HI friends,I want to implement cause-effect relationship between two objectives( goals). Both goals belongs to different perspectives. How can i implement. Well-developed causal Balanced Scorecard, Cause and Effect, models are valuable Objective: To find out whether cause and effect relationship in BSC at the. asked me whether there was any alternative to the balanced scorecard (BSC) as a Kaplan and Norton's strategy maps lay out the relationships among I'm confident that more companies will pursue “cause-and-effect.
This just leads to a complex categorisation on measures that are unrelated. To understand why this does not work, watch our Strategy Mapping video. They lose the causal relationship across perspectives, failing to realise that the balance is a consequence of a well-defined cause and effect relationship.
As a result, the measures do not describe how strategy is driven and change occurs. This is another way to achieve the problems created in 1 or 2. Unfortunately, it creates a complex categorisation and often destroys any story of the strategy and the cause and effect model. Here are some articles explaining specific aspects of each perspective and some typical problems that are created when the perspectives are ignored or renamed.
It acts as an anchor for everything else.
Here are two articles that discuss that: Using shareholder value or return at the top of a strategy map 3. In commercial organisations it contains the financial outcomes and the results of what the organisation costs and the revenues that the customers provide. In not for profit organisations, you also look at donations and sources of income, as opposed to customer sources revenue. I often get some odd questions about the financial perspective.
Here are the most common ones. It represents the impact and outcomes that the organisation has on the environment. We have been doing it for our clients for years.
Customer loyalty was perceived by earlier scholars as the most important driver of long-term financial performance as the high level of customer satisfaction would increase customer loyalty Reichheld and Sasser, In support of this, it was found that the relationships between customer satisfaction and loyalty is non-linear in nature; only highly satisfied customers remained loyal to the service provider Haskett et al.
Furthermore, it was empirically found that customer satisfaction was not a driver for revenue in corporate business services but significantly positively correlated for small business services Silvestro and Low, There was no sound theory for a model in which relationships were derived from logic.
Empirical evidence can provide some guidance in the effort to build such models of which the validation of those relationships can be conducted statistically. Therefore, earlier researchers proposed that a causality test be conducted on the measures in BSC.
Issues of causation between measures in BSC were seldom addressed in research. It was obtained from earlier researches that the relationships between employee engagement or employee satisfaction to revenue and vice versa showed only correlation relating to both variables and not due to causation Clark, Furthermore, this finding was supported empirically that the causation should strongly run both ways.
The linkages between employee engagement and financial report revenue needed to Yusof et al, Australian Journal of Basic and Applied Sciences, 8 2 FebruaryPages: The usefulness in predictions of Performance Management Model PMM depends on how reliable the cause and effect relationships. Thus, the usefulness of BSC highly depended on how reliable the cause and effect relationships in the strategy maps.
The existence of causal model or causal linkages in strategy maps was empirically proven by earlier researchers to be essential to the organization Ittner and Larcker, ; Speckbacher et al. In support, it was found empirically that organisations that adopt BSC with causal model and utilize it performed better than the one that did not have nor use it Marr and Schiuma, ; Othman, ; Lucianetti, Even though a causal model is one of the main characteristics of the BSC approach, inexplicably, a study revealed that only half of the companies that used BSC were able to develop causal models Speckbacher et al.
The previous findings seem to be in line with the concerns given by earlier researchers as stated below. Studies revealed that companies that adopt BSC without having strategy map models reasoned that they faced problems in describing the cause and effect relationships Malmi, This was due to inadequate empirical evidence on how the construction of the cause and effect relationships were done in the strategy map of BSC Ittner and Larcker, From the identified evidences with respect to the cause and effect relationships, it was really important to identify the existence of causal model in strategy map, as suggested by earlier researches Grant, ; Ittner and Larcker, ; Norreklit, ; Harter et al.
Hence, the cause and effect relationships between internal processes and the desired outcomes has to be identified from the beginning Othman, Due to the need of causality study in order to explore the relationships between measures in PMM, two previous researchers investigated whether the assumption of linkages in PMM was derived by logical, finality or cause and effect relations, using statistical causality tests Malina and Selto, The statistical causality test used in their research was econometric analysis called Granger causality tests Granger, The study revealed no statistical evidence of causal relations but there was statistical evidence to support that linkages in PMM were based on logical and finality.
However, as their study was limited to only 17 quarters data point, further research was proposed to cater for a larger data which may reveal that the cause and effect relationship among performance measures could be statistically significant.
Due to that, another study with the same objective and methodology was conducted using the Granger causality tests on the historical data of PMM with 31 quarterly data points from to Malina et al. However the findings were still as previously, i. Recent studies on validating the cause and effect relationships in the BSC were conducted by Bento et al. From this study, it was found that the learning and growth, internal and customer perspectives gave a significant direct impact on the financial perspective.
However, even though this study claimed to concentrate on testing the cause and effect relationships in BSC, in some way, it was more on studying the relationships and not the causality between performance measures. Therefore, it was suggested that other features of the BSC also be tested using longitudinal test to identify the time lag needed for leading indicators to translate into lagging indicators.
