Information use in supply chain forecasting

Demand forecasting to support supply chain planning is a critical activity, recognized as pivotal in manufacturing and retailing operations where information is shared across functional areas to produce final detailed forecasts. The approach generally encountered is that a baseline statistical forecast is examined in the light of shared information from sales, marketing and logistics and the statistical forecast may then be modified to take these various pieces of information into account. This experimental study explores forecasters’ use of available information when they are faced with the task of adjusting a baseline forecast for a number of retail stock keeping units to take into account a forthcoming promotion. Forecasting demand in advance of promotions carries a particular significance given their intensive supply chain repercussions and financial impact. Both statistical and qualitative information was provided through a forecasting support system typical of those found in practice. Our results show participants responding to the quantity of information made available, though with decreasing scale effects. In addition, various statistical cues (which are themselves extraneous) were illustrated to be particularly important, including the size and timing of the last observed promotion. Overall, participants appeared to use a compensatory strategy when combining information that had either positive or negative implications for the success of the promotions. However, there was a consistent bias towards underestimating the effect of the promotions. These observed biases have important implications for the design of organizational sales and operations planning processes and the forecasting support systems that such processes rely on

Use and misuse of information in supply chain forecasting of promotion events

Demand forecasting is a critical component of sales and operations planning (S&OP) and is pivotal in supporting inventory and production planning in supply chains. Because of their relative infrequency the effects of sales promotions can be particularly difficult to forecast - yet these are events where production and inventory planners need clear guidance on the probable uplifts in demand. A widely-documented practice involves judgmentally adjusting a baseline statistical forecast on receipt of shared information from sales, marketing and logistics. However, much of this information will either have no predictive value in estimating demand uplift resulting from the promotion or its predictive diagnosticity will be unknown. Theoretical arguments on ‘system neglect’ and ‘base rate discounting’ suggest that the provision of information with no or unknown diagnosticity would lead to the forecasters being distracted from the underlying base-rate uplift with deleterious effects on forecast accuracy. This study investigates this possibility when forecasters made judgmental adjustments to forecasts via a forecasting support system (FSS) in advance of forthcoming sales promotions. In experiments forecasters were provided with the mean rate of sales uplift achieved through promotions (the base rate), and a baseline statistical forecast, together with both quantitative and qualitative information relating to a range of products that were due to be promoted. The results revealed that forecasters were distracted from the base rate, misinterpreting the diverse information available to them, and this led to underestimates of the uplift achieved by the promotions. By extending earlier findings from field observation to a representative experimental setting, these findings have important implications for the quality of inventory decisions, for the design of organizational S&OP processes, and for the implementation of the FSSs that such processes rely on

Bridging the Distributor into a Collaborative Demand and Supply Planning Process

YesBased on their study of the food distribution supply chain, Can Eksoz and Dilek Önkal argue that the distributor has largely been overlooked in the principles we’ve created for collaborative demand and supply planning. Their article re-inserts the distributor into the supply chain and examines the challenges of collaboration from the distributor’s vantage point. This is a good lesson in how collaborative agreements must address the particular structures of the supply chain as well as the markets in which the supply-chain partners operate

Using scenarios to forecast outcomes of a refugee crisis

The Syrian civil war has led to millions of Syrians fleeing the country, and has resulted in a humanitarian crisis. By considering how such socio-political events may unfold, scenarios can lead to informed forecasts that can be used for decision-making. We examined the relationship between scenarios and forecasts in the context of the Syrian refugee crisis. Forty Turkish students trained to use a brainstorming technique generated scenarios that might follow within six months of the Turkish government banning Syrian refugees from entering the country. Participants generated from 3-6 scenarios. Over half were rated as ‘high’ quality in terms of completeness, relevance/pertinence, plausibility, coherence, and transparency (order effects). Scenario quality was unaffected by scenario quantity. Even though no forecasts were requested, participants’ first scenarios contained from 0-17 forecasts. Mean forecast accuracy was 45% and this was unaffected by forecast quantity. Therefore, brainstorming can offer a simple and quick way of generating scenarios and forecasts that can potentially help decision-makers tackle humanitarian crises

Expertise, credibility of system forecasts and integration methods in judgmental demand forecasting

YesExpert knowledge elicitation lies at the core of judgmental forecasting—a domain that relies fully on the power of such knowledge and its integration into forecasting. Using experts in a demand forecasting framework, this work aims to compare the accuracy improvements and forecasting performances of three judgmental integration methods. To do this, a field study was conducted with 31 experts from four companies. The methods compared were the judgmental adjustment, the 50–50 combination, and the divide-and-conquer. Forecaster expertise, the credibility of system forecasts and the need to rectify system forecasts were also assessed, and mechanisms for performing this assessment were considered. When (a) a forecaster’s relative expertise was high, (b) the relative credibility of the system forecasts was low, and (c) the system forecasts had a strong need of correction, judgmental adjustment improved the accuracy relative to both the other integration methods and the system forecasts. Experts with higher levels of expertise showed higher adjustment frequencies. Our results suggest that judgmental adjustment promises to be valuable in the long term if adequate conditions of forecaster expertise and the credibility of system forecasts are met

Evaluating expert advice in forecasting: users' reactions to presumed vs. experienced credibility

YesIn expert knowledge elicitation (EKE) for forecasting, the perceived credibility of an expert is likely to affect the weighting attached to their advice. Four experiments have investigated the extent to which the implicit weighting depends on the advisor’s experienced (reflecting the accuracy of their past forecasts), or presumed (based on their status) credibility. Compared to a control group, advice from a source with a high experienced credibility received a greater weighting, but having a low level of experienced credibility did not reduce the weighting. In contrast, a high presumed credibility did not increase the weighting relative to a control group, while a low presumed credibility decreased it. When there were opportunities for the two types of credibility to interact, a high experienced credibility tended to eclipse the presumed credibility if the advisees were non-experts. However, when the advisees were professionals, both the presumed and experienced credibility of the advisor were influential in determining the weight attached to the advice

Technology as a disruptive agent: Intergenerational perspectives

YesThis study explores how British South Asian parents perceive their children’s technology consumption through their collectivist lenses and interdependent values. The findings for this qualitative study indicate that second and third generation South Asian parents acknowledge the benefits of children’s technology use; but largely perceive technology as a disruptive agent, whereby children are becoming isolated and increasingly independent within the household. The analysis aims to understand how parents view their children’s relationship with others as a result of technology consumption. Accordingly, this paper proposes an extension of the Construal of self conceptualisation and contributes a Techno-construal matrix that establishes a dyadic connection between technology consumption and cultural values. Overall, the study reveals that children display less inter-reliance and conformance typically associated with collectivist cultures, resulting from their technology use. Consequently, parents interpret their children’s shift from interdependence to more independence as a disruptive and unsettling phenomenon within the household