ALTERNATIVE CAPITAL INVESTMENT PROGRAMS By Ke D. Duft, Extesio Ecoomist I the March 98 issue of this publicatio we reviewed the procedure by which a capital ivestmet project was assessed. The

More information

CCH CRM Books Online Software Fee Protection Consultancy Advice Lines CPD Books Online Software Fee Protection Consultancy Advice Lines CPD

CCH CRM Books Online Software Fee Protection Consultancy Advice Lines CPD Books Online Software Fee Protection Consultancy Advice Lines CPD Books Olie Software Fee Fee Protectio Cosultacy Advice Advice Lies Lies CPD CPD facig today s challeges As a accoutacy practice, maagig relatioships with our cliets has to be at the heart of everythig

More information

Agenda. Outsourcing and Globalization in Software Development. Outsourcing. Outsourcing here to stay. Outsourcing Alternatives

Agenda. Outsourcing and Globalization in Software Development. Outsourcing. Outsourcing here to stay. Outsourcing Alternatives Outsourcig ad Globalizatio i Software Developmet Jacques Crocker UW CSE Alumi 2003 jc@cs.washigto.edu Ageda Itroductio The Outsourcig Pheomeo Leadig Offshore Projects Maagig Customers Offshore Developmet

More information

CHAPTER 3 THE TIME VALUE OF MONEY

CHAPTER 3 THE TIME VALUE OF MONEY CHAPTER 3 THE TIME VALUE OF MONEY OVERVIEW A dollar i the had today is worth more tha a dollar to be received i the future because, if you had it ow, you could ivest that dollar ad ear iterest. Of all

More information

Enhancing Oracle Business Intelligence with cubus EV How users of Oracle BI on Essbase cubes can benefit from cubus outperform EV Analytics (cubus EV)

Enhancing Oracle Business Intelligence with cubus EV How users of Oracle BI on Essbase cubes can benefit from cubus outperform EV Analytics (cubus EV) Ehacig Oracle Busiess Itelligece with cubus EV How users of Oracle BI o Essbase cubes ca beefit from cubus outperform EV Aalytics (cubus EV) CONTENT 01 cubus EV as a ehacemet to Oracle BI o Essbase 02

More information

Investing in Stocks WHAT ARE THE DIFFERENT CLASSIFICATIONS OF STOCKS? WHY INVEST IN STOCKS? CAN YOU LOSE MONEY?

Investing in Stocks WHAT ARE THE DIFFERENT CLASSIFICATIONS OF STOCKS? WHY INVEST IN STOCKS? CAN YOU LOSE MONEY? Ivestig i Stocks Ivestig i Stocks Busiesses sell shares of stock to ivestors as a way to raise moey to fiace expasio, pay off debt ad provide operatig capital. Ecoomic coditios: Employmet, iflatio, ivetory

More information

Agency Relationship Optimizer

Agency Relationship Optimizer Decideware Developmet Agecy Relatioship Optimizer The Leadig Software Solutio for Cliet-Agecy Relatioship Maagemet supplier performace experts scorecards.deploymet.service decide ware Sa Fracisco Sydey

More information

Digital Enterprise Unit. White Paper. Web Analytics Measurement for Responsive Websites

Digital Enterprise Unit. White Paper. Web Analytics Measurement for Responsive Websites Digital Eterprise Uit White Paper Web Aalytics Measuremet for Resposive Websites About the Authors Vishal Machewad Vishal Machewad has over 13 years of experiece i sales ad marketig, havig worked as a

More information

To c o m p e t e in t o d a y s r e t a i l e n v i r o n m e n t, y o u n e e d a s i n g l e,

To c o m p e t e in t o d a y s r e t a i l e n v i r o n m e n t, y o u n e e d a s i n g l e, Busiess Itelligece Software for Retail To c o m p e t e i t o d a y s r e t a i l e v i r o m e t, y o u e e d a s i g l e, comprehesive view of your busiess. You have to tur the decisio-makig of your

More information

Analyzing Longitudinal Data from Complex Surveys Using SUDAAN

Analyzing Longitudinal Data from Complex Surveys Using SUDAAN Aalyzig Logitudial Data from Complex Surveys Usig SUDAAN Darryl Creel Statistics ad Epidemiology, RTI Iteratioal, 312 Trotter Farm Drive, Rockville, MD, 20850 Abstract SUDAAN: Software for the Statistical

