贝恩战略分析方法分析方法varianceanalysis017

1、1 author: alton shader, james baker variance analysis march 1998 variance analysis 2 agenda what is variance analysis? linear variance ice cream co. two component variance analysis jesses brewery variance analysis with more than two components boston video key takeaways variance analysis 3 what is v

2、ariance analysis? variance analysis is used to understand and assess the drivers of change in measured variables. variance analysis helps explain and understand what drives the difference between two measures of the same variable (e.g., 1998 profit vs. 1995 profit) variance analysis explains differe

3、nces between measures by breaking those measures into their base components (e.g., 1998 revenue and 1998 opex as components of 1998 profit) and quantifying the impact of each component bain frequently uses variance analysis to quantify and identify true profit drivers help drive future analysis on t

4、he most leveraged issues variance analysis 4 the value of variance analysis why do we need to perform variance analysis? gives business insight as to what drives revenue/cost/ profit leads to actions bain uses variance analysis to gain business insight and to identify the most effective and valuable

5、 action steps. why does profit change? what driver has the most impact? what explains differences in relative cost position? used to determine product line profitability identifies areas of focus for cost reduction indicates impact of lowering price drives customer segmentation strategies variance a

6、nalysis 5 definitions in variance analysis most situations fall into one of three categories of variance analysis. description: two component understanding individual impact of two variable on a single measure linear simple comparison of one component against another more than two component understa

7、nding individual impact of more than two variables on a single measure example:1998 revenue increases driven by 1998 price increase and unit sales 1990 total cost per unit versus 1995 total cost per unit differences in customer revenue driven by number of transactions, product mix and other fees var

8、iance analysis 6 agenda what is variance analysis? linear variance ice cream co. two component variance analysis jesses brewery variance analysis with more than two components boston video key takeaways variance analysis 7 situation:orit and toms ice cream co. produce ice cream which they sell in ga

9、llon-sized containers at supermarkets around the country they have tracked their cost to produce ice cream per gallon over time and have seen it decline over five years by 25% question:what has driven costs downward? what might orit and tom focus on to achieve better cost savings going into the futu

10、re? linear variance example (ice cream co.) variance analysis 8 19951990variance production costs: (includes sales, labor, admin) $220,500$210,000$10,500 raw materials costs: $63,000$60,000$3,000 advertising expenses:$31,500$30,000$1,500 total gallons sold:70,00050,00020,000 linear variance example

11、variance analysis 9 unit production costs:$3.15$4.20($1.05) unit raw materials costs:$0.90$1.20($0.30) unit advertising costs:$0.45$0.60($0.15) total per unit costs:$4.50$6.00($1.50) 19951990variance linear variance example (variance per gallon) variance analysis 10 1990increase in production volume

12、s raw materials purchasing savings reduced advertising expense 1995 $6.00 ($1.05) ($0.30) ($0.15) $4.50 $0.00 $1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 ice cream co. cost per gallon of ice cream (1995 constant dollars) thorough bain analysis of the data allocated the reduced costs into three compone

13、nts. linear variances example (ice cream co.) variance analysis 11 linear variances example management of ice cream co. appears to have enjoyed increasing economies of scale, particularly relating to production costs, which have driven costs downward orit and tom might want to focus in the future on

14、 gaining even greater leverage in managing production costs as production volume increases variance analysis 12 agenda what is variance analysis? linear variance ice cream co. two component variance analysis jesses brewery variance analysis with more than two components boston video key takeaways va

15、riance analysis 13 situation:jesses brewery produces high-quality beers which it sells in cases in the past year, jesses brewery has experienced 15% revenue growth. during the same time, sales volumes and prices have both increased question:jesses brewery would like to understand what percent of the

16、 revenue increase comes from the increase in sales volumes, and what percent from the increase in price two component variance example - jesses brewery (1 of 6) variance analysis 14 19971998 $176.5 $203.5 $0 $50 $100 $150 $200 $250 jesses brewery annual revenues (millions of dollars) two component v

17、ariance example - jesses brewery (2 of 6) case price: cases sold: $18.20$20.00 9.7mm10.2mm what percent of the $27mm increase in revenue is due to the price increasing? the volume sold increasing? both the price and volume sold increasing? 8this is covariance, where part of the variance is not easil

18、y attributable to a single variable variance analysis 15 volume 1998 revenue $203.5mm 1997 revenue price variance (part of revenue change attributable to price) $18.20 (1997) $20.00 (1998) 10.2mm (1998) 9.7mm (1997) price volume variance (part of revenue change attributable to volume) covariance (pa

19、rt of revenue change attributable to change in both volume and price) the best way to approach variance analysis problems is to use the rectangle diagrams to intuitively understand how the changes in the two variables account for the change in the overall quantity. two component variance example - j

20、esses brewery (3 of 6) variance analysis 16 volume 1998 revenue (p2 x v2) 1997 revenue (p1 x v1) price variance (part of revenue change attributable to price) p1 (1997) p2 (1998) v2 (1998) v1 (1997) price volume variance (part of revenue change attributable to volume) co- variance step 1: volume var