The suggested method is supported by studies previously conducted by Malina and Selto and Malina et al. Taking this into consideration, therefore, the data used in this study was longitudinal data or time series data. Thus, the Granger causality test was chosen for identifying the evidence of causal relations among measures in BSC. Granger causality test from econometrics analysis is widely used by previous researchers to establish the causality between economic factors Foresti, ; Omachonu et al.
In Malaysia, the Granger causality test was employed to study the relationship between health spending, income and health price. The study indicated that the unidirectional causality existed from health spending and health price while bidirectional causality is between income and health price Tang, The study whether the relationships among performance measures are based on causality or not is not exclusive to PMS, including the BSC, as causal relationships in a strategy map are the key features that differentiate the BSC from other PMSs.
In a strategy map, unidirectional relationship is clearly known for its bottom-up approach. However, the cause and effect relation performance measures in BSC was found to be empirically refutable by earlier researchers Ittner and Larcker, ; Norreklit, Briefly, in this study, the Granger causality test was conducted on the 45 time series secondary data points extracted from BPR report from April to December with 10 propositions tested.
Prior to conducting Granger causality test, the unit root tests were conducted individually onto performance measures to check the nature of the data in terms of the stationary data level.
Originally, the SPC is a theory and business model developed by researchers from Harvard University in the mid-nineties Haskett et al.
It provides a framework to link internal portion employee and external portion customer assessment to the profitability of the firms.
It provides an integrative framework for understanding how the investments made by the company into service operations are related to employee satisfaction, customer perceptions and behaviours which in turn drives profit. The framework emphasised that employees who are satisfied and motivated would bring out satisfied customers with a tendency to purchase more, thus in turn increases the revenue and profit of the organisation.
A theoretical framework consisting of ten 10 propositions was developed and tested to provide evidence for the cause and effect relationships among measures in BSC.
Cause-effect relationship in balanced scorecard
Without the theory, the econometrics analysis cannot be conducted to establish the statistical evidence from the cause and effect relationships. Most discussion on the relationships in the SPC model focuses on the correlation analysis instead of causation.
There were plenty of arguments on the existence of causality in the said model and modest study on the causation conducted previously. In order to find out whether cause and effect relationships in BSC at the research site exists or not, a statistical analysis test of causality was conducted on the archival data using statistical causality analysis. Based on the research framework, as illustrated in Figure 1 below, the propositions were developed mostly based on the correlation relationships that were found from previous studies but with very little to causation.
Admittedly, employee engagement is an important variable in order to ensure the survival of the organisation in terms of the profitability. Organisations with disengaged employees seem to have lower productivity, inefficient and experience high employee turnover. The relationship between employee engagements with other variables is thoroughly discussed and ascertained empirically in terms of correlation and not much to causation.
The relationships between employee engagement to customer satisfaction, productivity, profit, employee retention and employee safety were studied using Meta analysis approach Harter et al. The study reveals that the relationship of employee engagement to productivity and profit are positively correlated with low magnitude whilst relation of employee engagement to customer satisfaction, employee retention and employee safety are positively correlated with high magnitude. Findings from studies on service management showed that, as employees become engaged with their work, it increases their commitment, thus improve productivity.
As productivity increases, it leads to the improvement in service quality which in turns drive customer satisfaction Haskett et al. The same study on this relationship suggests that employee engagement is directly related to financial performance Pfau and Kay, However, issues of causation were not often addressed in research.
Clark found the relationship between employee engagement and satisfaction to revenue and vice versa showed the correlation relates only to both variables and not due to causation.
This was supported by Grant that the causation should strongly run both ways, the linkages between employee engagement to financial report revenuein order to test the Yusof et al, Australian Journal of Basic and Applied Sciences, 8 2 FebruaryPages: Another study on the same issue showed that employee satisfaction affects the financial results and a company with higher financial metrics affects employee satisfaction result as well.
However, the model only showed the correlation and not causation between variables. Integrity Healthcare Services reported that customer satisfaction has a direct correlation to customer growth through word of mouth among customers. It is supported that better customer satisfaction leads to the positive verbal communication, thus in turn leads to customer growth Luo and Homburg, This directly supports the study that high customer satisfaction leads to growth in customer-base.
Deep insight into customer behaviour is very important and the company should study where and how customers perceive the product or services value given by the service provider. Therefore, the corporate programmes should be designed carefully by the company to suit the customers to ensure that these programmes are able to attract new customers while retaining existing customers, ultimately leading to the increase in revenue Lev et al. This directly supports the notion that customer growth leads to better financial performance.
However, the reverse is not true, where increase revenue does not necessarily bring in new customers Icebridge-Strategic-Sales-Consulting, A few studies were conducted to identify the relationship between customer satisfaction and financial performance which drew the conclusion that customer satisfaction theoretically, is a driving measure of financial performance, revenue growth Ittner and Larcker, ; Luo and Homburg, ; Yoo and Park, ; Lev et al.