More information

LEASE-PURCHASE DECISION

LEASE-PURCHASE DECISION Public Procuremet Practice STANDARD The decisio to lease or purchase should be cosidered o a case-by case evaluatio of comparative costs ad other factors. 1 Procuremet should coduct a cost/ beefit aalysis

More information

Learning objectives. Duc K. Nguyen - Corporate Finance 21/10/2014

Learning objectives. Duc K. Nguyen - Corporate Finance 21/10/2014 1 Lecture 3 Time Value of Moey ad Project Valuatio The timelie Three rules of time travels NPV of a stream of cash flows Perpetuities, auities ad other special cases Learig objectives 2 Uderstad the time-value

More information

Terminology for Bonds and Loans

Terminology for Bonds and Loans ³ ² ± Termiology for Bods ad Loas Pricipal give to borrower whe loa is made Simple loa: pricipal plus iterest repaid at oe date Fixed-paymet loa: series of (ofte equal) repaymets Bod is issued at some

More information

Lesson 17 Pearson s Correlation Coefficient

Lesson 17 Pearson s Correlation Coefficient Outlie Measures of Relatioships Pearso s Correlatio Coefficiet (r) -types of data -scatter plots -measure of directio -measure of stregth Computatio -covariatio of X ad Y -uique variatio i X ad Y -measurig

More information

CHAPTER 11 Financial mathematics

CHAPTER 11 Financial mathematics CHAPTER 11 Fiacial mathematics I this chapter you will: Calculate iterest usig the simple iterest formula ( ) Use the simple iterest formula to calculate the pricipal (P) Use the simple iterest formula

More information

Hypothesis testing. Null and alternative hypotheses

Hypothesis testing. Null and alternative hypotheses Hypothesis testig Aother importat use of samplig distributios is to test hypotheses about populatio parameters, e.g. mea, proportio, regressio coefficiets, etc. For example, it is possible to stipulate

More information

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions Chapter 5 Uit Aual Amout ad Gradiet Fuctios IET 350 Egieerig Ecoomics Learig Objectives Chapter 5 Upo completio of this chapter you should uderstad: Calculatig future values from aual amouts. Calculatig

More information

facing today s challenges As an accountancy practice, managing relationships with our clients has to be at the heart of everything we do.

facing today s challenges As an accountancy practice, managing relationships with our clients has to be at the heart of everything we do. CCH CRM cliet relatios facig today s challeges As a accoutacy practice, maagig relatioships with our cliets has to be at the heart of everythig we do. That s why our CRM system ca t be a bolt-o extra it

More information

Grow your business with savings and debt management solutions

Grow your business with savings and debt management solutions Grow your busiess with savigs ad debt maagemet solutios A few great reasos to provide bak ad trust products to your cliets You have the expertise to help your cliets get the best rates ad most competitive

More information

Supply Chain Management

Supply Chain Management Supply Chai Maagemet Douglas M. Lambert, Ph.D. The Raymod E. Maso Chaired Professor ad Director, The Global Supply Chai Forum Supply Chai Maagemet is NOT a New Name for Logistics The Begiig of Wisdom Is

More information

How to use what you OWN to reduce what you OWE

How to use what you OWN to reduce what you OWE How to use what you OWN to reduce what you OWE Maulife Oe A Overview Most Caadias maage their fiaces by doig two thigs: 1. Depositig their icome ad other short-term assets ito chequig ad savigs accouts.

More information

Incremental calculation of weighted mean and variance

Incremental calculation of weighted mean and variance Icremetal calculatio of weighted mea ad variace Toy Fich faf@cam.ac.uk dot@dotat.at Uiversity of Cambridge Computig Service February 009 Abstract I these otes I eplai how to derive formulae for umerically

More information

FM4 CREDIT AND BORROWING

FM4 CREDIT AND BORROWING FM4 CREDIT AND BORROWING Whe you purchase big ticket items such as cars, boats, televisios ad the like, retailers ad fiacial istitutios have various terms ad coditios that are implemeted for the cosumer

More information

Wells Fargo Insurance Services Claim Consulting Capabilities

Wells Fargo Insurance Services Claim Consulting Capabilities Wells Fargo Isurace Services Claim Cosultig Capabilities Claim Cosultig Claims are a uwelcome part of America busiess. I a recet survey coducted by Fulbright & Jaworski L.L.P., large U.S. compaies face