21、iance = (v2 -v1) x p1 step 2: price variance = (p2 -p1) x v1 step 3: covariance = (v2 - v1) x (p2 - p1) step 4: allocate covariance to volume and price variance based on the proportion of the total for each variance -e.g., if: volume variance = $2m price variance = $1m covariance = $.5m then 66.7% o

22、f $.5 is added to the volume and 33.3% is added to the price a four-step process leads to the solution. two component variance example - jesses brewery (4 of 6) variance analysis 17 jesses brewery 1997variance data price per case$18.20 $1.8 number of cases sold (in mm)9.7.5 revenues (in $mm)$176.5$2

23、7.0 step 1: price variance$17.0 step 2: volume variance $9.1 step 3: covariance $0.9 revenue variance excluding covariance$26.1 proportions for assigning covariance price volume assignment of covariance to price variance$0.6 to volume variance $0.3 adjusted variances price variance volume variance (

24、p1)(p2 - p1) (v1)(v2 - v1) $176.5 (p1 x v1) (193.5 - 176.5) (185.6 - 176.5) (p2-p1)x(v2-v1) (17.0+9.1) (0.9x65%) (0.9x35%) 63% 34% 3% 65% 35% (17.0/27.0) (9.1/27.0) (0.9/27.0) (17.0/26.1) (9.1/26.1) $176.5 (p1 x v1) 1998 $20.00 10.2 $203.5 (p2) (v2) $185.6 (v2 x p1) $193.5 (p2 x v1) $17.6 $9.4 (17.0

25、+0.6) (9.1+0.3) variance % here is an example of an annotated spreadsheet to determine variance. two component variance example - jesses brewery (5 of 6) variance analysis 18 price variance: volume variance: covariance: $17.0mm $9.1mm $0.9mm proportions are 65% 35% 65%35% to price variance $0.6mm to

26、 volume variance $0.3mm + $17.0mm $17.6mm price $9.1mm $9.4mm volume total variances: (65%)(35%) if price and volume variances are calculated correctly, then we can take their proportions to allocate covariance. two component variance example - jesses brewery (6 of 6) variance analysis 19 negative c

27、ovariance 14.7 new (1998) 9.7 (1997) $18.20 (1997) $17.00 new (1998) volume price even if one variable decreases, the formula applies the same way. the only difference is that price variance and covariance turn negative. volume= (14.7-9.7) x $18.20 price= ($17.00-$18.20) x 9.7 = = $91.0 mm - $11.6 m

28、m covariance = (14.7-9.7) x ($17.00-$18.20) =- $6.0 mm $73.4 mmtotal variance in some situations one variable may fall as the other rises. the formula for covariance does not change. variance analysis 20 negative covariance in two variable problems, when one variable increases and one decreases (+ -

29、 ), we arrive at a negative covariance if the formulas are applied exactly as before (change only the variable whose variance we are calculating) this negative covariance (p2 - p1) x (v2 - v1) then needs assigning in proportion to the absolute values of the two variables this absolute value approach

30、 can be applied to multiple variables using the excel spreadsheet the example given is also intuitively correct (price falls, volume rises) to summarize, the methodology does not change in calculating negative covariance. variance analysis 21 agenda what is variance analysis? linear variance ice cre

31、am co. two component variance analysis jesses brewery variance analysis with more than two components boston video key takeaways variance analysis 22 more than two component variance example situation:boston video is a chain of video rental stores in the northeast u.s. in addition to renting video m

32、ovies and games, the stores sell a variety of movie-related items (popcorn, candy, film magazines). they also get money for late fees bain has been hired to help boston video segment its customer base and understand what drives the differences in spending patterns between segments question:what vari

33、ables impact revenue per customer? what is the overall variance by customer type? what are the breakdowns of that variance by customer type? what should bain focus on improving? variance analysis 23 c b a c b a c b a number of customersnumber of transactionstotal revenue 0% 20% 40% 60% 80% 100% perc

34、ent of total 11,411 customers74k transactions$441k customers were segmented into 3 groups. “a” customers represent only 20% of bostons customer base but generate 50% of store transactions and 60% of revenue. a, b, & c customers data how might you frame an analysis to understand a lot impacts revenue

35、s per customer? more than two component variance example variance analysis 24 revenue drivers framework the differences in customer spending levels between segments can be identified and isolated into two broad categories. revenue per customer number of transactions sell thru revenue rental revenue

36、late fees and other quantity product mix revenue per transaction more than two component variance example variance analysis 25 other $0.13 late fees $1.03 sell thru $1.01 video rental $4.72 $0.12 $0.66 $0.60 $4.20 $0.07 $0.34 $0.31 $3.73 abc $6.89 $5.58 $4.45 $0 $2 $4 $6 $8 dollars 2.76 1.29 0.45 ab

