SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models

Bindu Narayan, Deepak Ravindran, Picton Sue, Jayant Das Pattnaik

2012

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.

References

  1. Tom, Snyder. 2006. White Paper, Rational Forecasting. Martin, Lewis. 2009. Webinar, Principal, 3g Selling.
  2. Gilmore, Lewis. 2006. White Paper, How To Develop An Effective Sales Forecast.
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Paper Citation


in EndNote Style

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


in Harvard Style

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


in Bibtex Style

@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},
}