More information

A Guide to the Pricing Conventions of SFE Interest Rate Products

A Guide to the Pricing Conventions of SFE Interest Rate Products A Guide to the Pricig Covetios of SFE Iterest Rate Products SFE 30 Day Iterbak Cash Rate Futures Physical 90 Day Bak Bills SFE 90 Day Bak Bill Futures SFE 90 Day Bak Bill Futures Tick Value Calculatios

More information

France caters to innovative companies and offers the best research tax credit in Europe

France caters to innovative companies and offers the best research tax credit in Europe 1/5 The Frech Govermet has three objectives : > improve Frace s fiscal competitiveess > cosolidate R&D activities > make Frace a attractive coutry for iovatio Tax icetives have become a key elemet of public

More information

Evaluating Model for B2C E- commerce Enterprise Development Based on DEA

Evaluating Model for B2C E- commerce Enterprise Development Based on DEA , pp.180-184 http://dx.doi.org/10.14257/astl.2014.53.39 Evaluatig Model for B2C E- commerce Eterprise Developmet Based o DEA Weli Geg, Jig Ta Computer ad iformatio egieerig Istitute, Harbi Uiversity of

More information

1 Correlation and Regression Analysis

1 Correlation and Regression Analysis 1 Correlatio ad Regressio Aalysis I this sectio we will be ivestigatig the relatioship betwee two cotiuous variable, such as height ad weight, the cocetratio of a ijected drug ad heart rate, or the cosumptio

More information

A Guide to Better Postal Services Procurement. A GUIDE TO better POSTAL SERVICES PROCUREMENT

A Guide to Better Postal Services Procurement. A GUIDE TO better POSTAL SERVICES PROCUREMENT A Guide to Better Postal Services Procuremet A GUIDE TO better POSTAL SERVICES PROCUREMENT itroductio The NAO has published a report aimed at improvig the procuremet of postal services i the public sector

More information

Properties of MLE: consistency, asymptotic normality. Fisher information.

Properties of MLE: consistency, asymptotic normality. Fisher information. Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout

More information

Biology 171L Environment and Ecology Lab Lab 2: Descriptive Statistics, Presenting Data and Graphing Relationships

Biology 171L Environment and Ecology Lab Lab 2: Descriptive Statistics, Presenting Data and Graphing Relationships Biology 171L Eviromet ad Ecology Lab Lab : Descriptive Statistics, Presetig Data ad Graphig Relatioships Itroductio Log lists of data are ofte ot very useful for idetifyig geeral treds i the data or the

More information

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection The aalysis of the Courot oligopoly model cosiderig the subjective motive i the strategy selectio Shigehito Furuyama Teruhisa Nakai Departmet of Systems Maagemet Egieerig Faculty of Egieerig Kasai Uiversity

More information

A guide to School Employees' Well-Being

A guide to School Employees' Well-Being A guide to School Employees' Well-Beig Backgroud The public school systems i the Uited States employ more tha 6.7 millio people. This large workforce is charged with oe of the atio s critical tasks to

More information

rs e n i n Discuss various financial products for savers and nvestors Understand various types of personalities and their financial needs

rs e n i n Discuss various financial products for savers and nvestors Understand various types of personalities and their financial needs e-learig ad referece solutios for the global fiace professioal Fiacial Plaig A comprehesive e-learig co u rs e o Fi acial P la i g The themes of this product are: Kow basic cocepts i fiacial plaig Discuss

More information

leasing Solutions We make your Business our Business

leasing Solutions We make your Business our Business if you d like to discover how Bp paribas leasig Solutios Ca help you to achieve your goals please get i touch leasig Solutios We make your Busiess our Busiess We look forward to hearig from you you ca

More information

Prescribing costs in primary care

Prescribing costs in primary care Prescribig costs i primary care LONDON: The Statioery Office 13.50 Ordered by the House of Commos to be prited o 14 May 2007 REPORT BY THE COMPTROLLER AND AUDITOR GENERAL HC 454 Sessio 2006-2007 18 May

More information

INVESTMENT PERFORMANCE COUNCIL (IPC)

