Foresight: The International Journal of Applied Forecasting, 2017
The integration of demand forecasting and inventory control is an area that deserves increased at... more The integration of demand forecasting and inventory control is an area that deserves increased attention from practitioners as well as more research work from academics. In inventory planning, there is an explicit linkage between the variance of the forecast errors over the replenishment lead time and the calculation of safety stocks. If the calculation of the forecast error variance is flawed, then the calculation of the safety stocks will be flawed too. The implications can be dramatic: if stocks are too high, there is a financial penalty. If they are too low, service levels will be compromised. In this article, Steve Morlidge and Aris Syntetos describe common but critical mistakes in the calculation of the lead-time forecast error variance and discuss the implications for setting safety stocks. They explain what the mistakes are and where they're coming from, and they provide estimates of their consequences. The authors argue that resolving such problems goes beyond the actual technicalities to include closer communication between demand forecasters, inventory controllers, and suppliers of the software in use. Copyright International Institute of Forecasters, 2017
Foresight: The International Journal of Applied Forecasting, 2015
In this eye-opening article, Steve Morlidge shows that when our demand histories are intermittent... more In this eye-opening article, Steve Morlidge shows that when our demand histories are intermittent, we should rethink the use of our most common accuracy metrics for selecting a best forecast method. The problem is acute because many software applications use these metrics for performance evaluation and method selection; in doing so, they potentially provide us with poor feedback and inferior models, resulting in harmful consequences for inventory management. Copyright International Institute of Forecasters, 2015
Systemic Practice and Action Research, May 23, 2009
Variety engineering was the term coined by Stafford Beer to describe the management of the system... more Variety engineering was the term coined by Stafford Beer to describe the management of the system of constraints placed on an organisation. Successful variety engineering involves working with the demands of Ashby's Law of Requisite Variety; matching regulatory variety with that of the situation being regulated. Money is an important mechanism for variety engineering: the allocation of financial resources helps amplify variety; its withdrawal attenuates. This paper argues that budgeting, the conventional approach to the management of financial resources, demonstrably does not have requisite variety. This fact could be manifest in a range of undesirable patterns of behaviour. The practice of budgeting has not, however, been seriously challenged by systems theorists nor alternative mechanisms proposed. This paper sets to remedy this by describing how the cybernetic regulation of the flow of financial resources can be incorporated into the framework provided by Beer's Viable Systems Model. Keywords Cybernetics Á Variety engineering Á Budgeting Á VSM Á Regulation Background Most of us would concur with Lennon and McCartney that 'money can't buy me love'. It does, however, buy you choice. In cybernetic language, money helps engineering variety; the number of states a system is capable of adopting. The absence of money attenuates variety (and so constrains choice), having money amplifies variety (creates choice). The term 'variety' was coined by Ashby (1957), and the concept underpinned his 'Law of Requisite Variety, which stated that, for a system to be effectively regulated, the variety of a regulator must be equal to or greater than the variety of environmental perturbations. Since variety is constrained by money, we might expect that the way in which an organisation manages the flow of money-how available resources are deployed-would be
Foresight: The International Journal of Applied Forecasting, 2016
Morlidge adds a sixth commentary on the previous article by Sujit Singh, Academia versus Business... more Morlidge adds a sixth commentary on the previous article by Sujit Singh, Academia versus Business. Copyright International Institute of Forecasters, 2016
Foresight: The International Journal of Applied Forecasting, 2016
Over the last two years I have written a number of pieces for Foresight with proposals about how ... more Over the last two years I have written a number of pieces for Foresight with proposals about how to improve the measurement of forecast error. In this article, I show how these and related ideas can be used to manage the performance of the forecast process. Such analyses can be embedded in a control system to provide speedy, actionable feedback to forecasters and to their internal customers. They could also form the basis of an approach for consultants or internal experts to audit the quality of the forecasting process. This article furnishes examples of the practical application of this approach in the demand forecasting process of a typical consumer-goods business, selling product from stock. Copyright International Institute of Forecasters, 2016
Foresight: The International Journal of Applied Forecasting, 2016
Morlidge first describes the contents of the recent book by Tetlock and Gardner, then suggests se... more Morlidge first describes the contents of the recent book by Tetlock and Gardner, then suggests several takeaways for business forecasters. Copyright International Institute of Forecasters, 2016
