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Authors: Bindu Narayan ; Deepak Ravindran ; Picton Sue and Jayant Das Pattnaik

Affiliation: Hewlett Packard and Global e-Business Operations, India

ISBN: 978-989-8425-97-3

Keyword(s): Sales Pipeline, Predictive model, Time Series, Seasonality.

Related Ontology Subjects/Areas/Topics: Forecasting ; Methodologies and Technologies ; Operational Research

Abstract: Sales pipeline metaphorically is a pipe through which the opportunities pass on the way to becoming a sale. As the opportunity progresses through the pipe the likelihood of becoming a sale increases. Predicting the sales pipeline is very critical. Accurately predicting the sales pipeline is essential in planning future costs and capacity requirements. Since the sales pipeline is in itself a subjective prediction made by sales reps, predicting the pipeline essentially becomes a problem of predicting a prediction. Most managers do this by solely depending on their sales representatives perception on which business will close. A prediction model was developed using time series modeling to predict the next quarter sales pipeline. The uniqueness of the model is that, it captures two different types of co-existing seasonlaities. A predictive model was created which is refreshed weekly with actual pipeline numbers and is successfully deployed within business.

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Paper citation in several formats:
Narayan, B.; Ravindran, D.; Sue, P. and Das Pattnaik, J. (2012). SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models.In Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-8425-97-3, pages 114-119. DOI: 10.5220/0003716201140119

@conference{icores12,
author={Bindu Narayan. and Deepak Ravindran. and Picton Sue. and Jayant Das Pattnaik.},
title={SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models},
booktitle={Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2012},
pages={114-119},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003716201140119},
isbn={978-989-8425-97-3},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models
SN - 978-989-8425-97-3
AU - Narayan, B.
AU - Ravindran, D.
AU - Sue, P.
AU - Das Pattnaik, J.
PY - 2012
SP - 114
EP - 119
DO - 10.5220/0003716201140119

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