Final Exam for ACCT 5330 - Balanced Scorecard
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Part One:
Memo
To: Christine Howard, CEO From: Jeff Benedict Date: May 12, 1998 Re: Explanation of the Balanced Scorecard
The purpose of this memo is to clarify the concept of a balanced scorecard to which you have
recently been introduced. I understand you recently heard Robert Kaplan speak on the topic, he
has made this topic popular and since it is his idea you may need some additional verification
that this idea works in the “real world.”
First we must establish what is wrong with the current system which focuses on financial
measures. Management currently makes sacrifices in the current year so things like net income
will be better reported at the cost of future financial performance. The balanced scorecard looks
at ways to measure the financial performance in the long-term. Considering research and
development costs, if you look at the first year you have a large expense and the last year large
revenue, but you have to look at it over its entire life to evaluate the performance. The balanced
scorecard first looks at the company’s mission statement and strategy then translates into four
measures by which the long-term financial performance of the organization can be assessed. The
four measures are broadly defined as organization learning & growth, internal business
processes, customer value, and financial results. The organization learning and growth comes
which have been performance measures for years. The key to the balanced scorecard idea is that
within an organization causal relationships exist such as how a change in human capital causes
changes in other areas. A balanced scorecard can tell you whether spending more time to train
employees will translate into increased profits. Through assessments of an organization one can
create causal relationships which are tied to the mission. Then this, so called model should be
tested to validate whether these relationships exist. The power of a balanced scorecard should
not be underestimated. Suppose a possible causal relationship model looks as such: increased
training, causing less defects, causing lower cycle times and ultimately increased financial
performance. Now, a strategy like increasing training can be measured with some certainty on
how it will affect the overall performance of the organization.
To address your concerns as to whether causal models can really be created and what other
management gurus think. Although, Kaplan stated some examples of effective implementations
of the balanced scorecard, the causal models will be different for every organization and may or
may not be able to be created in this organization. Through discussions you can determine what
the causal model may look like, but that model must be tested to estimate its accuracy. Many
management gurus have bought in on the idea of the balanced scorecard. It has been documented
that the French have used a similar technique for fifty years, their titled translates to English as
the "dashboard." Many articles other than those published by Kaplan and Norton were written
concerning the balanced scorecard, two in particular I would recommend. An article by Chow,
Haddad and Williamson titled, "Applying the Balanced Scorecard to Small Companies," and
another by Curtis and Ellis titled, "Balanced Scorecards for New Product Development. Both
Part Two:
(This part is answered as the responses I would have to the specific questions independent
of each other)
In response to the VP of Marketing:
This concept may very well be a fad, but SWAT analysis, ABC, Target Costing and many
other widely accepted management tools started out as management fads. Not until these
techniques are embraced worldwide and proven to be useless can they be determined to
be truly a fad. The economy today sets us in a highly competitive environment; new
ideas, and chances need to be taken in order to stay afloat. Whether a balanced scorecard
is useless and just a fad is a concern but has yet to be determined as such. As I mentioned
to Ms. Howard, a concept similar to the balanced scorecard has been used for nearly fifty
years in France. This adds some creditability to manager's perception that this tool can
work and is not just a fad. To address your second concern on the time it takes to validate
whether causal relationships exist and whether they will be obsolete. The purpose of a
balanced scorecard is to tie the mission of an organization to the financial performance
and so only if the mission of an organization is changed should the causal relationships or
model change. Considering a model in which highly educated employees equals better
customer retention and better financial performance. The mission of the organization
would be something like delivery of a quality service, and in order to maintain that
Your concern is that these relationships are just someone’s best guess, and you are right.
That is how you first determine causal relationships, but then you test these relationships
either with logic like reality checks or multiple evaluations, or you test it with statistics. I
assume many decisions you make are built off a hunch or your best guess, but to prove
that they will work you either have to roll the dice and take a chance or test the theory. In
addition you mentioned communication of strategy over a management tool. This is a
good question for it seems logical to see that it is a good method to communicate strategy,
but it is not as easy to see its manageability. By communicating strategy all personnel
will work in unity toward a common organizational goal, this in essence is the stepping
stone toward success. You no longer need to manage like you are used to, now
employees will evaluate their contribution in context of how the organization is doing
overall. Basically, you manage the employees by evaluating how well they are doing in
context to their contribution to the overall financial success of the organization.