Foresight: The International Journal of Applied Forecasting, 2015
In his last Foresight article, ?Measuring the Quality of Intermittent Demand Forecasts? in the Sp... more In his last Foresight article, ?Measuring the Quality of Intermittent Demand Forecasts? in the Spring 2015 issue, Steve showed that certain common error metrics?the MAE and MAPE?can readily lead to the selection of inappropriate forecasting methods when demands are intermittent. Intermittent demands are a special case of asymmetric (skewed) distributions, for which Steve proposed an alternative metric, the bias-adjusted mean absolute error (BAMAE). In this article Steve makes the argument that the BAMAE can serve as the most valid and appropriate error metric for any distribution of demands, symmetric or asymmetric. It is well worth giving this metric some thought. Copyright International Institute of Forecasters, 2015
Recent management control research considers how performance management systems (PMS), conceptual... more Recent management control research considers how performance management systems (PMS), conceptualized as packages of controls with competing objectives, operate in an integrated fashion. Larger organisations must also consider how to achieve integration across organizational levels. It is not clear from traditional accounting-based frameworks how this coherence is achieved. The viable system model (VSM), a theoretical framework drawn from the field of organizational cybernetics, explains how components of control systems are integrated. Nonetheless, management control researchers fail to recognize the potential of the model. Their reluctance to use the VSM may reflect past criticisms of the model, including it is difficult to understand, cannot be applied in practice and provides no additional insights. Alternately, they may simply be unsure how the model accommodates accounting controls. This paper finds the criticisms of the VSM to be unjustified and argues for greater use of the model in accounting control research. The intelligibility of the VSM is advanced by highlighting similarities between the model and accounting control frameworks, and developing an accounting-oriented VSM that clarifies how accounting controls are handled in the model. The practicability of the model is confirmed by using the VSM to depict the performance management system of a tertiary institution. The insights developed from the competed model extend those available through traditional accounting-control frameworks.
Foresight: The International Journal of Applied Forecasting, 2014
Building on his two previous publications in Foresight on the measurement of forecastability, Ste... more Building on his two previous publications in Foresight on the measurement of forecastability, Steve shows how forecast quality can be objectively measured using the relative absolute error (RAE) metric and how this metric can be used to reveal the potential for improvements in forecast accuracy. He presents compelling evidence that many companies fail to achieve levels of relative error that are better than a simple ?same as last period? na‹ve forecast, and that around 50% of individual forecasts fail to meet this benchmark. He makes it clear that, while there is a great need for improvement in forecast quality, there is the potential for forecasters to accomplish just such improvement. Copyright International Institute of Forecasters, 2014
Foresight: The International Journal of Applied Forecasting, 2011
In our previous issue (Summer 2011), Steve Morlidge introduced a set of guiding principles for th... more In our previous issue (Summer 2011), Steve Morlidge introduced a set of guiding principles for the organizational forecasting process. To make progress, he argues in this second installment, “forecasters need to move beyond the exchange of experience and the simplistic peddling of best practice and seek to lay out a set of principles that collectively define forecasting craftsmanship based on an amalgam of technical knowledge, research, and hard-won experience.” Copyright International Institute of Forecasters, 2011
Foresight: The International Journal of Applied Forecasting, 2014
How can we identify our best opportunities to improve forecast accuracy? Steve Morlidge concludes... more How can we identify our best opportunities to improve forecast accuracy? Steve Morlidge concludes his four-part Foresight series on forecast quality by offering an approach based on (a) product volumes and variability, and (b) a forecastability metric that assesses forecast accuracy in relation to the accuracy of a na•ve (i.e., no change) forecast. The metric helps supply-chain forecasters set meaningful targets for improvement, quantifies the scope for improvement, and tracks progress toward final goals. Copyright International Institute of Forecasters, 2014
Foresight: The International Journal of Applied Forecasting, 2010
Based upon his forthcoming book Future Ready: How to Master the Art of Business Forecasting, Stev... more Based upon his forthcoming book Future Ready: How to Master the Art of Business Forecasting, Steve Morlidge – a finance professional by background – argues here that forecasters need to adopt a broader perspective on the role of strategic forecasting and a longer-range view on forecasts themselves. Steve offers a series of principles that should enable the business to navigate better through troubled waters. Copyright International Institute of Forecasters, 2010