INVESTMENT PERFORMANCE COUNCIL (IPC) INVESTMENT PEFOMANCE COUNCIL (IPC) INVITATION TO COMMENT: Global Ivestmet Performace Stadards (GIPS ) Guidace Statemet o Calculatio Methodology The Associatio for Ivestmet Maagemet ad esearch (AIM) seeks

More information

Assessment of the Board

Assessment of the Board Audit Committee Istitute Sposored by KPMG Assessmet of the Board Whe usig a facilitator, care eeds to be take if the idividual is i some way coflicted due to the closeess of their relatioship with the

More information

Making training work for your business

Making training work for your business Makig traiig work for your busiess Itegratig core skills of laguage, literacy ad umeracy ito geeral workplace traiig makes sese. The iformatio i this pamphlet will help you pla for ad build a successful

More information

Confidence Intervals for One Mean

Confidence Intervals for One Mean Chapter 420 Cofidece Itervals for Oe Mea Itroductio This routie calculates the sample size ecessary to achieve a specified distace from the mea to the cofidece limit(s) at a stated cofidece level for a

More information

The Big Picture: An Introduction to Data Warehousing

The Big Picture: An Introduction to Data Warehousing Chapter 1 The Big Picture: A Itroductio to Data Warehousig Itroductio I 1977, Jimmy Carter was Presidet of the Uited States, Star Wars hit the big scree, ad Apple Computer, Ic. itroduced the world to the

More information

INDEPENDENT BUSINESS PLAN EVENT 2016

INDEPENDENT BUSINESS PLAN EVENT 2016 INDEPENDENT BUSINESS PLAN EVENT 2016 The Idepedet Busiess Pla Evet ivolves the developmet of a comprehesive proposal to start a ew busiess. Ay type of busiess may be used. The Idepedet Busiess Pla Evet

More information

PENSION ANNUITY. Policy Conditions Document reference: PPAS1(7) This is an important document. Please keep it in a safe place.

PENSION ANNUITY. Policy Conditions Document reference: PPAS1(7) This is an important document. Please keep it in a safe place. PENSION ANNUITY Policy Coditios Documet referece: PPAS1(7) This is a importat documet. Please keep it i a safe place. Pesio Auity Policy Coditios Welcome to LV=, ad thak you for choosig our Pesio Auity.

More information

DAME - Microsoft Excel add-in for solving multicriteria decision problems with scenarios Radomir Perzina 1, Jaroslav Ramik 2

DAME - Microsoft Excel add-in for solving multicriteria decision problems with scenarios Radomir Perzina 1, Jaroslav Ramik 2 Itroductio DAME - Microsoft Excel add-i for solvig multicriteria decisio problems with scearios Radomir Perzia, Jaroslav Ramik 2 Abstract. The mai goal of every ecoomic aget is to make a good decisio,

More information

Full Lifecycle Project Cost Controls

Full Lifecycle Project Cost Controls Full Lifecycle Project Cost Cotrols EcoSys EPC is a ext geeratio plaig ad cost cotrols software solutio deliverig best practices for full lifecycle project cost maagemet i a itegrated, easy-to-use web

More information

TIAA-CREF Wealth Management. Personalized, objective financial advice for every stage of life

TIAA-CREF Wealth Management. Personalized, objective financial advice for every stage of life TIAA-CREF Wealth Maagemet Persoalized, objective fiacial advice for every stage of life A persoalized team approach for a trusted lifelog relatioship No matter who you are, you ca t be a expert i all aspects

More information

Dilution Example. Chapter 24 Warrants and Convertibles. Warrants. The Difference Between Warrants and Call Options. Warrants

Dilution Example. Chapter 24 Warrants and Convertibles. Warrants. The Difference Between Warrants and Call Options. Warrants Chapter 24 Warrats ad Covertibles Warrats The Differece betee Warrats ad Call Optios Warrat Pricig ad the Black-Scholes Model Covertible Bods The Value of Covertible Bods Reasos for Issuig Warrats ad Covertibles

More information

Working with numbers

Working with numbers 4 Workig with umbers this chapter covers... This chapter is a practical guide showig you how to carry out the types of basic calculatio that you are likely to ecouter whe workig i accoutig ad fiace. The

More information

Chapter 2. Fixed versus Variable Costs

Chapter 2. Fixed versus Variable Costs Chapter 11 Total Hotel Reveue Maagemet Chapter 2 Key Learig Objectives: To uderstad the costs of a occupied room ad why it is importat to cosider this whe executig a reveue strategy; To uderstad why reveue