Response to Human Resources Director:
You have to be happy if everyone buys into the program, one of its intentions is to have
all the managers working toward the mission of the organization and employing the same
strategies. I believe you are concerned about change and I agree that if you are going to
make the change to a new system it must be evaluated completely. As I have mentioned
before, the model must be tested and tested throughout all divisions, for all divisions need
Part Three:
The model is constructed as such:
Dimensions of Performance Measures of Performance
(The construction of this model is based solely on discussions with division managers and controllers)
The model begins with average grade level. Through discussions with various managers and controllers of the different divisions, an increase in the grade level would reduce the average number of defects per month, but would also increase the average hourly wage due to higher skills needing to be paid more. It is felt that a higher hourly wage will better retain employees and therefore reduce the voluntary turnover rate. If more employees are retained, then both average defects per month and cycle time per order will be reduced. The reduction of defects and cycle time will minimize the rework and overall
Avg. Grade Level Completed
Customer Value
Profitability
the model was been constructed this way. In the first line of Kaplan’s article “Why Does Business Need a Balanced Scorecard?” he states, “If you can’t measure it, you can’t manage it.”
The constructed on page 6 is developed based on logic derived from discussions with prominent individuals within the organization. To add some creditability to the model we will test it with statistics.
Part Four:
To test the model, each causal relationship was tested independently of each other. The relationship between average grade level and hourly wage was tested first. The testing was conducted by comparing the percentage change in grade level from division to division with the percentage change in dollars paid from division to division. For a more elaborate description of how the graphs were created, refer to page 10. The argument is that an increase in grade level should cause an increase in hourly wage. Here is the graphical representation.
Grade Level vs. Hourly Wage
-150%
-100%
-50%
0%
50%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
are causally linked, but not in all. There is not a valid causal relationship.
à Next the average grade level completed was compared to average defects per month. Here is the graphical representation.
Grade Level Vs. Average Defects
0%
10%
20%
30%
40%
As you can see they are not completely causally linked. Not until division seven do we see the lines running parallel with each other. After division ten you that they are a radical inverse of each other. Based on the graph we have to conclude that within some divisions these measures
This one is a slam-dunk. Within all divisions you see that when average grade level increases the average number of defects per month decreases and vice versa. A causal relationship exists between grade
à Argument is that an increase in hourly wage will reduce the voluntary turnover rate. Hourly Wage Vs. Voluntary Turnover
-60%
-40%
60%
80%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
à When voluntary turnover rate decreases, the average cycle time per order will decrease and the average defects will also decrease. Each relationship is graphed separately.
Voluntary Turnover Vs. Avg. Defects
-60%
-40%
-20%
0%
20%
40%
60%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
In many divisions the turnover rate is related to the average amount of defects, but you can also see many divisions like 2 and 15 where the average defects has an inverse relationship with the turnover rate. It appears conclusive that in most cases the turnover rate is related to the average amount of defects and is validated as a causal relationship. With the exception of a couple of divisions, 4, 13 & 14, the turnover rate is causally related to the cycle time per order. The lines are to run parallel with each other and in most cases they do.
à Average defects and cycle time in relation to the percentage of on-time deliveries.
As the average number of defects decrease, the percentage of on-time deliveries is to also increase. This effect is split about
Defects Vs. % of On-Time Deliveries
30%
40%
-60%
-40%
-20%
0%
20%
40%
60%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
You see that a causal relationship exists between hourly wage and voluntary turnover rate. They are to be inversely related. Compare division 7’s data, approximately 40% decrease in hourly wage causes an approximate10% increase in the turnover rate.
On the other hand, cycle time appears to be strongly correlated with on-time deliveries. When the cycle time as a percentage decreases, the percentage of on-time deliveries increases nearly throughout all divisions.
The argument has been made that customer value is related to the customer receiving the goods on time. The graph below depicts the relationship of on-time deliveries and customer satisfaction score.
O n - T i m e D e l i v e r i e s V s . C u s t o m e r S a t i s f a c t i o n
- 3 0 %
- 2 0 %
- 1 0 %
1 0 %
2 0 %
3 0 %
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7
For a causal relationship to exist the lines should run parallel and for the most part they do. There is a definite relationship between on-time deliveries and the customer satisfaction score. Now let’s see if the customer satisfaction score translates in the financial measure of return on assets. It is argued that if the customers are happy then they will return and therefore create a higher return on assets.