In addition to that, satisfied customers do tend to recommend services or product to others, which in turn increase the financial gains. However, service quality and customer satisfaction do not always lead to better financial performance Ittner et al. There is no relationship observed between customer satisfaction and revenue in corporate business service, but significant positive correlation in small business service sector Silvestro and Low, Their study also showed that there is non-linearity relationship between customer satisfaction and loyalty, i.
Even though the study carried out by Ittner and Larcker, demonstrate that improving service quality and customer satisfaction is associated strongly with financial performance as revenue grow resulting from improved customer satisfaction however, the relationship does not represent a causal relationships Ittner and Larcker, ; Ittner et al.
It has been suggested by previous researchers that the causal model should be developed to explore the generalisation of how employee engagement affect the short terms outcomes, and how customer satisfaction result in financial performance Harter et al.
This directly supports the usefulness of causality linkages identification from customer satisfaction to revenue and vice versa. For testing the causality linkages among measures, the data or information related to this study was collected from April to December and monthly time series for employee engagement, customer service charter CSC or productivity, customer satisfaction, customer growth and revenue were extracted from BPR report at the research site.
The Augmented Dickey-Fuller ADF and Philips-Perron PP methods were employed to ascertain existence of the stationary in the series followed by the Granger causality test to identify the cause and effect relationships among the variables.
For this study, E-Views 7. The cause and effect is adapted from a conceptual framework in the service management, the SPC Haskett et al. The methods used in this study are briefly explained in the subsequent sections together with their findings.
A unit root test is a statistical method to test whether a time series variable contains unit root and thus making the series is non-stationary if it does Gujarati and Porter, Otherwise, the series will be categorised as stationary. If Ho was rejected, that means the series were stationary, otherwise, it is non-stationary instead.
Empirical evidence shows that most of the macroeconomics time series are non-stationary at level and most of them are stationary after first differencing Nelson and Plosser, ; Chimobi and Uche, ; Tang, In brief, Unit Root tests are needed to determine which level of variables are stationary or the order of integration of the variables, either at first order, second or more.
It may provide spurious regression results if the variables are non-stationary Granger and Newbold, ; Philips, To avoid this, the order of integration for each series of variables needs to be determined.
Understanding & using balanced scorecard perspectives, and cause and effect
Below is the equation of the unit root test: Series contains a unit root Non-StationaryHa: Series does not contains a unit root StationaryTable 1: Whilst only customer growth variable significantly rejected the null hypothesis of a unit root at second difference. Therefore, the Granger causality test was conducted up to the lag of 2. The Granger causality test, founded by Professor Clive Granger, is a statistical test that is based on prediction and is widely used in economics since s Granger, Granger causality test is needed to identify the direction of causality or to test the causal connection between two or more variables.
In other words, it is widely used to determine whether the current and lagged value of one variable affects another or in the simplest way, to determine if one time series is useful in forecasting another. The equation of Granger causality test for two variables involve are as below: The hypotheses for the Granger causality test for equations above are: Similarly, the rejection of H0 for equation 6 indicates that Yt Granger cause to Xt.
If the rejection of H0 for both equation 4 and 6then the feedback or bilateral or bidirectional causality between X and Y exist. Based on the previous study, the number of lags up to four quarters were considered conservative in econometrics analysis since most of the data was in quarterly basis Malina and Selto, ; Malina et al.
It is unlikely to take longer than one year for a BSC measure to influence any other measures as the performance measurement is always measured on yearly basis.
In addition, the identification of stationary data of variables is part of the criteria to identify the number of lag when conducting Granger causality test. In this study, the Granger causality test was conducted up to lags two since the highest level for variables to become stationary was at second differences. Results for the Granger causality test based on the propositions were illustrated in Table 2 below.
The Results of Granger Causality Test. R does not Granger cause EE 6. EE does not Granger cause R 0. EE does not Granger cause CS 1. CS does not Granger cause CG 0. CS does not Granger cause R 2. R does not Granger cause CS 3.
CG does not Granger cause R 0. It was found that only four propositions were supported significantly by the archival data at the research site; P1, P2, P8 and P9. Obviously, this was consistent with the suggestion by Grant that the causation between employee satisfaction and revenue should strongly run both ways. However, there was new unidirectional causality discovered in this statistical causality test which was not highlighted in the propositions; employee engagement was a Granger cause to customer growth.
It is essential to establish the causality among BSC performance measures as it is well known to follow the unidirectional cause and effect relationships.
Cause and effect relations are important features of BSC depicted in its financial prediction ability and an organizational communication and learning tool. It also acts as a motivation and incentives channel to be given to employees.
Furthermore, the causal model is important to PMS for improving business performance as it is empirically proven that a company with causality model performs better than a company without one.
This implied the existence of causal linkages between customer growth and revenue. The finding is in line with previous studies on correlation indicating that there is a positive correlation with low magnitude between those two variables Harter et al.