Foresight: The International Journal of Applied Forecasting, 2017
The integration of demand forecasting and inventory control is an area that deserves increased at... more The integration of demand forecasting and inventory control is an area that deserves increased attention from practitioners as well as more research work from academics. In inventory planning, there is an explicit linkage between the variance of the forecast errors over the replenishment lead time and the calculation of safety stocks. If the calculation of the forecast error variance is flawed, then the calculation of the safety stocks will be flawed too. The implications can be dramatic: if stocks are too high, there is a financial penalty. If they are too low, service levels will be compromised. In this article, Steve Morlidge and Aris Syntetos describe common but critical mistakes in the calculation of the lead-time forecast error variance and discuss the implications for setting safety stocks. They explain what the mistakes are and where they're coming from, and they provide estimates of their consequences. The authors argue that resolving such problems goes beyond the actual technicalities to include closer communication between demand forecasters, inventory controllers, and suppliers of the software in use. Copyright International Institute of Forecasters, 2017
Foresight: The International Journal of Applied Forecasting, 2015
In this eye-opening article, Steve Morlidge shows that when our demand histories are intermittent... more In this eye-opening article, Steve Morlidge shows that when our demand histories are intermittent, we should rethink the use of our most common accuracy metrics for selecting a best forecast method. The problem is acute because many software applications use these metrics for performance evaluation and method selection; in doing so, they potentially provide us with poor feedback and inferior models, resulting in harmful consequences for inventory management. Copyright International Institute of Forecasters, 2015
Systemic Practice and Action Research, May 23, 2009
Variety engineering was the term coined by Stafford Beer to describe the management of the system... more Variety engineering was the term coined by Stafford Beer to describe the management of the system of constraints placed on an organisation. Successful variety engineering involves working with the demands of Ashby's Law of Requisite Variety; matching regulatory variety with that of the situation being regulated. Money is an important mechanism for variety engineering: the allocation of financial resources helps amplify variety; its withdrawal attenuates. This paper argues that budgeting, the conventional approach to the management of financial resources, demonstrably does not have requisite variety. This fact could be manifest in a range of undesirable patterns of behaviour. The practice of budgeting has not, however, been seriously challenged by systems theorists nor alternative mechanisms proposed. This paper sets to remedy this by describing how the cybernetic regulation of the flow of financial resources can be incorporated into the framework provided by Beer's Viable Systems Model. Keywords Cybernetics Á Variety engineering Á Budgeting Á VSM Á Regulation Background Most of us would concur with Lennon and McCartney that 'money can't buy me love'. It does, however, buy you choice. In cybernetic language, money helps engineering variety; the number of states a system is capable of adopting. The absence of money attenuates variety (and so constrains choice), having money amplifies variety (creates choice). The term 'variety' was coined by Ashby (1957), and the concept underpinned his 'Law of Requisite Variety, which stated that, for a system to be effectively regulated, the variety of a regulator must be equal to or greater than the variety of environmental perturbations. Since variety is constrained by money, we might expect that the way in which an organisation manages the flow of money-how available resources are deployed-would be
Foresight: The International Journal of Applied Forecasting, 2016
Morlidge adds a sixth commentary on the previous article by Sujit Singh, Academia versus Business... more Morlidge adds a sixth commentary on the previous article by Sujit Singh, Academia versus Business. Copyright International Institute of Forecasters, 2016
Foresight: The International Journal of Applied Forecasting, 2016
Over the last two years I have written a number of pieces for Foresight with proposals about how ... more Over the last two years I have written a number of pieces for Foresight with proposals about how to improve the measurement of forecast error. In this article, I show how these and related ideas can be used to manage the performance of the forecast process. Such analyses can be embedded in a control system to provide speedy, actionable feedback to forecasters and to their internal customers. They could also form the basis of an approach for consultants or internal experts to audit the quality of the forecasting process. This article furnishes examples of the practical application of this approach in the demand forecasting process of a typical consumer-goods business, selling product from stock. Copyright International Institute of Forecasters, 2016
Foresight: The International Journal of Applied Forecasting, 2016
Morlidge first describes the contents of the recent book by Tetlock and Gardner, then suggests se... more Morlidge first describes the contents of the recent book by Tetlock and Gardner, then suggests several takeaways for business forecasters. Copyright International Institute of Forecasters, 2016