As you see in most cases, the higher the customer satisfaction score, the higher return on assets. Return on assets was computed from the table of data as throughput minus operating expenses divided by assets employed. A causal relationship exists between customer satisfaction and return on assets.
C y c le Tim e V s . % o f On-T im e D e l iver ies
-40%
-20%
0%
-30%
-20%
-10%
0%
10%
20%
30%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
RELATIONSHIP
• GRADE LEVEL VS. AVERAGE HOURLY WAGE • GRADE LEVEL VS. AVERAGE DEFECTS • HOURLY WAGE VS. VOLUNTARY TURNOVER
RATE • VOLUTARY TURNOVER RATE VS. AVERAGE
DEFECTS • VOLUNTARY TURNOVER RATE VS. AVERAGE
CYCLE TIME • AVERAGE DEFECTS VS. ON. TIME DELIVERIES • CYCLE TIME VS. ON-TIME DELIVERIES • ON-TIME DELIVERIES VS. CUSTOMER
SATISFACTION • CUSTOMER SATISFACTION VS. RETURN ON
ASSETS
How the Graphs were Created:
By using the spreadsheet of data, I took the change from one division to the next and compared that percentage to that of another measure. To demonstrate, consider the first relationship identified, Grade Level Vs. Hourly Wage.
D ivisions
D ivision to
the next 1 10.71 -15% 11.11$ 11% 2 11.93 7% 9.49$ 0% 3 11.95 0% 10.11$ -15% 4 10.15 -2% 10.13$ 14% 5 11.62 -3% 9.89$ -11% 6 10.31 -21% 9.59$ 8% 7 11.14 10% 7.59$ 7% 8 11.97 -4% 8.35$ -12% 9 10.47 8% 8.02$ 5%
10 11.02 0% 8.65$ -3% 11 10.65 -26% 8.66$ 3% 12 10.96 58% 6.42$ -8% 13 10.14 -14% 10.13$ 6% 14 10.73 -7% 8.71$ 0% 15 10.75 -29% 8.09$ -4% 16 10.36 85% 5.72$ 10% 17 11.34 -3% 10.59$ -6%
The graph is created by taking the percent change from one division to the next for grade level and comparing that with the percent change from one division to the next for average hourly wage. The graph is as follows:
Grade Level vs. Hourly Wage
-150%
-100%
-50%
0%
50%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Division 16 provides a good example of how the comparison takes place. You see the percent change for grade level jump 85% and
The advantages are that you can use the data to compute statistical correlation between the different measures in the model. It helps add confidence to your logical assumptions about causal relationships and how to measure your performance based on a balanced scorecard model. The biggest disadvantage is the validity of the numbers. Consider the customer satisfaction score that was computed by assumptions made from managers of what customers really value. The measure was computed with measurable qualities like average defects per month, but the customer could value things like brand name, appearance and other immeasurables. The balanced scorecard needs to be tested and statistical testing appears to be the most conclusive, the only thing is that the measures used to test the model should be tested before hand so that certain relationships are not excluded for inaccurate numbers.
Additional Data:
As aforementioned, using population data may create a more balanced scorecard among all the different divisions. To evaluate the performance of one division over another adjustments need to be made. If one division resides in a highly competitive market and the other does not and adjustment should be made. The most useful data may not be measurable, such as the value of quality products and quality service. The controller of Division 11 hypothesized that the quality of the processes is derived from the employee turnover rate. It is felt that this may be one component of many which equate to process quality and that not all are measurable. A measure much like customer satisfaction score but for internal processes would be useful, something like total quality management.
Part Five:
Throughout the management literature it is stated that most balanced scorecard models are not implemented until a couple of years of testing has taken place. This would be a recommendation. I would take the data computed in part four and see where the variances are that make the relationship not causal, then talk to the particular division managers about their perceptions. You want to take the implementation slowly, for as was mentioned by the director of human resources everyone will go along, so everyone will either sink or swim. A pilot program on one division would not be effective, for the balanced scorecard is to represent the organization as a whole, plus it is long-term in nature.