More information

THE ARITHMETIC OF INTEGERS. - multiplication, exponentiation, division, addition, and subtraction

THE ARITHMETIC OF INTEGERS. - multiplication, exponentiation, division, addition, and subtraction THE ARITHMETIC OF INTEGERS - multiplicatio, expoetiatio, divisio, additio, ad subtractio What to do ad what ot to do. THE INTEGERS Recall that a iteger is oe of the whole umbers, which may be either positive,

More information

Mathematical goals. Starting points. Materials required. Time needed

Mathematical goals. Starting points. Materials required. Time needed Level A1 of challege: C A1 Mathematical goals Startig poits Materials required Time eeded Iterpretig algebraic expressios To help learers to: traslate betwee words, symbols, tables, ad area represetatios

More information

Math C067 Sampling Distributions

Math C067 Sampling Distributions Math C067 Samplig Distributios Sample Mea ad Sample Proportio Richard Beigel Some time betwee April 16, 2007 ad April 16, 2007 Examples of Samplig A pollster may try to estimate the proportio of voters

More information

Determining the sample size

Determining the sample size Determiig the sample size Oe of the most commo questios ay statisticia gets asked is How large a sample size do I eed? Researchers are ofte surprised to fid out that the aswer depeds o a umber of factors

More information

2 Time Value of Money

2 Time Value of Money 2 Time Value of Moey BASIC CONCEPTS AND FORMULAE 1. Time Value of Moey It meas moey has time value. A rupee today is more valuable tha a rupee a year hece. We use rate of iterest to express the time value

More information

STUDENTS PARTICIPATION IN ONLINE LEARNING IN BUSINESS COURSES AT UNIVERSITAS TERBUKA, INDONESIA. Maya Maria, Universitas Terbuka, Indonesia

STUDENTS PARTICIPATION IN ONLINE LEARNING IN BUSINESS COURSES AT UNIVERSITAS TERBUKA, INDONESIA. Maya Maria, Universitas Terbuka, Indonesia STUDENTS PARTICIPATION IN ONLINE LEARNING IN BUSINESS COURSES AT UNIVERSITAS TERBUKA, INDONESIA Maya Maria, Uiversitas Terbuka, Idoesia Co-author: Amiuddi Zuhairi, Uiversitas Terbuka, Idoesia Kuria Edah

More information

Predictive Modeling Data. in the ACT Electronic Student Record

Predictive Modeling Data. in the ACT Electronic Student Record Predictive Modelig Data i the ACT Electroic Studet Record overview Predictive Modelig Data Added to the ACT Electroic Studet Record With the release of studet records i September 2012, predictive modelig

More information

EVALUATION OF THE EFFECTIVENESS OF THE QUALITY MANAGEMENT SYSTEM OF THE SERVICE ENTERPRISE

EVALUATION OF THE EFFECTIVENESS OF THE QUALITY MANAGEMENT SYSTEM OF THE SERVICE ENTERPRISE EVALUATION OF THE EFFECTIVENESS OF THE QUALITY MANAGEMENT SYSTEM OF THE SERVICE ENTERPRISE Rimatas Zajarskas, Juozas Ruževičius 2 Vilius Uiversity, Lithuaia, rimatas.zajarskas@gmail.com 2 Vilius Uiversity,

More information

Present Value Tax Expenditure Estimate of Tax Assistance for Retirement Saving

Present Value Tax Expenditure Estimate of Tax Assistance for Retirement Saving Preset Value Tax Expediture Estimate of Tax Assistace for Retiremet Savig Tax Policy Brach Departmet of Fiace Jue 30, 1998 2 Preset Value Tax Expediture Estimate of Tax Assistace for Retiremet Savig This

More information

Overview. Learning Objectives. Point Estimate. Estimation. Estimating the Value of a Parameter Using Confidence Intervals

Overview. Learning Objectives. Point Estimate. Estimation. Estimating the Value of a Parameter Using Confidence Intervals Overview Estimatig the Value of a Parameter Usig Cofidece Itervals We apply the results about the sample mea the problem of estimatio Estimatio is the process of usig sample data estimate the value of