Foresight: The International Journal of Applied Forecasting, 2015
In his last Foresight article, ?Measuring the Quality of Intermittent Demand Forecasts? in the Sp... more In his last Foresight article, ?Measuring the Quality of Intermittent Demand Forecasts? in the Spring 2015 issue, Steve showed that certain common error metrics?the MAE and MAPE?can readily lead to the selection of inappropriate forecasting methods when demands are intermittent. Intermittent demands are a special case of asymmetric (skewed) distributions, for which Steve proposed an alternative metric, the bias-adjusted mean absolute error (BAMAE). In this article Steve makes the argument that the BAMAE can serve as the most valid and appropriate error metric for any distribution of demands, symmetric or asymmetric. It is well worth giving this metric some thought. Copyright International Institute of Forecasters, 2015
Recent management control research considers how performance management systems (PMS), conceptual... more Recent management control research considers how performance management systems (PMS), conceptualized as packages of controls with competing objectives, operate in an integrated fashion. Larger organisations must also consider how to achieve integration across organizational levels. It is not clear from traditional accounting-based frameworks how this coherence is achieved. The viable system model (VSM), a theoretical framework drawn from the field of organizational cybernetics, explains how components of control systems are integrated. Nonetheless, management control researchers fail to recognize the potential of the model. Their reluctance to use the VSM may reflect past criticisms of the model, including it is difficult to understand, cannot be applied in practice and provides no additional insights. Alternately, they may simply be unsure how the model accommodates accounting controls. This paper finds the criticisms of the VSM to be unjustified and argues for greater use of the model in accounting control research. The intelligibility of the VSM is advanced by highlighting similarities between the model and accounting control frameworks, and developing an accounting-oriented VSM that clarifies how accounting controls are handled in the model. The practicability of the model is confirmed by using the VSM to depict the performance management system of a tertiary institution. The insights developed from the competed model extend those available through traditional accounting-control frameworks.
Foresight: The International Journal of Applied Forecasting, 2014
Building on his two previous publications in Foresight on the measurement of forecastability, Ste... more Building on his two previous publications in Foresight on the measurement of forecastability, Steve shows how forecast quality can be objectively measured using the relative absolute error (RAE) metric and how this metric can be used to reveal the potential for improvements in forecast accuracy. He presents compelling evidence that many companies fail to achieve levels of relative error that are better than a simple ?same as last period? na‹ve forecast, and that around 50% of individual forecasts fail to meet this benchmark. He makes it clear that, while there is a great need for improvement in forecast quality, there is the potential for forecasters to accomplish just such improvement. Copyright International Institute of Forecasters, 2014
Foresight: The International Journal of Applied Forecasting, 2011
In our previous issue (Summer 2011), Steve Morlidge introduced a set of guiding principles for th... more In our previous issue (Summer 2011), Steve Morlidge introduced a set of guiding principles for the organizational forecasting process. To make progress, he argues in this second installment, “forecasters need to move beyond the exchange of experience and the simplistic peddling of best practice and seek to lay out a set of principles that collectively define forecasting craftsmanship based on an amalgam of technical knowledge, research, and hard-won experience.” Copyright International Institute of Forecasters, 2011
Foresight: The International Journal of Applied Forecasting, 2014
How can we identify our best opportunities to improve forecast accuracy? Steve Morlidge concludes... more How can we identify our best opportunities to improve forecast accuracy? Steve Morlidge concludes his four-part Foresight series on forecast quality by offering an approach based on (a) product volumes and variability, and (b) a forecastability metric that assesses forecast accuracy in relation to the accuracy of a na•ve (i.e., no change) forecast. The metric helps supply-chain forecasters set meaningful targets for improvement, quantifies the scope for improvement, and tracks progress toward final goals. Copyright International Institute of Forecasters, 2014
Foresight: The International Journal of Applied Forecasting, 2010
Based upon his forthcoming book Future Ready: How to Master the Art of Business Forecasting, Stev... more Based upon his forthcoming book Future Ready: How to Master the Art of Business Forecasting, Steve Morlidge – a finance professional by background – argues here that forecasters need to adopt a broader perspective on the role of strategic forecasting and a longer-range view on forecasts themselves. Steve offers a series of principles that should enable the business to navigate better through troubled waters. Copyright International Institute of Forecasters, 2010
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