The opportunity to better understand your business processes and how all divisions match
Resources Used:
"Why Does Business Need a Balanced Scorecard?" by Kaplan and Norton
"Why Does Business Need a Balanced Scorecard? (Part Two)" by Kaplan and Norton
"Applying the Balanced Scorecard to Small Companies," by Chow, Haddad, and Williamson
"Balanced Scorecards for New Product Development," by Curtis and Ellis
Lectures given by Dr. Frank Selto
Part One:
Memo
To: Christine Howard, CEO From: Jeff Benedict Date: May 12, 1998 Re: Explanation of the Balanced Scorecard
The purpose of this memo is to clarify the concept of a balanced scorecard to which you have
recently been introduced. I understand you recently heard Robert Kaplan speak on the topic, he
has made this topic popular and since it is his idea you may need some additional verification
that this idea works in the “real world.”
First we must establish what is wrong with the current system which focuses on financial
measures. Management currently makes sacrifices in the current year so things like net income
will be better reported at the cost of future financial performance. The balanced scorecard looks
at ways to measure the financial performance in the long-term. Considering research and
development costs, if you look at the first year you have a large expense and the last year large
revenue, but you have to look at it over its entire life to evaluate the performance. The balanced
scorecard first looks at the company’s mission statement and strategy then translates into four
measures by which the long-term financial performance of the organization can be assessed. The
four measures are broadly defined as organization learning & growth, internal business
processes, customer value, and financial results. The organization learning and growth comes
which have been performance measures for years. The key to the balanced scorecard idea is that
within an organization causal relationships exist such as how a change in human capital causes
changes in other areas. A balanced scorecard can tell you whether spending more time to train
employees will translate into increased profits. Through assessments of an organization one can
create causal relationships which are tied to the mission. Then this, so called model should be
tested to validate whether these relationships exist. The power of a balanced scorecard should
not be underestimated. Suppose a possible causal relationship model looks as such: increased
training, causing less defects, causing lower cycle times and ultimately increased financial
performance. Now, a strategy like increasing training can be measured with some certainty on
how it will affect the overall performance of the organization.
To address your concerns as to whether causal models can really be created and what other
management gurus think. Although, Kaplan stated some examples of effective implementations
of the balanced scorecard, the causal models will be different for every organization and may or
may not be able to be created in this organization. Through discussions you can determine what
the causal model may look like, but that model must be tested to estimate its accuracy. Many
management gurus have bought in on the idea of the balanced scorecard. It has been documented
that the French have used a similar technique for fifty years, their titled translates to English as
the "dashboard." Many articles other than those published by Kaplan and Norton were written
concerning the balanced scorecard, two in particular I would recommend. An article by Chow,
Haddad and Williamson titled, "Applying the Balanced Scorecard to Small Companies," and
another by Curtis and Ellis titled, "Balanced Scorecards for New Product Development. Both
Part Two:
(This part is answered as the responses I would have to the specific questions independent
of each other)
In response to the VP of Marketing:
This concept may very well be a fad, but SWAT analysis, ABC, Target Costing and many
other widely accepted management tools started out as management fads. Not until these
techniques are embraced worldwide and proven to be useless can they be determined to
be truly a fad. The economy today sets us in a highly competitive environment; new
ideas, and chances need to be taken in order to stay afloat. Whether a balanced scorecard
is useless and just a fad is a concern but has yet to be determined as such. As I mentioned
to Ms. Howard, a concept similar to the balanced scorecard has been used for nearly fifty
years in France. This adds some creditability to manager's perception that this tool can
work and is not just a fad. To address your second concern on the time it takes to validate
whether causal relationships exist and whether they will be obsolete. The purpose of a
balanced scorecard is to tie the mission of an organization to the financial performance
and so only if the mission of an organization is changed should the causal relationships or
model change. Considering a model in which highly educated employees equals better
customer retention and better financial performance. The mission of the organization
would be something like delivery of a quality service, and in order to maintain that
Your concern is that these relationships are just someone’s best guess, and you are right.
That is how you first determine causal relationships, but then you test these relationships
either with logic like reality checks or multiple evaluations, or you test it with statistics. I
assume many decisions you make are built off a hunch or your best guess, but to prove
that they will work you either have to roll the dice and take a chance or test the theory. In
addition you mentioned communication of strategy over a management tool. This is a
good question for it seems logical to see that it is a good method to communicate strategy,
but it is not as easy to see its manageability. By communicating strategy all personnel
will work in unity toward a common organizational goal, this in essence is the stepping
stone toward success. You no longer need to manage like you are used to, now
employees will evaluate their contribution in context of how the organization is doing
overall. Basically, you manage the employees by evaluating how well they are doing in
context to their contribution to the overall financial success of the organization.