37、c 0.00 0.50 1.00 1.50 2.00 2.50 3.00 transactions per customer per month number of transactionsrevenue per transaction the following data was made available about customer habits. customer segmentation more than two component variance example variance analysis 26 revenue per customer per month $19.0

38、1 $7.20 $2.00 abc $0 $5 $10 $15 $20 revenue per customer per month “a” customers spent on average 2.6x the average “b” customer and nearly 10 x the average “c” customer. $11.82 $17.02 customer segment: more than two component variance example 2.76 x $6.89 1.29 x $5.38 0.45 x $4.45 variance analysis

39、27 drivers of variance revenue per transaction number of transactions revenue per transaction number of transactions b customersc customers $11.82$17.02 percent of total variance how would you complete this slide showing the split between the two variance drivers? more than two component variance ex

40、ample variance analysis 28 this spreadsheet details the calculations necessary to compute the variances and covariance for transactions and revenue per customer. facts: totaltrans/rev/total customerrev/mnthmnthtransvariance a19.01$ 2.766.88$ b7.20$ 1.295.58$ (11.82)$ c 2.00$ 0.454.45$ (17.02)$ varia

41、nce from a to b (11.82)$ %total:calculation: trans variance(10.14)$ (1.47)6.88$ 74%(b trans - a trans) times a price rev variance(3.60)$ 2.76(1.30)$ 26%+ (b price - a price) times a trans total variance before covar(13.73)$ =total variance before covariance covariance1.92$ (1.47)(1.30)$ + (b trans -

42、 a trans) times (b price - a price) answer(11.82)$ =total variance allocate covariance:1.92$ 100% trans1.42$ 74%74% to transaction rev0.50$ 26%26% to rev total delta trans(8.72)$ 74%regular trans variance plus allocation from covariance total delta price(3.09)$ 26%regular rev variance plus allocatio

43、n from covariance (11.82)$ 100%=total variance sample spreadsheet more than two component variance example variance analysis 29 sample spreadsheet variance from a to c (17.02)$ %total:calculation: trans variance(15.98)$ (2.31)6.88$ 70%(c trans - a trans) times a price rev variance(6.73)$ 2.76(2.44)$

44、 30%+ (c price - a price) times a trans total variance before covar(22.66)$ =total variance before covariance covariance5.64$ (2.31)(2.44)$ + (c trans - a trans) times (c price - a price) answer(17.02)$ =total variance allocate covariance:5.64$ 100% trans3.96$ 70%70% to transaction rev1.67$ 30%30% t

45、o rev total delta trans(11.96)$ 70%regular trans variance plus allocation from covariance total delta price(5.05)$ 30%regular rev variance plus allocation from covariance (17.02)$ 100%=total variance more than two component variance example variance analysis 30 now suppose the client wants to furthe

46、r understand what drives revenue per transaction. how would you complete this slide showing the split between the three revenue per transaction variables? late fees and other sell thru rental revenue late fees and other sell thru rental revenue bc percentage point delta to a customer segment: more t

47、han two component variance example revenue per transaction sources of variance variance analysis (revenue per transaction) variance analysis 31 sample spreadsheet customer revenue per transaction variance customertotalrentalnon-rental late feesother total variance a revenue per transaction6.88$ 4.72

48、$ 1.01$ 1.03$ 0.13$ b revenue per transaction5.58$ 4.20$ 0.60$ 0.66$ 0.12$ 1.30$ delta to a1.30$ 0.52$ 0.40$ 0.38$ 0.01$ % of total100%40%31%29%0% of 26%10%8%8%0% c revenue per transaction4.45$ 3.73$ 0.31$ 0.34$ 0.07$ 2.44$ delta to a2.44$ 0.99$ 0.69$ 0.69$ 0.06$ % of total100%41%28%28%2% of 30%12%8

49、%8%1% this spreadsheet further allocates revenue per transaction variance into types of product purchased. more than two component variance example variance analysis 32 variance analysis showed that the primary difference between customer segments was how often they came to the store. over 70% of th

50、e variance between a customers and the others was explained by transaction frequency. drivers of variance revenue per transaction $3.09 number of transactions $8.72 revenue per transaction $5.05 number of transactions $11.96 b customersc customers $11.81$17.01 0% 20% 40% 60% 80% 100% percent of tota

51、l variance 26% 74% 70% 30% more than two component variance example variance analysis 33 late fees and other 8% sell thru 8% rental revenue 10% late fees and other 10% sell thru 8% rental revenue 12% bc 26% 30% 0% 5% 10% 15% 20% 25% 30% percentage point delta to a revenue per transaction analysis wa

52、s not very telling. customer segment: revenue per transaction sources of variance variance analysis (revenue per transaction) variance analysis 34 summary what drives a customer behavior is the number of transactions they complete so, bain needs to help improve the frequency of transactions of b and c customers (assuming that a customers continue to remain loyal and that a retention strategy is therefore not the most leveraged work) variance analysis 35 agenda what is variance analysis? linear variance ic