More information

Comparing Credit Card Finance Charges

Comparing Credit Card Finance Charges Comparig Credit Card Fiace Charges Comparig Credit Card Fiace Charges Decidig if a particular credit card is right for you ivolves uderstadig what it costs ad what it offers you i retur. To determie how

More information

Sole trader financial statements

Sole trader financial statements 3 Sole trader fiacial statemets this chapter covers... I this chapter we look at preparig the year ed fiacial statemets of sole traders (that is, oe perso ruig their ow busiess). We preset the fiacial

More information

BENEFIT-COST ANALYSIS Financial and Economic Appraisal using Spreadsheets

BENEFIT-COST ANALYSIS Financial and Economic Appraisal using Spreadsheets BENEIT-CST ANALYSIS iacial ad Ecoomic Appraisal usig Spreadsheets Ch. 2: Ivestmet Appraisal - Priciples Harry Campbell & Richard Brow School of Ecoomics The Uiversity of Queeslad Review of basic cocepts

More information

A GUIDE TO BUILDING SMART BUSINESS CREDIT

A GUIDE TO BUILDING SMART BUSINESS CREDIT A GUIDE TO BUILDING SMART BUSINESS CREDIT Establishig busiess credit ca be the key to growig your compay DID YOU KNOW? Busiess Credit ca help grow your busiess Soud paymet practices are key to a solid

More information

Non-life insurance mathematics. Nils F. Haavardsson, University of Oslo and DNB Skadeforsikring

Non-life insurance mathematics. Nils F. Haavardsson, University of Oslo and DNB Skadeforsikring No-life isurace mathematics Nils F. Haavardsso, Uiversity of Oslo ad DNB Skadeforsikrig Mai issues so far Why does isurace work? How is risk premium defied ad why is it importat? How ca claim frequecy

More information

Optimize your Network. In the Courier, Express and Parcel market ADDING CREDIBILITY

Optimize your Network. In the Courier, Express and Parcel market ADDING CREDIBILITY Optimize your Network I the Courier, Express ad Parcel market ADDING CREDIBILITY Meetig today s challeges ad tomorrow s demads Aswers to your key etwork challeges ORTEC kows the highly competitive Courier,

More information

Savings and Retirement Benefits

Savings and Retirement Benefits 60 Baltimore Couty Public Schools offers you several ways to begi savig moey through payroll deductios. Defied Beefit Pesio Pla Tax Sheltered Auities ad Custodial Accouts Defied Beefit Pesio Pla Did you

More information

Subject CT5 Contingencies Core Technical Syllabus

Subject CT5 Contingencies Core Technical Syllabus Subject CT5 Cotigecies Core Techical Syllabus for the 2015 exams 1 Jue 2014 Aim The aim of the Cotigecies subject is to provide a groudig i the mathematical techiques which ca be used to model ad value

More information

CDs Bought at a Bank verses CD s Bought from a Brokerage. Floyd Vest

CDs Bought at a Bank verses CD s Bought from a Brokerage. Floyd Vest CDs Bought at a Bak verses CD s Bought from a Brokerage Floyd Vest CDs bought at a bak. CD stads for Certificate of Deposit with the CD origiatig i a FDIC isured bak so that the CD is isured by the Uited

More information

Time Value of Money. First some technical stuff. HP10B II users

Time Value of Money. First some technical stuff. HP10B II users Time Value of Moey Basis for the course Power of compoud iterest $3,600 each year ito a 401(k) pla yields $2,390,000 i 40 years First some techical stuff You will use your fiacial calculator i every sigle

More information

Modified Line Search Method for Global Optimization

Modified Line Search Method for Global Optimization Modified Lie Search Method for Global Optimizatio Cria Grosa ad Ajith Abraham Ceter of Excellece for Quatifiable Quality of Service Norwegia Uiversity of Sciece ad Techology Trodheim, Norway {cria, ajith}@q2s.tu.o

More information

Bond Valuation I. What is a bond? Cash Flows of A Typical Bond. Bond Valuation. Coupon Rate and Current Yield. Cash Flows of A Typical Bond

Bond Valuation I. What is a bond? Cash Flows of A Typical Bond. Bond Valuation. Coupon Rate and Current Yield. Cash Flows of A Typical Bond What is a bod? Bod Valuatio I Bod is a I.O.U. Bod is a borrowig agreemet Bod issuers borrow moey from bod holders Bod is a fixed-icome security that typically pays periodic coupo paymets, ad a pricipal