Response to Human Resources Director:
You have to be happy if everyone buys into the program, one of its intentions is to have
all the managers working toward the mission of the organization and employing the same
strategies. I believe you are concerned about change and I agree that if you are going to
make the change to a new system it must be evaluated completely. As I have mentioned
before, the model must be tested and tested throughout all divisions, for all divisions need
Part Three:
The model is constructed as such:
Dimensions of Performance Measures of Performance
(The construction of this model is based solely on discussions with division managers and controllers)
The model begins with average grade level. Through discussions with various managers and controllers of the different divisions, an increase in the grade level would reduce the average number of defects per month, but would also increase the average hourly wage due to higher skills needing to be paid more. It is felt that a higher hourly wage will better retain employees and therefore reduce the voluntary turnover rate. If more employees are retained, then both average defects per month and cycle time per order will be reduced. The reduction of defects and cycle time will minimize the rework and overall
Avg. Grade Level Completed
Customer Value
Profitability
the model was been constructed this way. In the first line of Kaplan’s article “Why Does Business Need a Balanced Scorecard?” he states, “If you can’t measure it, you can’t manage it.”
The constructed on page 6 is developed based on logic derived from discussions with prominent individuals within the organization. To add some creditability to the model we will test it with statistics.
Part Four:
To test the model, each causal relationship was tested independently of each other. The relationship between average grade level and hourly wage was tested first. The testing was conducted by comparing the percentage change in grade level from division to division with the percentage change in dollars paid from division to division. For a more elaborate description of how the graphs were created, refer to page 10. The argument is that an increase in grade level should cause an increase in hourly wage. Here is the graphical representation.
Grade Level vs. Hourly Wage
-150%
-100%
-50%
0%
50%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
are causally linked, but not in all. There is not a valid causal relationship.
à Next the average grade level completed was compared to average defects per month. Here is the graphical representation.
Grade Level Vs. Average Defects
0%
10%
20%
30%
40%
As you can see they are not completely causally linked. Not until division seven do we see the lines running parallel with each other. After division ten you that they are a radical inverse of each other. Based on the graph we have to conclude that within some divisions these measures
This one is a slam-dunk. Within all divisions you see that when average grade level increases the average number of defects per month decreases and vice versa. A causal relationship exists between grade
à Argument is that an increase in hourly wage will reduce the voluntary turnover rate. Hourly Wage Vs. Voluntary Turnover
-60%
-40%
60%
80%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
à When voluntary turnover rate decreases, the average cycle time per order will decrease and the average defects will also decrease. Each relationship is graphed separately.
Voluntary Turnover Vs. Avg. Defects
-60%
-40%
-20%
0%
20%
40%
60%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
In many divisions the turnover rate is related to the average amount of defects, but you can also see many divisions like 2 and 15 where the average defects has an inverse relationship with the turnover rate. It appears conclusive that in most cases the turnover rate is related to the average amount of defects and is validated as a causal relationship. With the exception of a couple of divisions, 4, 13 & 14, the turnover rate is causally related to the cycle time per order. The lines are to run parallel with each other and in most cases they do.
à Average defects and cycle time in relation to the percentage of on-time deliveries.
As the average number of defects decrease, the percentage of on-time deliveries is to also increase. This effect is split about
Defects Vs. % of On-Time Deliveries
30%
40%
-60%
-40%
-20%
0%
20%
40%
60%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
You see that a causal relationship exists between hourly wage and voluntary turnover rate. They are to be inversely related. Compare division 7’s data, approximately 40% decrease in hourly wage causes an approximate10% increase in the turnover rate.
On the other hand, cycle time appears to be strongly correlated with on-time deliveries. When the cycle time as a percentage decreases, the percentage of on-time deliveries increases nearly throughout all divisions.
The argument has been made that customer value is related to the customer receiving the goods on time. The graph below depicts the relationship of on-time deliveries and customer satisfaction score.
O n - T i m e D e l i v e r i e s V s . C u s t o m e r S a t i s f a c t i o n
- 3 0 %
- 2 0 %
- 1 0 %
1 0 %
2 0 %
3 0 %
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7
For a causal relationship to exist the lines should run parallel and for the most part they do. There is a definite relationship between on-time deliveries and the customer satisfaction score. Now let’s see if the customer satisfaction score translates in the financial measure of return on assets. It is argued that if the customers are happy then they will return and therefore create a higher return on assets.