More information

A Balanced Scorecard

A Balanced Scorecard A Balaced Scorecard with VISION A Visio Iteratioal White Paper Visio Iteratioal A/S Aarhusgade 88, DK-2100 Copehage, Demark Phoe +45 35430086 Fax +45 35434646 www.balaced-scorecard.com 1 1. Itroductio

More information

AGC s SUPERVISORY TRAINING PROGRAM

AGC s SUPERVISORY TRAINING PROGRAM AGC s SUPERVISORY TRAINING PROGRAM Learig Today...Leadig Tomorrow The Kowledge ad Skills Every Costructio Supervisor Must Have to be Effective The Associated Geeral Cotractors of America s Supervisory

More information

For customers Key features of the Guaranteed Pension Annuity

For customers Key features of the Guaranteed Pension Annuity For customers Key features of the Guarateed Pesio Auity The Fiacial Coduct Authority is a fiacial services regulator. It requires us, Aego, to give you this importat iformatio to help you to decide whether

More information

Introducing Your New Wells Fargo Trust and Investment Statement. Your Account Information Simply Stated.

Introducing Your New Wells Fargo Trust and Investment Statement. Your Account Information Simply Stated. Itroducig Your New Wells Fargo Trust ad Ivestmet Statemet. Your Accout Iformatio Simply Stated. We are pleased to itroduce your ew easy-to-read statemet. It provides a overview of your accout ad a complete

More information

CREATIVE MARKETING PROJECT 2016

CREATIVE MARKETING PROJECT 2016 CREATIVE MARKETING PROJECT 2016 The Creative Marketig Project is a chapter project that develops i chapter members a aalytical ad creative approach to the marketig process, actively egages chapter members

More information

CCH Accountants Starter Pack

CCH Accountants Starter Pack CCH Accoutats Starter Pack We may be a bit smaller, but fudametally we re o differet to ay other accoutig practice. Util ow, smaller firms have faced a stark choice: Buy cheaply, kowig that the practice

More information

Performance Measurement In The ecommerce Industry Jamshed Mistry (E-mail: jjmistry@wpi.edu), Worcester Polytechnic Institute

Performance Measurement In The ecommerce Industry Jamshed Mistry (E-mail: jjmistry@wpi.edu), Worcester Polytechnic Institute Performace Measuremet I The ecommerce Idustry Jamshed Mistry (E-mail: mistry@wpi.edu), Worcester Polytechic Istitute Abstract The Balaced Scorecard framework (BSC) developed by Kapla ad Norto (1992) has

More information

An Approach to Fusion CRM Adoption

An Approach to Fusion CRM Adoption White Paper A Approach to Fusio CRM Adoptio May eterprise customers are ivestig time ad effort to evaluate how ext-geeratio Oracle eterprise applicatios will chage iteractios with iteral ad exteral stakeholders.

More information

CHAPTER 7: Central Limit Theorem: CLT for Averages (Means)

CHAPTER 7: Central Limit Theorem: CLT for Averages (Means) CHAPTER 7: Cetral Limit Theorem: CLT for Averages (Meas) X = the umber obtaied whe rollig oe six sided die oce. If we roll a six sided die oce, the mea of the probability distributio is X P(X = x) Simulatio:

More information

Research Method (I) --Knowledge on Sampling (Simple Random Sampling)

Research Method (I) --Knowledge on Sampling (Simple Random Sampling) Research Method (I) --Kowledge o Samplig (Simple Radom Samplig) 1. Itroductio to samplig 1.1 Defiitio of samplig Samplig ca be defied as selectig part of the elemets i a populatio. It results i the fact

More information

Solving Logarithms and Exponential Equations

Solving Logarithms and Exponential Equations Solvig Logarithms ad Epoetial Equatios Logarithmic Equatios There are two major ideas required whe solvig Logarithmic Equatios. The first is the Defiitio of a Logarithm. You may recall from a earlier topic:

More information

I. Why is there a time value to money (TVM)?

I. Why is there a time value to money (TVM)? Itroductio to the Time Value of Moey Lecture Outlie I. Why is there the cocept of time value? II. Sigle cash flows over multiple periods III. Groups of cash flows IV. Warigs o doig time value calculatios

More information

Flood Emergency Response Plan

Flood Emergency Response Plan Flood Emergecy Respose Pla This reprit is made available for iformatioal purposes oly i support of the isurace relatioship betwee FM Global ad its cliets. This iformatio does ot chage or supplemet policy

More information

CHAPTER 3 DIGITAL CODING OF SIGNALS

CHAPTER 3 DIGITAL CODING OF SIGNALS CHAPTER 3 DIGITAL CODING OF SIGNALS Computers are ofte used to automate the recordig of measuremets. The trasducers ad sigal coditioig circuits produce a voltage sigal that is proportioal to a quatity

More information

An Introduction to Logistics and the Supply Chain. An Introduction To Logistics And The Supply Chain

An Introduction to Logistics and the Supply Chain. An Introduction To Logistics And The Supply Chain Departmet of Global Busiess ad Trasportatio A Itroductio to Logistics ad the Supply Chai Itroductio Cosider bottled water. Abstract Oft times I have foud that studets come ito a course that assumes they

More information

Statement of cash flows

Statement of cash flows 6 Statemet of cash flows this chapter covers... I this chapter we study the statemet of cash flows, which liks profit from the statemet of profit or loss ad other comprehesive icome with chages i assets

More information

CCH Practice Management

CCH Practice Management 1 CCH Practice Maagemet practice maagemet facig today s challeges Every year it seems we face more regulatios, growig cliet expectatios ad lower margis o our compliace work. It s a tough time for a accoutig

More information

Erik Ottosson & Fredrik Weissenrieder, 1996-03-01 CVA. Cash Value Added - a new method for measuring financial performance.

Erik Ottosson & Fredrik Weissenrieder, 1996-03-01 CVA. Cash Value Added - a new method for measuring financial performance. CVA Cash Value Added - a ew method for measurig fiacial performace Erik Ottosso Strategic Cotroller Sveska Cellulosa Aktiebolaget SCA Box 7827 S-103 97 Stockholm Swede Fredrik Weisserieder Departmet of

More information

Z-TEST / Z-STATISTIC: used to test hypotheses about. µ when the population standard deviation is unknown

Z-TEST / Z-STATISTIC: used to test hypotheses about. µ when the population standard deviation is unknown Z-TEST / Z-STATISTIC: used to test hypotheses about µ whe the populatio stadard deviatio is kow ad populatio distributio is ormal or sample size is large T-TEST / T-STATISTIC: used to test hypotheses about

More information

Audit of Assumptions for the March 2001 Budget. REPORT BY THE COMPTROLLER AND AUDITOR GENERAL HC 304 Session 2000 2001: 7 March 2001

Audit of Assumptions for the March 2001 Budget. REPORT BY THE COMPTROLLER AND AUDITOR GENERAL HC 304 Session 2000 2001: 7 March 2001 Audit of Assumptios for the March 2001 Budget REPORT BY THE COMPTROLLER AND AUDITOR GENERAL HC 304 Sessio 2000 2001: 7 March 2001 Audit of Assumptios for the March 2001 Budget REPORT BY THE COMPTROLLER

More information

Engineering Data Management

Engineering Data Management BaaERP 5.0c Maufacturig Egieerig Data Maagemet Module Procedure UP128A US Documetiformatio Documet Documet code : UP128A US Documet group : User Documetatio Documet title : Egieerig Data Maagemet Applicatio/Package

More information

Platform Solution. White Paper. Transaction Based Pricing in BPO: In Tune with Changing Times

Platform Solution. White Paper. Transaction Based Pricing in BPO: In Tune with Changing Times Platform Solutio White Paper Trasactio Based Pricig i BPO: I Tue with Chagig Times About the Author(s) Raj Agrawal Curret Desigatio Raj heads the Platform Solutios Uit at TCS. I his career spaig over 19

More information

SOCIAL MEDIA. Keep the conversations going

SOCIAL MEDIA. Keep the conversations going SOCIAL MEDIA Keep the coversatios goig Social media is where most of the world is. It is therefore a ope source of cosumer data, a chael of commuicatio ad a platform for establishig relatioships with customers.

More information

Valuing Firms in Distress

Valuing Firms in Distress Valuig Firms i Distress Aswath Damodara http://www.damodara.com Aswath Damodara 1 The Goig Cocer Assumptio Traditioal valuatio techiques are built o the assumptio of a goig cocer, I.e., a firm that has

More information