As you see in most cases, the higher the customer satisfaction score, the higher return on assets. Return on assets was computed from the table of data as throughput minus operating expenses divided by assets employed. A causal relationship exists between customer satisfaction and return on assets.
C y c le Tim e V s . % o f On-T im e D e l iver ies
-40%
-20%
0%
-30%
-20%
-10%
0%
10%
20%
30%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
RELATIONSHIP
• GRADE LEVEL VS. AVERAGE HOURLY WAGE • GRADE LEVEL VS. AVERAGE DEFECTS • HOURLY WAGE VS. VOLUNTARY TURNOVER
RATE • VOLUTARY TURNOVER RATE VS. AVERAGE
DEFECTS • VOLUNTARY TURNOVER RATE VS. AVERAGE
CYCLE TIME • AVERAGE DEFECTS VS. ON. TIME DELIVERIES • CYCLE TIME VS. ON-TIME DELIVERIES • ON-TIME DELIVERIES VS. CUSTOMER
SATISFACTION • CUSTOMER SATISFACTION VS. RETURN ON
ASSETS
How the Graphs were Created:
By using the spreadsheet of data, I took the change from one division to the next and compared that percentage to that of another measure. To demonstrate, consider the first relationship identified, Grade Level Vs. Hourly Wage.
D ivisions
D ivision to
the next 1 10.71 -15% 11.11$ 11% 2 11.93 7% 9.49$ 0% 3 11.95 0% 10.11$ -15% 4 10.15 -2% 10.13$ 14% 5 11.62 -3% 9.89$ -11% 6 10.31 -21% 9.59$ 8% 7 11.14 10% 7.59$ 7% 8 11.97 -4% 8.35$ -12% 9 10.47 8% 8.02$ 5%
10 11.02 0% 8.65$ -3% 11 10.65 -26% 8.66$ 3% 12 10.96 58% 6.42$ -8% 13 10.14 -14% 10.13$ 6% 14 10.73 -7% 8.71$ 0% 15 10.75 -29% 8.09$ -4% 16 10.36 85% 5.72$ 10% 17 11.34 -3% 10.59$ -6%
The graph is created by taking the percent change from one division to the next for grade level and comparing that with the percent change from one division to the next for average hourly wage. The graph is as follows:
Grade Level vs. Hourly Wage
-150%
-100%
-50%
0%
50%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Division 16 provides a good example of how the comparison takes place. You see the percent change for grade level jump 85% and
The advantages are that you can use the data to compute statistical correlation between the different measures in the model. It helps add confidence to your logical assumptions about causal relationships and how to measure your performance based on a balanced scorecard model. The biggest disadvantage is the validity of the numbers. Consider the customer satisfaction score that was computed by assumptions made from managers of what customers really value. The measure was computed with measurable qualities like average defects per month, but the customer could value things like brand name, appearance and other immeasurables. The balanced scorecard needs to be tested and statistical testing appears to be the most conclusive, the only thing is that the measures used to test the model should be tested before hand so that certain relationships are not excluded for inaccurate numbers.
Additional Data:
As aforementioned, using population data may create a more balanced scorecard among all the different divisions. To evaluate the performance of one division over another adjustments need to be made. If one division resides in a highly competitive market and the other does not and adjustment should be made. The most useful data may not be measurable, such as the value of quality products and quality service. The controller of Division 11 hypothesized that the quality of the processes is derived from the employee turnover rate. It is felt that this may be one component of many which equate to process quality and that not all are measurable. A measure much like customer satisfaction score but for internal processes would be useful, something like total quality management.
Part Five:
Throughout the management literature it is stated that most balanced scorecard models are not implemented until a couple of years of testing has taken place. This would be a recommendation. I would take the data computed in part four and see where the variances are that make the relationship not causal, then talk to the particular division managers about their perceptions. You want to take the implementation slowly, for as was mentioned by the director of human resources everyone will go along, so everyone will either sink or swim. A pilot program on one division would not be effective, for the balanced scorecard is to represent the organization as a whole, plus it is long-term in nature.
The opportunity to better understand your business processes and how all divisions match
Resources Used:
"Why Does Business Need a Balanced Scorecard?" by Kaplan and Norton
"Why Does Business Need a Balanced Scorecard? (Part Two)" by Kaplan and Norton
"Applying the Balanced Scorecard to Small Companies," by Chow, Haddad, and Williamson
"Balanced Scorecards for New Product Development," by Curtis and Ellis
Lectures given by Dr. Frank Selto
